Supply Chain Management and Mathematical Logistics

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Financial Mathematics".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 38699

Special Issue Editors


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Guest Editor
School of Business, Central South University, Yuelu District, Changsha 410083, China
Interests: game theory and application; decision analysis; supply chain and logistics management; business big data analysis
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Business, Central South University, Yuelu District, Changsha 410083, China
Interests: logistics and supply chain management; operation management and service science; e-commerce and marketing science; big data business intelligence analysis; fintech, supply chain finance

Special Issue Information

Dear Colleagues,

The function of supply chain management is to design and manage the processes, assets, and flows of material and information required to satisfy customers’ demands. The globalization of economy and electronic commerce has heightened the strategic importance of supply chain management. E-logistics has created new distribution channels for consumers. The last decade has seen rapid growth in business models built around digital platforms that bring together buyers and sellers to interact and trade in new and innovative ways. These business models, referred to as the sharing economy, on-demand economy, and platform economy, bring new challenges to supply chain management and logistics. The COVID-19 pandemic has profoundly affected the stability of global logistics and supply chains. Rapid advances and complexity in digital technology such as big data, cloud computing, blockchain, and artificial intelligence (AI), and the growing uncertainty in the global business environment, have had a profound impact on the development of supply chain management and logistics. The global economy and advanced digital technologies have also generated unprecedented opportunities for innovative methodologies and technologies for designing, operating, and managing supply chains and logistics.

This Special Issue aims to collate original research papers that offer the latest developments and applications of supply chain management and logistics in a broad range of fields.

Prof. Dr. Chunqiao Tan
Prof. Dr. Xiongwei Zhou
Guest Editors

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Keywords

  • sustainable supply chain
  • green supply chain
  • low-carbon supply chain
  • closed-loop supply chain
  • omni-channel supply chain
  • low-carbon logistics
  • supply chain agility
  • supply chain adaptability
  • dynamic supply chain alignment
  • supply chain resilience
  • mathematical logistics
  • game theory
  • contract design
  • information economy
  • marketing
  • big data
  • blockchain
  • artificial intelligence
  • platform economy
  • on-demand economy
  • sharing economy
  • digital economy
  • multiple-criteria decision-making

Published Papers (19 papers)

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Research

16 pages, 2433 KiB  
Article
Optimal Circular Economy and Process Maintenance Strategies for an Imperfect Production–Inventory Model with Scrap Returns
by Rung-Hung Su, Ming-Wei Weng, Chih-Te Yang and Chia-Hsuan Hsu
Mathematics 2023, 11(14), 3041; https://doi.org/10.3390/math11143041 - 8 Jul 2023
Cited by 1 | Viewed by 1050
Abstract
To protect our environment, current firms are committed to the circular economy and process maintenance strategies to reduce the waste of resources. In this way, they can also save costs and create an enterprise image and value. Therefore, this study explores an imperfect [...] Read more.
To protect our environment, current firms are committed to the circular economy and process maintenance strategies to reduce the waste of resources. In this way, they can also save costs and create an enterprise image and value. Therefore, this study explores an imperfect production system with a circular economy and process maintenance activities, wherein the defective products can be converted into scrap returns (i.e., secondary raw materials) and products can be manufactured using mixed materials containing scrap returns. The proposed system considers multiple products with varying feed rates of scrap returns. According to the scenario of the aforementioned production system, this paper develops a production–inventory model aimed at cost minimization, in which the production run time, purchased quantity of material, number of maintenance times, and recovery rate are decision variables. Furthermore, we also develop a computational algorithm to obtain these optimal solutions efficiently. Finally, the numerical and sensitivity analyses based on a practical case are presented to illustrate the applicability of our method and some managerial implications. For example, both strategies efficiently reduce the total cost per unit time in the proposed numerical example. The sensitivity results can be used to determine the optimal combination of two strategies and the execution moment under various changes in cost parameters. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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29 pages, 1258 KiB  
Article
Research on a Dynamic Task Update Assignment Strategy Based on a “Parts to Picker” Picking System
by Kaibo Liang, Li Zhou, Jianglong Yang, Huwei Liu, Yakun Li, Fengmei Jing, Man Shan and Jin Yang
Mathematics 2023, 11(7), 1684; https://doi.org/10.3390/math11071684 - 31 Mar 2023
Cited by 4 | Viewed by 1768
Abstract
Order picking is a crucial operation in the storage industry, with a significant impact on storage efficiency and cost. Responding quickly to customer demands and shortening picking time is crucial given the random nature of order arrival times and quantities. This paper presents [...] Read more.
