Search Results (47)

Personal Rapid Transit (PRT) and Group Rapid Transit (GRT) are classes of fully automated public transport systems, where passengers can travel in small vehicles on an interconnected, grade-separated network of guideways, non-stop, from origin to destination. PRT and GRT are considered sustainable as they are low-emission and able to attract car drivers. The parameterized cost modeling framework developed in this paper has the advantage that profitability of different PRT/GRT systems can be rapidly verified in a transparent way and in function of a variety of relevant system parameters. This framework may contribute to a more transparent, rapid, and low-cost evaluation of PRT/GRT schemes for planning and decision-making purposes. The main innovation is the introduction of the “peak hour network saturation” S: the number of vehicles in circulation during peak hour divided by the maximum number of vehicles running at line speed with minimum time headways. It is an index that aggregates the main uncertainties in the planning process, namely the demand level relative to the supply level. Furthermore, a maximum S can be estimated for a PRT/GRT project, even without a detailed demand estimation. The profit per trip is analytically derived based on S and a series of more certain parameters, such as fares, capital and maintenance costs, daily demand curve, empty vehicle share, and physical properties of the system. To demonstrate the ability of the framework to analyze profitability in function of various parameters, we apply the methods to a single vehicle PRT, a platooned PRT, and a mixed PRT/GRT. The results show that PRT services with trip length proportional fares could be profitable already for $S>0.25$. The PRT capacity, profitability, and robustness to tripled infrastructure costs can be increased by vehicle platooning or GRT service during peak hours. Full article

This study takes the dual-channel fresh product supply chain involving the participation of third-party logistics (3PL) as the background to explore how 3PL makes choices between homogeneous and differentiated logistics service strategies and how the supply chain formulates optimal decisions under different logistics service strategies to achieve maximum benefits. This paper constructs a sequential game model of the three-tier supply chain composed of 3PL, a supplier, and a retailer; uses the consumer utility function to describe market demand; and considers different logistics service strategies adopted by 3PL. It compares and analyzes the equilibrium strategies under the traditional retail channel (O Model), the homogeneous cold-chain service dual-channel model (D1 Model), and the differentiated cold-chain service dual-channel model (D2 Model). The results show the following: (1) The D1 Model reduces the transportation cost of the supply chain through economies of scale. Under the D2 Model, the transportation and sales prices of the offline channels are higher than those of the online channels, while the online marketing effort is higher than that of the offline channels. (2) The profits generated by the dual-channel models (D1 Model and D2 Model) are both higher than those of O Model. In most cases, the D1 Model generates the highest system profit. However, in scenarios where consumers are highly sensitive to freshness and marketing efforts, the system profit of the D2 Model is higher than that of the D1 Model. (3) The supply chain has lower pricing and effort input when consumers are more sensitive to prices and higher pricing and effort input when consumers are more sensitive to freshness. These findings contribute valuable insights to the field of supply chain management, particularly in the context of fresh product supply chains involving 3PL. They underscore the importance of considering consumer behavior and logistics service strategies in optimizing supply chain performance and highlight the potential trade-offs between standardization and differentiation in logistics services. Full article

Land use and land cover (LULC) in coastal areas is critical in shaping the ecological systems, regional economy, and livelihood of indigenous communities. This study analyzes LULC changes (LULCC) in Soc Trang Province, Vietnam Mekong Delta, from 2010 to 2020 and simulates future LULC for 2030 under four scenarios: natural growth (business as usual, BAU), climate change challenges, profit optimization, and adaptation strategies. Satellite-based LULC maps and geospatial datasets were integrated into a LULC simulation model based on a Markov Chain and Cellular Automata to predict LULC in 2030 under disparate scenarios. Simultaneously, this study also estimates economic values and ecosystem service values as proxies to evaluate benefits and trade-offs between the scenarios. The research findings reveal that the critical LULCC observed during 2010–2020 are transitions from triple rice crops to double rice crops, rice–shrimp to brackish aquaculture, and expansion of perennial plantations. These transitional trends will persist at a modest rate under the BAU scenario in 2030. The climate change challenge scenario will intervene up to 24.2% of the total area, with double rice crops reaching the most extensive area compared to other scenarios, about 106,047 ha. The profit optimization scenario will affect 16.03% of the total area, focusing on aquaculture expansion to the maximum shared proportion of 34% (approximately 57,000 ha). Adaptive solutions will emphasize reducing triple rice crops while expanding double rice crops and reviving rice–shrimp to different extents depending on development pathways. Economic evaluations show a growth trend across scenarios, with maximum returns under profit optimization. Yet, ecosystem service values notably highlight ecological trade-offs, raising concerns about balancing economic benefits and ecological trade-offs in land use planning. The research findings recommend a comprehensive and multitarget approach to land use planning that integrates ecosystem services into initial assessments to balance benefits and trade-offs in coastal areas commonly affected by LULCC. By adopting well-informed and strategic land use plans that minimize ecological and social impacts, local sustainability and resilience to climate change can be significantly enhanced. Full article

