Mathematics

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28 pages, 2910 KiB

Open AccessArticle

Joint Scheduling of Yard Crane, Yard Truck, and Quay Crane for Container Terminal Considering Vessel Stowage Plan: An Integrated Simulation-Based Optimization Approach

by Hsien-Pin Hsu, Chia-Nan Wang, Hsin-Pin Fu and Thanh-Tuan Dang

Mathematics 2021, 9(18), 2236; https://doi.org/10.3390/math9182236 - 12 Sep 2021

Cited by 14 | Viewed by 3390

Abstract

The joint scheduling of quay cranes (QCs), yard cranes (YCs), and yard trucks (YTs) is critical to achieving good overall performance for a container terminal. However, there are only a few such integrated studies. Especially, those who have taken the vessel stowage plan [...] Read more.

The joint scheduling of quay cranes (QCs), yard cranes (YCs), and yard trucks (YTs) is critical to achieving good overall performance for a container terminal. However, there are only a few such integrated studies. Especially, those who have taken the vessel stowage plan (VSP) into consideration are very rare. The VSP is a plan assigning each container a stowage position in a vessel. It affects the QC operations directly and considerably. Neglecting this plan will cause problems when loading/unloading containers into/from a ship or even congest the YT and YC operations in the upstream. In this research, a framework of simulation-based optimization methods have been proposed firstly. Then, four kinds of heuristics/metaheuristics has been employed in this framework, such as sort-by-bay (SBB), genetic algorithm (GA), particle swarm optimization (PSO), and multiple groups particle swarm optimization (MGPSO), to deal with the yard crane scheduling problem (YCSP), yard truck scheduling problem (YTSP), and quay crane scheduling problem (QCSP) simultaneously for export containers, taking operational constraints into consideration. The objective aims to minimize makespan. Each of the simulation-based optimization methods includes three components, load-balancing heuristic, sequencing method, and simulation model. Experiments have been conducted to investigate the effectiveness of different simulation-based optimization methods. The results show that the MGPSO outperforms the others. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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26 pages, 369 KiB

Open AccessArticle

Studying the Effect of Noise on Pricing and Marketing Decisions of New Products under Co-op Advertising Strategy in Supply Chains: Game Theoretical Approaches

by Ata Allah Taleizadeh, Zahedeh Cheraghi, Leopoldo Eduardo Cárdenas-Barrón and Mahsa Noori-Daryan

Mathematics 2021, 9(11), 1222; https://doi.org/10.3390/math9111222 - 27 May 2021

Cited by 5 | Viewed by 1930

Abstract

The success of launching new products is the main challenge of companies since it is one of the key factors of competition. Thus, success in today’s high rival markets depends on the presentation of new products with new options, which must be compatible [...] Read more.

The success of launching new products is the main challenge of companies since it is one of the key factors of competition. Thus, success in today’s high rival markets depends on the presentation of new products with new options, which must be compatible with customers’ desires. This research aims to analyze the psychological effect of the noise of a new product on the total profit of the chain and the optimal pricing and marketing decisions of the chain’s members. Additionally, a cooperative (co-op) advertising strategy as a coordination mechanism is considered among the partners such that it helps them to obtain their target markets. Commonly, under co-op advertising, the manufacturer pays a percentage of the retailer’s advertising costs. In this chain, the manufacturer and the retailer agree to share the retailer’s advertising costs. Afterwards, four different relations between the manufacturer and retailer are studied and analyzed including three non-cooperative games with symmetrical distribution of market power and one asymmetrical distribution of it. So, four game models and their closed-form solutions are illustrated with a numerical example. It was found that the noise effect affects the total profit of the manufacturer and the retailer, as well as the supply chain by influencing the partners’ advertising policies. In other word, increasing the noise effect of the product indicates to the manufacturer and the retailer to globally and locally advertise more, respectively. In turn, their profits increase, although also increasing the advertising costs. Finally, a complete sensitivity analysis is conducted and reported. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

19 pages, 309 KiB

Open AccessArticle

Fast Algorithms for Basic Supply Chain Scheduling Problems

by Nodari Vakhania and Badri Mamporia

Mathematics 2020, 8(11), 1919; https://doi.org/10.3390/math8111919 - 2 Nov 2020

Viewed by 1704

Abstract

A basic supply chain scheduling problem in which the orders released over time are to be delivered into the batches with unlimited capacity is considered. The delivery of each batch has a fixed cost D, whereas any order delivered after its release [...] Read more.