Order picking is a crucial operation in the storage industry, with a significant impact on storage efficiency and cost. Responding quickly to customer demands and shortening picking time is crucial given the random nature of order arrival times and quantities. This paper presents a study on the order-picking process in a distribution center, employing a “parts-to-picker” system, based on dynamic order batching and task optimization. Firstly, dynamic arriving orders with uncertain information are transformed into static picking orders with known information. A new method of the hybrid time window is proposed by combining fixed and variable time windows, and an order consolidation batch strategy is established with the aim of minimizing the number of target shelves for picking. A heuristic algorithm is designed to select a shelf selection model, taking into account the constraint condition that the goods on the shelf can meet the demand of the selection list. Subsequently, task division of multi-AGV is carried out on the shelf to be picked, and the matching between the target shelf and the AGVs, as well as the order of the AGVs to complete the task of picking, is determined. A scheduling strategy model is constructed to consider the task completion time as the incorporation of moving time, queuing time, and picking time, with the shortest task completion time as the objective function and AGV task selection as the decision variable. The improved ant colony algorithm is employed to solve the problem. The average response time of the order batching algorithm based on a hybrid time window is 4.87 s, showing an improvement of 22.20% and 40.2% compared to fixed and variable time windows, respectively. The convergence efficiency of the improved ant colony algorithm in AGV task allocation is improved four-fold, with a better convergence effect. By pre-selecting the nearest picking station for the AGVs, the multi-AGV picking system can increase the queuing time. Therefore, optimizing the static picking station selection and dynamically selecting the picking station queue based on the queuing situation are proposed. The Flexsim simulation results show that the queue-waiting and picking completion times are reduced to 34% of the original, thus improving the flexibility of the queuing process and enhancing picking efficiency. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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16 pages, 566 KiB  
Article
Deterring Sellers’ Cheap Talk Actions via Online Rating Schemes
by Meijian Yang, Enjun Xia and Yang Yang
Mathematics 2023, 11(6), 1304; https://doi.org/10.3390/math11061304 - 8 Mar 2023
Viewed by 839
Abstract
This paper develops a two-period game theoretic model to investigate a seller’s quality claims in a cheap-talk setting. In this model, consumers are reference-dependent with respect to product quality, and consumers who have purchased items can share their quality assessments via online ratings; [...] Read more.
This paper develops a two-period game theoretic model to investigate a seller’s quality claims in a cheap-talk setting. In this model, consumers are reference-dependent with respect to product quality, and consumers who have purchased items can share their quality assessments via online ratings; additionally, consumers may be naive or experienced: naive consumers simply believe the quality claims and quality assessments, whereas experienced consumers can accordingly make rational quality inferences. We find that, in the scenario with only naive consumers, when the reference effect is weak, the seller will always claim the highest quality; when the reference effect is strong, the low-quality seller will claim the highest quality, whereas the high-quality seller will understate its products’ quality. In the scenario with only experienced consumers, the seller will claim some moderate quality levels. In the scenario with both types of consumers, in period one, the low-quality seller will always claim some moderate quality levels to serve both types of consumers, whereas the high-quality seller will claim the highest quality when the reference effect is extremely weak and thus serve only naive consumers, or it will adopt truth-telling otherwise; in period two, the low-quality seller will charge a higher price to serve only experienced consumers, whereas the high-quality seller will charge a lower price to serve both types of consumers. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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14 pages, 321 KiB  
Article
LNG Bunkering Station Deployment Problem—A Case Study of a Chinese Container Shipping Network
by Jingwen Qi and Shuaian Wang
Mathematics 2023, 11(4), 813; https://doi.org/10.3390/math11040813 - 5 Feb 2023
Cited by 5 | Viewed by 1321
Abstract
Liquefied natural gas (LNG) is a promising measure to reduce shipping emissions and alleviate air pollution problem, especially in coastal areas. Currently, the lack of a complete infrastructure system is preventing the extensive application of dual-fueled ships that are mainly LNG-powered. Given that [...] Read more.