Internet services are increasingly being deployed using cloud computing. However, the workload of an Internet service is not constant; therefore, the required cloud computing resources need to be allocated elastically to minimize the associated costs. Thus, this study proposes a proactive cloud resource scheduling framework. First, we propose a new workload prediction method—named the adaptive two-stage multi-neural network based on long short-term memory (LSTM)—which can adaptively route prediction tasks to the corresponding LSTM sub-model according to the workload change trend (i.e., uphill and downhill categories), in order to improve the predictive accuracy. To avoid the cost associated with manual labeling of the training data, the first-order gradient feature is used with the k-means algorithm to cluster and label the original training data set automatically into uphill and downhill training data sets. Then, based on stochastic queueing theory and the proposed prediction method, a maximum cloud service profit resource search algorithm based on the network workload prediction algorithm is proposed to identify a suitable number of virtual machines (VMs) in order to avoid delays in resource adjustment and increase the service profit. The experimental results demonstrate that the proposed proactive adaptive elastic resource scheduling framework can improve the workload prediction accuracy (MAPE: 0.0276, RMSE: 3.7085, $R^2$: 0.9522) and effectively allocate cloud resources. Full article

Container transport is one of the most promising modes of international freight transport. Railway container transport is mainly carried out using flat cars. Container cars can be damaged under the most unfavorable operating load conditions of a 1520 mm track gauge, i.e., shunting collisions. In this context, an improvement to the supporting structure of flat cars is proposed to ensure their strength, involving the installation of special superstructures in their cantilever parts to limit the movement of the containers. The choice of the superstructure profiles was made on the basis of the section modulus of their components. Mathematical modeling of the dynamic loading of a flat car with containers in the event of a shunting collision was carried out. The determined value of acceleration was taken into account in the calculation of the strength of the load-bearing structure of the flat car. It was found that the maximum stresses were 24% lower than the allowable stresses. Therefore, the strength condition of the flat car was met. The results of this study will contribute to reducing damage to container transport vehicles in service, to the formulation of recommendations for their construction and to an increase in their profitability, including in international transport. Full article

There are three operational modes for restaurant takeaway services: a takeaway platform combined with restaurant delivery (mode A), a takeaway platform paired with platform delivery (mode B), and a self-established platform with delivery (mode C). In the face of intense market competition, determining how restaurants can select appropriate operational delivery modes to maintain competitiveness and profitability has emerged as a pressing issue. In this paper, we develop game models that encompass a restaurant and food delivery platform to investigate the optimal operational mode for restaurants. Our analysis indicates that when the market size is small, mode B results in the lowest ordering costs, the highest sales volume, and the maximum profit. Conversely, in the context of a large market size, if the commission rate is low, mode A minimizes the ordering costs and maximizes sales volume; if the commission rate is high, mode C minimizes the ordering costs while also achieving the highest sales volume. Notably, we find that as long as the market size is sufficiently large, mode C consistently yields the highest restaurant profits. The outcomes of this study contribute to the theoretical framework surrounding the operation and management of food delivery platforms and offer theoretical guidance and decision-making support for selecting restaurant food delivery operational modes. Full article

Different refund policies offered by e-commerce platforms provide diverse options for consumers and are crucial for enhancing after-sales service. This study constructs a refund and ordering decision model based on three typical refund policies: both basic refund and refund guarantee option (‘Policy I’), basic refund only (‘Policy II’), and refund guarantee option only (‘Policy III’). We examine scenarios where demand is influenced by price, refund policies, and stochastic factors, and returns are affected by refund policies, aiming to determine the optimal refund and ordering decisions for fresh produce e-commerce platforms. Our results indicate that, under the same parameters, the platform achieves the maximum order quantity and highest expected profit with Policy I. The return rate under Policy I is always higher than under Policy III, but not consistently higher than under Policy II. Additionally, as the sensitivity of demand to the refund policy increases, both the order quantity and basic refund price rise, while the refund guarantee option price decreases. Conversely, as the sensitivity of returns to the refund policy increases, the opposite occurs. Although market demand uncertainty does not impact the basic refund or refund guarantee option prices, the platform must increase order quantities to manage market volatility. Full article