A basic supply chain scheduling problem in which the orders released over time are to be delivered into the batches with unlimited capacity is considered. The delivery of each batch has a fixed cost D, whereas any order delivered after its release time yields an additional delay cost equal to the waiting time of that order in the system. The objective is to minimize the total delivery cost of the batches plus the total delay cost of the orders. A new algorithmic framework is proposed based on which fast algorithms for the solution of this problem are built. The framework can be extended to more general supply chain scheduling models and is based on a theoretical study of some useful properties of the offline version of the problem. An online scenario is considered as well, when at each assignment (order release) time the information on the next order released within the following T time units is known but no information on the orders that might be released after that time is known. For the online setting, it is shown that there is no benefit in waiting for more than D time units for incoming orders, i.e., potentially beneficial values for T are

0 < T < D

, and three linear-time algorithms are proposed, which are optimal for both the offline and the online cases when

T \geq D

. For the case

0 < T < D

an important real-life scenario is studied. It addresses a typical situation when the same number of orders are released at each order release time and these times are evenly distributed within the scheduling horizon. An optimal algorithm which runs much faster than earlier known algorithms is proposed. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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23 pages, 4711 KiB

Open AccessArticle

Design of Manufacturing Lines Using the Reconfigurability Principle

by Vladimír Vavrík, Milan Gregor, Patrik Grznár, Štefan Mozol, Marek Schickerle, Lukáš Ďurica, Martin Marschall and Tomáš Bielik

Mathematics 2020, 8(8), 1227; https://doi.org/10.3390/math8081227 - 26 Jul 2020

Cited by 15 | Viewed by 2214

Abstract

Nowadays, many factories face changes on the global market and manufacturing is unpredictable. This fact creates a demand for developing new concepts of the factory which can represent a solution to these changes. This study presents a way for designing these new factory [...] Read more.

Nowadays, many factories face changes on the global market and manufacturing is unpredictable. This fact creates a demand for developing new concepts of the factory which can represent a solution to these changes. This study presents a way for designing these new factory concepts, particularly a concept of the reconfigurable manufacturing lines. The methodology in this study uses characteristics of reconfigurable manufacturing systems for developing an algorithm for designing the basic factory layout. The methodology also combines classical math operations for designing the production layout with such approaches as simulation, cluster analysis, and LCS algorithm. This combination method with LCS algorithm and an entirely different approach to the design of the manufacturing line, has not yet been used. The accuracy of this methodology is then verified through the results of the complete algorithm containing these features. The main purpose of this study was to find new approaches to designing the reconfigurable factory layout. This article is presenting new ways that differ from the classical design method. The article suggests the new way is possible and the new systems also need new ways for designing and planning. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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20 pages, 1972 KiB

Open AccessArticle

Combining DEA and ARIMA Models for Partner Selection in the Supply Chain of Vietnam’s Construction Industry

by Han-Khanh Nguyen

Mathematics 2020, 8(6), 866; https://doi.org/10.3390/math8060866 - 27 May 2020

Cited by 12 | Viewed by 3832

Abstract

The competition between enterprises in the construction market is fierce. If enterprises are unable to afford financial and technological capabilities, they could go bankrupt. Therefore, the implementation of alliances between businesses can help increase their competitiveness. In this study, the authors simultaneously used [...] Read more.

The competition between enterprises in the construction market is fierce. If enterprises are unable to afford financial and technological capabilities, they could go bankrupt. Therefore, the implementation of alliances between businesses can help increase their competitiveness. In this study, the authors simultaneously used data envelopment analysis (DEA), the Grey model (GM (1,1)), and autoregressive integrated moving average (ARIMA) to choose a suitable strategic partner to boost the strength of each business and cut the cost of transportation and personnel in an attempt to help managers come up with suitable solutions, offer sustainability, and develop creative management. The results show that the chosen solution improves the business efficiency of construction businesses and offers cost savings on materials, production, and transportation. Management agencies can use the results of this study to propose suitable orientations, strengthen decision-making, and ensure strategic planning to develop the construction sector in Vietnam. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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31 pages, 5443 KiB

Open AccessArticle

Resources Planning for Container Terminal in a Maritime Supply Chain Using Multiple Particle Swarms Optimization (MPSO)

by Hsien-Pin Hsu and Chia-Nan Wang

Mathematics 2020, 8(5), 764; https://doi.org/10.3390/math8050764 - 11 May 2020

Cited by 18 | Viewed by 2701

Abstract

Resources planning is an important task in a supply chain in order to achieve a good result. The better the utilization of resources, especially scarce resources, the better the performance of a supply chain. This research focuses on allocating two scarce resources, i.e., [...] Read more.

Resources planning is an important task in a supply chain in order to achieve a good result. The better the utilization of resources, especially scarce resources, the better the performance of a supply chain. This research focuses on allocating two scarce resources, i.e., berth and quay cranes (QCs), to ships that call at a container terminal in a maritime supply chain. As global container shipments continue to grow, improving the efficiency of container terminals is important. A two-stage approach is used to find the optimal/near-optimal solution, in which the first stage is devoted to generating alternative ship placement sequences as inputs to the second stage that subsequently employs an event-based heuristic to place ships, resolve overlaps of ships, and assign/adjust QCs so as to develop a feasible solution. For identifying a better approach, various heuristics/metaheuristics, including first-come first-served (FCFS), particle swarm optimization (PSO), improved PSO (PSO2), and multiple PSO (MPSO), have been employed in the first stage, respectively. The experimental results show that combining the MPSO with the event-based heuristic leads to a better result. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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29 pages, 1666 KiB

Open AccessArticle

Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty

by Muhammad Imran, Muhammad Salman Habib, Amjad Hussain, Naveed Ahmed and Abdulrahman M. Al-Ahmari

Mathematics 2020, 8(3), 382; https://doi.org/10.3390/math8030382 - 9 Mar 2020

Cited by 16 | Viewed by 3382

Abstract

This paper presents a multi-objective, multi-period inventory routing problem in the supply chain of perishable products under uncertain costs. In addition to traditional objectives of cost and greenhouse gas (GHG) emission minimization, a novel objective of priority index maximization has been introduced in [...] Read more.