Liquefied natural gas (LNG) is a promising measure to reduce shipping emissions and alleviate air pollution problem, especially in coastal areas. Currently, the lack of a complete infrastructure system is preventing the extensive application of dual-fueled ships that are mainly LNG-powered. Given that groups of LNG bunkering stations are under establishment in various countries and areas, the construction plan becomes critical. In this paper, we focus on the LNG bunkering station deployment problem, which identifies the locations of the stations to be built. A large-scale case study of China’s container shipping network was conducted. The problem scale of this case paper exceeds those in previous academic studies. Thus, this study better validates the model and solution method proposed than numerical experiments that are randomly generated. Sensitive analyses on the LNG price, bunkering station construction costs, and total budget were carried out. The results yielded provide practical suggestions and managerial insights for the competent department. In addition to building a complete bunkering system, subsidies to ship operators for consuming LNG and higher production efficiency in bunkering station construction also help promote the application of LNG as marine fuel. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
18 pages, 3731 KiB  
Article
An Innovative Blockchain-Based Secured Logistics Management Architecture: Utilizing an RSA Asymmetric Encryption Method
by Nwosu Anthony Ugochukwu, S. B. Goyal, Anand Singh Rajawat, Sardar M. N. Islam, Jiao He and Muhammad Aslam
Mathematics 2022, 10(24), 4670; https://doi.org/10.3390/math10244670 - 9 Dec 2022
Cited by 10 | Viewed by 2570
Abstract
Purpose: The recent development in logistics due to the dawn of Logistics 4.0 has made global logistics providers more dependent on intelligent technologies. In this era, these technologies assist in data collection and transmission of logistical data and pose many security and privacy [...] Read more.
Purpose: The recent development in logistics due to the dawn of Logistics 4.0 has made global logistics providers more dependent on intelligent technologies. In this era, these technologies assist in data collection and transmission of logistical data and pose many security and privacy threats in logistics management systems. The customer’s private information, which is shared among the logistics stakeholders for optimal operation, faces unauthorized access due to a lack of privacy. This, amongst others, is a critical problem that needs to be addressed with blockchain. Blockchain is a disruptive technology that is transforming different sectors, and it has the potential to provide a solution to the issues mentioned above, with its unique features such as immutability, transparency, and anonymity. Method: This study designed a blockchain-based logistics management architecture on a decentralized peer-2-peer network using Ethereum smart contracts. The proposed system deployed the Rivest–Shamir–Adleman (RSA) asymmetric encryption method to protect the logistics system from cyber-attacks and secure customers’ private information from unauthorized access. Findings: Furthermore, the security and privacy of the proposed system are evaluated based on the theorem. The proof shows that the system can provide security to the logistics system and privacy to customers’ private data. The performance evaluation is based on throughput and latency. It shows that the proposed system is better than the baseline system, and the comparatives analysis shows that the proposed system is more secure and efficient than the existing systems. Implication and Limitation: The proposed system offers a better solution to the security/privacy of the logistics management system and provides recommendations to key stakeholders involved in the logistics industry while adopting blockchain technology. Apart from the study’s methodological limitation, it is also limited by a lack of reference materials. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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32 pages, 4948 KiB  
Article
Omnichannel Retail Strategy Considering Cost-Sharing and Consumer Heterogeneity under Different Power Structures
by Yande Gong, Yidan Ma and Zhe Wang
Mathematics 2022, 10(21), 4004; https://doi.org/10.3390/math10214004 - 28 Oct 2022
Cited by 2 | Viewed by 1517
Abstract
This paper explores two Omnichannel retail models consisted of one online platform and one brick-and-mortar store under different power structures considering cost-sharing mechanisms. In retail supply chain dominated by the online platform and brick-and-mortar store, respectively, under a “Buy online and pick up [...] Read more.
This paper explores two Omnichannel retail models consisted of one online platform and one brick-and-mortar store under different power structures considering cost-sharing mechanisms. In retail supply chain dominated by the online platform and brick-and-mortar store, respectively, under a “Buy online and pick up in store” strategy, the influences of the cost-sharing ratio and the proportion of traditional consumers on pricing and service decisions, the demands of various groups of consumers, and the performance of the retail system have been examined. In addition, the results of decision-making and profitabilities of retailers under different power structures have also been considered. The key findings show that the optimal price and service level first increase and then decrease with the cost-sharing ratio in a retail system dominated by the online platform. In contrast, the price and service level increase with the cost-sharing ratio only when the proportion of traditional consumers is relatively large in a retail system dominated by brick-and-mortar store. The symmetry demand increases as the scale of traditional consumers shrinks when the cost-sharing ratio is relatively large in a retail system dominated by the online system. At the same time, it only increases when the cost-sharing ratio is in the range of 5/8,5/6 in a retail system dominated by the brick-and-mortar store. No matter what the power structure is, the profit of the retail system always first increases and then decreases with the proportion of traditional consumers. Additionally, when the cost-sharing ratio and the proportion of traditional consumers are relatively small, the total demand in the retail system dominated by the online platform is higher than that in the retail system dominated by the brick-and-mortar store. The total profit is larger in the online platform-dominated retail system than that in the brick-and-mortar store-dominated retail system when the cost-sharing ratio is relatively high. However, when the cost-sharing ratio is relatively low, the profitability of the brick-and-mortar store-dominated retail system is stronger. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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19 pages, 786 KiB  
Article
Planning, Execution, and Control of Operations in SC Activities—Baja California Manufacturing Case Study
by Rubén Jesús Pérez-López, María Mojarro-Magaña, Jesús Everardo Olguín-Tiznado, Claudia Camargo-Wilson, Juan Andrés López-Barreras, Julio Cesar Cano Gutiérrez and Jorge Luis Garcia-Alcaraz
Mathematics 2022, 10(19), 3468; https://doi.org/10.3390/math10193468 - 23 Sep 2022
Cited by 1 | Viewed by 1089
Abstract
This paper reports a second order structural equation model (SEM) with four latent variables and six hypotheses to analyze the Planning, Execution, and Control of the information and communication technologies (ICT) implementation in supply chains (SC) and the operational Benefits obtained. [...] Read more.