In the context of actively and steadily implementing the “dual carbon” strategy, two competing electric vehicle manufacturers (manufacturers m₁ and m₂) were selected as research objects to construct two different leasing strategy models for electric vehicle manufacturers, namely, m₁ provided a unit rental electric vehicle strategy and m₂ provided a fixed rental electric vehicle strategy. We studied the optimal car rental strategy and pricing of the two manufacturers under the situation of m₂ providing and not providing rental service efforts, and the influence of relevant factors on the optimal decision are explored. It shows that the price of electric vehicles rented by consumers per unit increases with the combined effect of the coefficient of rental service effort and the marginal cost of the rental service effort, while the price of fixed rental electric vehicles decreases with the combined effect of both. When the unit rental preference coefficient is large, the unit rental of electric vehicles will give m₁ maximum profit. When the rental service effort coefficient is high, m₂ is the most profitable. The efforts to provide leasing services of m₂ increase their own interests to a certain extent. The greater the effort coefficient of leasing services, the smaller the marginal cost of leasing services, and the optimal social welfare reaches the maximum. The conclusion of the article can provide relevant leasing insights for electric vehicle manufacturers and also provide certain theoretical guidance for promoting electric vehicle leasing service strategies. Full article

Cloud brokers and service providers are concerned with utilizing available resources to maximize their profits. On the other hand, customers seek the best service provider/resource to provide them with maximum satisfaction. One of the main concerns is the variability of available service providers on the cloud, their capabilities, and the availability of their resources. Furthermore, various criteria influence the effective assignment of a task to a virtual machine (VM) before it is, in turn, submitted to the physical machine (PM). To bring cloud service providers (CSPs) and customers together, this study proposes a broker-based mechanism that measures the tendency of each customer’s task. Then, the proposed mechanism assigns all tasks—in prioritized order of importance—to the best available service provider/resource. The model acquires the importance of each task, CSP, or resource by extracting and manipulating the evaluations provided by decision makers and by adopting a multi-criteria decision-making (MCDM) method. Thus, a partial result of the proposed mechanism is a defined and prioritized pool for each of the tasks, CSPs, and resources. Various MCDM methods are examined and compared to validate the proposed model, and experiments show the applicability of the various methods within the model. Furthermore, the results of the experiments verify the suitability and applicability of the proposed model within the cloud environment. Full article

After the COVID-19 pandemic has subsided, the catering industry has returned to its previous thriving scene. Many restaurants have launched group buying services and collaborate with third-party online platforms to attract more customers. For the optimal decisions and maximum profits of restaurants and online platforms, a two-layer supply chain model is designed to investigate and study the price strategies and service strategies. Considering the service levels of restaurants and platforms, we construct the mathematical expressions of the offline retail model, online retail model, and online group buying model, respectively, and solve the game equilibrium. The results are shown as follows: (1) With cooperation between the restaurant and platform, both the restaurant and platform can obtain their maximum profits when they apply optimal pricing strategies. (2) The optimal pricing strategies of the restaurant are influenced by the sensitivity coefficients of customers to the restaurant and platform’s service levels, and the cost coefficients of the restaurant and platform’s service levels. (3) The maximum profit of the restaurant is directly proportional to the number of new potential consumers who are attracted. The more potential consumers who are attracted, the higher the profit the restaurant earns. The research results provide a reference for restaurants and platforms to formulate price strategies and service strategies, to help restaurants and platforms achieve more profits. Full article