This paper presents a multi-objective, multi-period inventory routing problem in the supply chain of perishable products under uncertain costs. In addition to traditional objectives of cost and greenhouse gas (GHG) emission minimization, a novel objective of priority index maximization has been introduced in the model. The priority index quantifies the qualitative social aspects, such as coordination, trust, behavior, and long-term relationships among the stakeholders. In a multi-echelon supply chain, the performance of distributor/retailer is affected by the performance of supplier/distributor. The priority index measures the relative performance index of each player within the supply chain. The maximization of priority index ensures the achievement of social sustainability in the supply chain. Moreover, to model cost uncertainty, a time series integrated regression fuzzy method is developed. This research comprises of three phases. In the first phase, a mixed-integer multi-objective mathematical model while considering the cost uncertainty has been formulated. In order to determine the parameters for priority index objective function, a two-phase fuzzy inference process is used and the rest of the objectives (cost and GHG) have been modeled mathematically. The second phase involves the development of solution methodology. In this phase, to solve the mathematical model, a modified interactive multi-objective fuzzy programming has been employed that incorporates experts’ preferences for objective satisfaction based on their experiences. Finally, in the third phase, a case study of the supply chain of surgical instruments is presented as an example. The results of the case provide optimal flow of products from suppliers to hospitals and the optimal sequence of the visits of different vehicle types that minimize total cost, GHG emissions, and maximizes the priority index. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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19 pages, 846 KiB

Open AccessArticle

Improved Compact Cuckoo Search Algorithm Applied to Location of Drone Logistics Hub

by Jeng-Shyang Pan, Pei-Cheng Song, Shu-Chuan Chu and Yan-Jun Peng

Mathematics 2020, 8(3), 333; https://doi.org/10.3390/math8030333 - 3 Mar 2020

Cited by 83 | Viewed by 4641

Abstract

Drone logistics can play an important role in logistics at the end of the supply chain and special environmental logistics. At present, drone logistics is in the initial development stage, and the location of drone logistics hubs is an important issue in the [...] Read more.

Drone logistics can play an important role in logistics at the end of the supply chain and special environmental logistics. At present, drone logistics is in the initial development stage, and the location of drone logistics hubs is an important issue in the optimization of logistics systems. This paper implements a compact cuckoo search algorithm with mixed uniform sampling technology, and, for the problem of weak search ability of the algorithm, this paper combines the method of recording the key positions of the search process and increasing the number of generated solutions to achieve further improvements, as well as implements the improved compact cuckoo search algorithm. Then, this paper uses 28 test functions to verify the algorithm. Aiming at the problem of the location of drone logistics hubs in remote areas or rural areas, this paper establishes a simple model that considers the traffic around the village, the size of the village, and other factors. It is suitable for selecting the location of the logistics hub in advance, reducing the cost of drone logistics, and accelerating the large-scale application of drone logistics. This paper uses the proposed algorithm for testing, and the test results indicate that the proposed algorithm has strong competitiveness in the proposed model. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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16 pages, 1046 KiB

Open AccessArticle

Resilience-Based Restoration Model for Supply Chain Networks

by Xinhua Mao, Xin Lou, Changwei Yuan and Jibiao Zhou

Mathematics 2020, 8(2), 163; https://doi.org/10.3390/math8020163 - 23 Jan 2020

Cited by 16 | Viewed by 2750

Abstract

An optimal restoration strategy for supply chain networks can efficiently schedule the repair activities under resource limits. However, a wide range of previous studies solve this problem from the perspective of cost-effectiveness instead of a resilient manner. This research formulates the problem as [...] Read more.

An optimal restoration strategy for supply chain networks can efficiently schedule the repair activities under resource limits. However, a wide range of previous studies solve this problem from the perspective of cost-effectiveness instead of a resilient manner. This research formulates the problem as a network maximum-resilience decision. We develop two metrics to measure the resilience of the supply chain networks, i.e., the resilience of cumulative performance loss and the resilience of restoration rapidity. Then, we propose a bi-objective nonlinear programming model, which aims to maximize the network resilience under the budget and manpower constraints. A modified simulated annealing algorithm is employed to solve the model. Finally, a testing supply chain network is utilized to illustrate the effectiveness of the proposed method framework. The results show that the optimal restoration schedule generated by the proposed model is a tradeoff between the cumulative performance loss and the restoration rapidity. Additionally, the sensitivity analysis of parameters indicates that decision-maker’s preference, tolerance factor of delivery time, number of work crews, and availability of budget all have significant impacts on the restoration schedule. Full article

(This article belongs to the Special Issue Supply Chain Optimization)

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