This paper reports a second order structural equation model (SEM) with four latent variables and six hypotheses to analyze the Planning, Execution, and Control of the information and communication technologies (ICT) implementation in supply chains (SC) and the operational Benefits obtained. The model is validated with information obtained from 80 responses to a questionnaire applied direct to manufacturing companies in Baja California state (Mexico), specifically in Ensenada, Mexicali, Tecate, and Tijuana municipalities. The variables are statistically validated using the Cronbach’s alpha index for internal and R-squared for predictive validity. Partial least squares algorithms are used to validate the model’s hypotheses in software WarpPLS version7.0 ScripWarp Systems, Laredo, TX, US. Findings indicate that the direct impact of Execution and Control is positive and therefore are the basis for successful integration of ICT and obtaining agility and flexibility benefits in the SC. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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23 pages, 1888 KiB  
Article
Research on Manufacturers’ Referral Strategy Considering Store Brand Retailers and Traditional Retailers
by Feiyan Han, Herui Wang, Hongyu Lv and Bo Li
Mathematics 2022, 10(18), 3326; https://doi.org/10.3390/math10183326 - 14 Sep 2022
Viewed by 1243
Abstract
It has become a common commercial phenomenon for retailers to establish their own brands. The manufacturer referral strategy is studied through a model which includes a manufacturer, a traditional retailer and a store brand retailer. We conduct research on the three cooperation methods [...] Read more.
It has become a common commercial phenomenon for retailers to establish their own brands. The manufacturer referral strategy is studied through a model which includes a manufacturer, a traditional retailer and a store brand retailer. We conduct research on the three cooperation methods of the manufacturer: “no information referral”, “exclusive referral” and “nonexclusive referral”. The equilibrium wholesale price, the manufacturer’s order quantity and the retailer’s own product output are studied by constructing game models, and the best referral cooperation choice between the manufacturer and the retailer is analysed according to their profit. The results show that the manufacturer’s referral level choice does not change the number of products, while the manufacturer’s market loss rate leads to a change in product order quantity among different choices. Under the combined effect of the market loss rate and the intensity of market competition, the store brand retailer will change the output decision of its own products. When the market loss rate meets a certain range, the manufacturer’s product sales can be maximized. For the manufacturer, any referral strategy is better than no referral strategy, and in most cases, the manufacturer prefers nonexclusive referrals. The traditional retailer is willing to accept the manufacturer’s referral cooperation, and the traditional retailer’s profit is better under the nonexclusive referrals; while most store brand retailers are willing to choose the nonexclusive referrals. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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28 pages, 3965 KiB  
Article
Performance Analysis of Picking Routing Strategies in the Leaf Layout Warehouse
by Li Zhou, Huwei Liu, Junhui Zhao, Fan Wang and Jianglong Yang
Mathematics 2022, 10(17), 3149; https://doi.org/10.3390/math10173149 - 2 Sep 2022
Cited by 2 | Viewed by 2237
Abstract
The routing strategy for order picking is an important factor in the efficiency of warehouse picking, and improvements to the warehouse layout provide more routing options for picking. The number of storage locations to be visited during the picking operation also has an [...] Read more.
The routing strategy for order picking is an important factor in the efficiency of warehouse picking, and improvements to the warehouse layout provide more routing options for picking. The number of storage locations to be visited during the picking operation also has an impact on the selection of routing strategies. In order to achieve an effective improvement in the efficiency of picking operations in warehouse distribution centers, this paper focuses on the leaf warehouse layout based on the previous single-command operation strategy and extends it to study the multi-command operation strategy, in which three heuristic routing strategies, the S-shape, the return, and the composite, are introduced to solve the walking distance problem of picking operations, with the study of the selection of the routing strategy for different numbers of storage locations to be visited. Based on the distance equation between any two storage locations to be visited in the leaf layout warehouse, travel distance models corresponding to the three routing strategies in the picking operation are constructed, and the cuckoo search algorithm is introduced to solve and calculate the travel distance of the composite strategies for the experiments. In addition, the computational experiments of the three path strategies are carried out according to the different numbers of storage locations to be visited in the picking operation. By analyzing the numerical results, we find that the composite strategy has the best overall results among the three routing strategies, with the average values of optimization rates exceeding 30% (the S-shape) and 40% (the return), respectively. At the same time, the return strategy outperforms the S-shape strategy when the number of locations to be visited is less than seven. As the number of locations to be visited increases, the S-shape strategy gradually outperforms the return strategy. From a managerial and practical perspective, compared to the single-command operation strategy that is the focus of the current research, the multi-command operation strategy we studied is more relevant to the actual situation of order merging picking in warehouses and can effectively improve the efficiency of picking operations, the competitiveness of enterprises, and customer satisfaction of e-commerce enterprises. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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37 pages, 599 KiB  
Article
Analysis of Stochastic M/M/c/N Inventory System with Queue-Dependent Server Activation, Multi-Threshold Stages and Optional Retrial Facility
by T. Harikrishnan, K. Jeganathan, S. Selvakumar, N. Anbazhagan, Woong Cho, Gyanendra Prasad Joshi and Kwang Chul Son
Mathematics 2022, 10(15), 2682; https://doi.org/10.3390/math10152682 - 29 Jul 2022
Cited by 1 | Viewed by 1530
Abstract
The purpose of this article is to examine the server activation policy (SAP) in a multi-server queuing-inventory system (MQIS). The queue has a total of c number of multi-threshold stages as well as c-homogeneous servers. The activation of each server begins one [...] Read more.
The purpose of this article is to examine the server activation policy (SAP) in a multi-server queuing-inventory system (MQIS). The queue has a total of c number of multi-threshold stages as well as c-homogeneous servers. The activation of each server begins one by one if there is an adequate queue length and inventory in the system; otherwise, they remain idle. The server deactivation process continues until the queue length exceeds the manageable level (predetermined stages) or there is insufficient stock. In addition, when we assume the length of the two successive threshold levels is one, the server activation policy model becomes a regular multi-server model. The Neuts matrix geometric approach is used to discuss the stability condition, stationary probability vector. The Laplace–Stieltjes transform (LST) is used to analyse the waiting time distributions of the queue and orbital customers. Additionally, significant system performance metrics and sensitivity analysis are used to investigate the effects of various parameters and cost values. In the comparative result between the server activation model (SAM) and without the server activation model (WSAM) on the expected total cost, we obtain the minimised cost in the SAM. Moreover, the results are obtained by assuming that the length of the intervals between the two successive threshold levels is to be taken into account as the non-uniform length. The expected inventory level, reorder rate, and waiting time of a customer in the waiting hall and orbit were explored numerically by the parameter analysis. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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23 pages, 3344 KiB  
Article
Decisions for Blockchain Adoption and Information Sharing in a Low Carbon Supply Chain
by Tianjian Yang, Chunmei Li, Xiongping Yue and Beibei Zhang
Mathematics 2022, 10(13), 2233; https://doi.org/10.3390/math10132233 - 26 Jun 2022
Cited by 11 | Viewed by 2427
Abstract
Enterprises in low-carbon supply chains have been exploring blockchain technology in order to make carbon data transparent. However, there is still some opaque information in the market, such as the value-added service efficiency. How do supply chain members make decisions between information sharing [...] Read more.
Enterprises in low-carbon supply chains have been exploring blockchain technology in order to make carbon data transparent. However, there is still some opaque information in the market, such as the value-added service efficiency. How do supply chain members make decisions between information sharing and blockchain adoption? This study considers blockchain adoption and information sharing in a low-carbon supply chain with a single manufacturer and a single retailer. The retailer has private information about value-added services and decides how to share it with the manufacturer. We examine six combined strategies comprised of blockchain scenarios and information sharing formats (no sharing, voluntary sharing, and mandatory sharing). The results indicate that supply chain members prefer blockchain technology under no sharing and voluntary sharing. Under mandatory sharing, supply chain members have incentives to participate in blockchain when the value-added service efficiency exceeds a threshold value. While the manufacturer prefers to obtain the value-added service information, the retailer decides to share information depending on the value-added service efficiency. Besides, supply chain members’ attitude toward the sharing contract also depends on the value-added service efficiency. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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21 pages, 1583 KiB  
Article
Information Disclosure Decision for Tourism O2O Supply Chain Based on Blockchain Technology
by Li Zhou, Chunqiao Tan and Huimin Zhao
Mathematics 2022, 10(12), 2119; https://doi.org/10.3390/math10122119 - 17 Jun 2022
Cited by 6 | Viewed by 1739
Abstract
(1) Background: With the development of blockchain technology and fierce competition between tourism platforms, tourism platforms can adopt blockchain technology to disclose product information to enhance their core competitiveness. As for a tourism O2O, i.e., online to offline, supply chain, the tourism platform [...] Read more.
(1) Background: With the development of blockchain technology and fierce competition between tourism platforms, tourism platforms can adopt blockchain technology to disclose product information to enhance their core competitiveness. As for a tourism O2O, i.e., online to offline, supply chain, the tourism platform sells the product online, and the tour operator provides services offline. (2) Methods: We establish a game theory model and study the optimal strategies of supply chain members in two scenarios (decentralized and centralized) when the online platform does not adopt or adopts blockchain technology. Then, we introduce a two-part tariff contract for coordination. Furthermore, we discuss the impact of the cost of adopting blockchain technology, disclosing information and the proportion of information-sensitive consumers on the optimal strategies. (3) Conclusions: When the costs of adopting blockchain technology and information disclosure are low, if the proportion of information-sensitive consumers is large, adopting blockchain technology is beneficial to supply chain members. Compared with a wholesale price contract, a two-part tariff contract can encourage the platform to improve information disclosure quality, so the tour operator can adjust their cooperation contract to achieve Pareto improvements. Under a two-part tariff contract, the tourism platforms are more likely to disclose information and can effectively regulate the operational performance of the tourism O2O supply chain. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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18 pages, 2312 KiB  
Article
The Differential Game of a Closed-Loop Supply Chain with Manufacturer Competition Considering Goodwill
by Lang Liu, Lulu Wang, Taisheng Huang and Jinhui Pang
Mathematics 2022, 10(11), 1795; https://doi.org/10.3390/math10111795 - 24 May 2022
Cited by 4 | Viewed by 1405
Abstract
The dynamic optimization of the closed-loop supply chain (CLSC) is a hot research topic. Members’ competitive behavior and product goodwill play an important role in the decision making of CLSC members. In this paper, a closed-loop supply chain (CLSC) with competitive manufacturers and [...] Read more.
The dynamic optimization of the closed-loop supply chain (CLSC) is a hot research topic. Members’ competitive behavior and product goodwill play an important role in the decision making of CLSC members. In this paper, a closed-loop supply chain (CLSC) with competitive manufacturers and single retailers is studied, in which the manufacturer produces and recycles the products, and the retailer is responsible for the sales of the products. On this basis, a dynamic linear differential equation of product goodwill is constructed, the optimal dynamic path of each decision variable is found, and the influence of price competition among manufacturers on the decision making of members in a dynamic closed-loop supply chain is studied. The conclusion is verified by an example. The results show that goodwill directly affects the wholesale price, the retail price, the recovery price, and the profit of supply chain members. The wholesale price and the retail price of products are not only positively affected by their own goodwill, but also by the goodwill of competing products. The manufacturer competition intensity will affect the product price and the supply chain member profit. To a certain extent, the more intense the manufacturer’s competition is, the higher the wholesale price and the retail price, and the greater the profit of the supply chain members. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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30 pages, 8317 KiB  
Article
Capacity-Oriented Train Scheduling of High-Speed Railway Considering the Operation and Maintenance of Rolling Stock
by Wenliang Zhou, Sha Li, Jing Kang and Yu Huang
Mathematics 2022, 10(10), 1639; https://doi.org/10.3390/math10101639 - 11 May 2022
Cited by 2 | Viewed by 1553
Abstract
The capacity of some busy rail lines is increasingly tight and passenger demand far exceeds the railway capacity. To schedule as many trains as possible in order to satisfy more transportation demands, we studied the capacity-oriented train scheduling problem. While most approaches focus [...] Read more.
The capacity of some busy rail lines is increasingly tight and passenger demand far exceeds the railway capacity. To schedule as many trains as possible in order to satisfy more transportation demands, we studied the capacity-oriented train scheduling problem. While most approaches focus only on increasing the capacity of the rail line, this research considers both the time-space distribution of transportation demands and the operation and maintenance of rolling stock. To solve this problem, we first constructed a time-space network to describe the time-space path of rolling stock. We then proposed an integer planning model with rolling stock maintenance and the OD service frequency constraints to maximize the number of running arcs in rail sections. After decomposing this model by introducing some Lagrangian multipliers to relax its hard constraints, we proposed a Lagrangian relaxation-based decomposition algorithm, including two path search sub-algorithms for rolling stock to optimize both the relaxed and the feasible solutions. Finally, we conducted a computation study on a practical double-track high-speed railway line to test the performance of this algorithm. It reports that the train timetables and the operation of rolling stock are well managed. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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35 pages, 4321 KiB  
Article
Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework
by Chih-Hung Hsu, Ming-Ge Li, Ting-Yi Zhang, An-Yuan Chang, Shu-Zhen Shangguan and Wan-Ling Liu
Mathematics 2022, 10(8), 1233; https://doi.org/10.3390/math10081233 - 9 Apr 2022
Cited by 21 | Viewed by 4058
Abstract
In the face of global competition, competitive enterprises should pursue sustainable development, and strengthen their supply chain resilience to cope with risks at any time. In addition, big data analysis has been successfully applied in a variety of fields. However, the method has [...] Read more.
In the face of global competition, competitive enterprises should pursue sustainable development, and strengthen their supply chain resilience to cope with risks at any time. In addition, big data analysis has been successfully applied in a variety of fields. However, the method has not been applied to improve supply chain resilience in order to reduce sustainable supply chain risks. An approach for enhancing the capabilities of big data analytics must be developed to enhance supply chain resilience, and mitigate sustainable supply chain risks. In this study, a decision framework that integrates two-stage House of Quality and multicriteria decision-making was constructed. By applying this framework, enterprise decision-makers can identify big data analytics that improve supply chain resilience, and resilience indicators that reduce sustainable supply chain risks. A case study of one of China’s largest relay manufacturers is presented to demonstrate the practicability of the framework. The results showed that the key sustainable supply chain risks are risks regarding the IT infrastructure and information system efficiency, customer supply disruptions, transport disruptions, natural disasters, and government instability. To reduce risk in sustainable supply chains, enterprises must improve the key resilience indicators ‘financial capability’, ‘flexibility’, ‘corporate culture’, ‘information sharing’, and ‘robustness’. Moreover, to increase supply chain resilience, the following most important big data analysis enablers should be considered: ‘capital investment’, ‘building big data sharing mechanism and visualisation’, and ‘strengthening big data infrastructures to support platforms and systems’. This decision framework helps companies prioritise big data analysis enablers to mitigate sustainable supply chain risks in manufacturing organisations by strengthening supply chain resilience. The identified priorities will benefit companies that are using big data strategies and pursuing supply chain resilience initiatives. In addition, the results of this study show the direction of creating a fruitful combination of big data technologies and supply chain resilience to effectively mitigate sustainable risks. Despite the limited enterprise resources, management decision-makers can determine where big data analysis enablers can be most cost-effectively improved to promote risk resilience of sustainable supply chains; this ensures the efficient implementation of effective big data strategies. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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16 pages, 2143 KiB  
Article
The Ordering Optimization Model for Bounded Rational Retailer with Inventory Transshipment
by Qingren He, Taiwei Shi, Botao Liu and Wanhua Qiu
Mathematics 2022, 10(7), 1079; https://doi.org/10.3390/math10071079 - 28 Mar 2022
Cited by 3 | Viewed by 1634
Abstract
In order to study retailers’ ordering behavior deviating from the standard theoretical optimal decision, which is caused by retailers’ information asymmetry, cognitive ability, insufficient computing ability, and other factors, we construct a bounded-rationality choice model with quantal response equilibrium. First, the existence and [...] Read more.
In order to study retailers’ ordering behavior deviating from the standard theoretical optimal decision, which is caused by retailers’ information asymmetry, cognitive ability, insufficient computing ability, and other factors, we construct a bounded-rationality choice model with quantal response equilibrium. First, the existence and uniqueness of quantal response equilibrium of transshipment game have been proved with the transshipment price satisfying certain conditions. Then, the numerical example demonstrates that with the increase of bounded-rationality parameters, retailers’ quantal response equilibrium will converge to Nash equilibrium due to the learning effect, and their profits will converge to the profits predicted by standard theory. Finally, the results show that retailers are more averse to the explicit loss of shortage than to the implicit loss of inventory surplus caused by the increase of order quantity. Hence, retailers tend to overorder to avoid loss of shortage. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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18 pages, 3457 KiB  
Article
Performance Analysis of Picking Path Strategies in Chevron Layout Warehouse
by Huwei Liu, Fan Wang, Junhui Zhao, Jianglong Yang, Chunqiao Tan and Li Zhou
Mathematics 2022, 10(3), 395; https://doi.org/10.3390/math10030395 - 27 Jan 2022
Cited by 7 | Viewed by 3077
Abstract
Order picking is the part with the highest proportion of operation cost and time in the warehouse. The characteristics of small-batch and multi-frequency current orders reduce the applicability of the traditional layout in the warehouse. Besides this, the improvement of the layout will [...] Read more.
Order picking is the part with the highest proportion of operation cost and time in the warehouse. The characteristics of small-batch and multi-frequency current orders reduce the applicability of the traditional layout in the warehouse. Besides this, the improvement of the layout will also affect the picking path, such as the Chevron warehouse layout, and at present, there is a lack of research on order picking with multiple picking locations under non-traditional layouts. In order to minimize the order picking cost and time, and expand the research in this field, this paper selects the Chevron layout to design and describe the warehouse layout, constructs the picking walking distance model of Return-type, S-type and Mixed-type path strategies in the random storage Chevron layout warehouse, and uses the Cuckoo Search (CS) algorithm to solve the picking walking distance generated by the Mixed-type path. Compared with the existing single-command order picking research, the order picking problem of multi picking locations is more suitable for the reality of e-commerce warehouses. Moreover, numerical experiments are carried out on the above three path strategies to study the impact of different walking paths on the picking walking distance, and the performance of different path strategies is evaluated by comparing the order picking walking distance with the different number of locations to be picked. The results show that, among the three path strategies, the Mixed-type path strategy is better than the Return-type path strategy, and the average optimization proportion is higher than 20%. When the number of locations to be picked is less than 36, the Mixed-type path is better than the S-type path. With the increase of the number of locations to be picked, the Mixed-type path is gradually worse than the S-type path. When the number of locations to be picked is less than 5, the Return-type path is better than the S-type path. With the increase of the number of locations to be picked in the order, the S-type path is gradually better than the Return-type path. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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22 pages, 4230 KiB  
Article
Incorporating ‘Mortgage-Loan’ Contracts into an Agricultural Supply Chain Model under Stochastic Output
by Liurui Deng, Shuge Wang, Yixuan Wen and Yuting Li
Mathematics 2022, 10(1), 85; https://doi.org/10.3390/math10010085 - 27 Dec 2021
Cited by 9 | Viewed by 2449
Abstract
This paper constructs an internal financing model in which the purchaser acts as the core leading enterprise to provide loans when the farmer has fixed assets as collateral. Numerical results show that the existence of fixed assets will increase the expected profit of [...] Read more.
This paper constructs an internal financing model in which the purchaser acts as the core leading enterprise to provide loans when the farmer has fixed assets as collateral. Numerical results show that the existence of fixed assets will increase the expected profit of the farmer, redistributing the risk and profit between the purchaser and the farmer. At the same time, the purchaser and the government are encouraged to provide more funds to the farmer with low value of its fixed assets, which will aid the overall return of the supply chain and the development of supply chain finance. In addition, under the framework of this model, the increase of agricultural production is beneficial to the farmer, not the purchaser. In the case of the same output level, we can alleviate this problem by selecting high-end agricultural products with high price elasticity of demand and high choking price so as to improve the profits of both purchaser and farmer. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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26 pages, 2568 KiB  
Article
Green Supply Chain Management with Nash Bargaining Loss-Averse Reference Dependence
by Wentao Yi, Zhongwei Feng, Chunqiao Tan and Yuzhong Yang
Mathematics 2021, 9(24), 3154; https://doi.org/10.3390/math9243154 - 8 Dec 2021
Cited by 3 | Viewed by 2081
Abstract
This paper investigates a two-echelon green supply chain (GSC) with a single loss-averse manufacturer and a single loss-averse retailer. Since the Nash bargaining solution exactly characterizes endogenous power and the contribution of the GSC members, it is introduced as the loss-averse reference point [...] Read more.
This paper investigates a two-echelon green supply chain (GSC) with a single loss-averse manufacturer and a single loss-averse retailer. Since the Nash bargaining solution exactly characterizes endogenous power and the contribution of the GSC members, it is introduced as the loss-averse reference point for the GSC members. Based on this, a decision model of the two-echelon GSC with loss aversion is formulated. The optimal strategies of price and product green degree are derived in four scenarios: (a) the centralized decision scenario with rational GSC members, namely the CD scenario; (b) the decentralized decision scenario with rational GSC members, namely the DD scenario; (c) the decentralized decision scenario with the GSC members loss-averse, where the manufacturer’s share is below its own loss-averse reference point, namely the DD(∆mπm) scenario; (d) the decentralized decision scenario with the GSC members loss-averse, where the retailer’s share is below its own loss-averse reference point, namely the DD(∆rπr) scenario. Then, a comparative analysis of the optimal strategies and profits in these four scenarios is conducted, and the impacts of loss aversion and green efficiency coefficient of products (GECP) on the GSC are also performed. The results show that (i) GECP has a critical influence on the retail price and the wholesale price; (ii) the GSC with loss aversion provide green products with the lowest green degree; (iii) the retail price, the wholesale price and product green degree are decreasing monotonically with the loss aversion level of the GSC member without incurring loss; (iv) furthermore, the effect of the loss aversion level of the GSC member with incurring loss on the optimal strategies is related to GECP and the gap between the GSC members’ loss aversion levels. Full article
(This article belongs to the Special Issue Supply Chain Management and Mathematical Logistics)
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