Taxis play a crucial role as an on-demand transportation mode in developing countries due to perceived inefficiencies of cities’ public transportation systems. However, studies on the locational distribution of taxis in urban areas are limited, despite the need to improve passenger service quality by balancing the demand and supply of taxi services. Notably, taxi stations possess distinct characteristics compared with other public transport stations that serve passengers directly; in contrast, taxi stations solely support taxi drivers in locations where they begin and conclude their work. This study aims to determine the spatial distribution pattern and assess the agglomeration economies of taxi stations, using Bangkok as a case study, a city with a significant number of registered taxis and dispersed taxi stations. This research takes into account various spatial variables, including land price, land use mix index, population density, and gas station locations. The primary tool for analyzing the spatial distribution pattern was the spatial statistics model, employing ArcGIS 10.8 software. The analysis consisted of three steps: testing for clustered or dispersed patterns using Moran’s I, applying Anselin’s local Moran’s I (LISA) to examine the relationship between taxi station coordinates and spatial variables such as land price, land use mix index, and population density, and evaluating the relationship between taxi stations and energy service stations using the network analysis tool. The results revealed that taxi stations exhibited a spatially clustered pattern and were closely correlated with the land use mix index, land price, and population density, as indicated by Moran’s index values of 0.425, 0.328, and 0.373, respectively, especially those located within a 3000 m radius of gas stations. These findings elucidate the location selection of taxi stations, which tend to prioritize areas that can generate maximum profits for the taxi business rather than those with minimal location costs. They also tend to be situated in proximity to market areas. Additionally, the study recommends that the government consider promoting electric taxis as a sustainable mode of urban transport in the future to reduce the usage of natural gas (NGV) and liquefied petroleum gas (LPG). Full article

Agrophotovoltaic (APV) systems produce both solar energy and crops, so they are considered a sustainable alternative to traditional solar power plants, which can potentially destroy farmlands. However, it is challenging to diffuse APV systems because of their high installation and operating costs. Thus, to resolve the issue by maximizing the productivity and profits of an APV system, this study aims to propose a mobile-phone-based decision support system (DSS) for a supply chain network design for APV systems in South Korea using satellite imagery incorporating geographic information system (GIS) data. Particularly, polynomial regression models estimating annual corn (Zea mays) yields and the predicted generation of electricity were developed and integrated with the proposed DSS. Field experiment data provided by the APV system at Jeollanamdo Agricultural Research and Extension Services in South Korea were utilized. Two photovoltaic (PV) module types (mono-facial and bi-facial) and three different shading ratios for APV systems (21.3%, 25.6%, and 32.0%) were considered design factors for APV systems. An optimal network structure of 6 candidate APV systems and 15 agricultural markets was devised using the generalized reduced gradient (GRG) method. The profits of the six candidate APV systems are mainly affected by the transportation costs to the markets and the policy of the electricity selling prices. As a result, the proposed supply chain design framework successfully identifies an APV system network with maximum profits from crop production as well as electricity generation. Full article

The optimal location for establishing logistics centers is of great importance in reducing logistics costs and improving supply chain efficiency. This paper aims to provide a conceptual framework for finding the optimal location and capacity for a logistics village establishment using mixed-integer linear programming (MILP). The proposed model is applied on Qazvin province, Iran, as a developing country with a strategic location in international transport corridors. Unlike previous research, the proposed approach considers various logistics operations such as warehousing, refrigeration, sorting, and packaging, along with their capacities as distinct decision variables. The study area is divided into 6972 blocks of 1.5 × 1.5 km, of which 59% are infeasible and excluded due to environmental and natural hazard constraints. The MILP model is then applied in the GAMS for each feasible block to identify the best alternatives for the logistic village establishment with maximum total profit. Based on the results, total freight imported to Qazvin province is directly transferred to their final destinations without visiting the logistics village, while around 98% of exports of Qazvin province would first enter the logistics village to get a service before delivering to customers. Full article

In this paper, a semi-Markov model for determining the optimal time for preventive replacements according to the age of technical objects is presented. In the analyzed system of transportation, due to its specific characteristics, the basic type of renewal process carried out is minimal repair. Minimal repairs of technical objects in semi-Markov models have been analyzed in the literature to date. In the system studied, the technical objects (sets of agricultural tractors with trailers), due to the continuous operation of combine harvesters, should carry out the assigned tasks of transporting agricultural crops without interruption. The damage to agricultural tractors that arises during the implementation of transport tasks should be repaired in the shortest possible time. The repairs to damaged tractors are carried out primarily by the Technical Emergency Service and, due to their purpose and scope, may be considered minimal repairs. The effectiveness of the function of the tested technical objects is analyzed by two criteria functions, which are very important for the system managers. These are profit per unit of time and availability. In the analyzed case, it is the availability to carry out the assigned transport tasks. The conditions for the existence of a maximum of criterion functions have been written for the assumptions. The analyzes carried out, which are presented in the work, are illustrated with sample calculations. It has been proven that, under general assumptions, the criterion functions considered in the paper have exactly one maximum. On the basis of the conducted analysis, sufficient conditions for the existence of a maximum of these functions were formulated. In the analyzed transport system, it is possible to increase the efficiency of the function of the technical facilities in use as a result of planning additional preventive replacements (increasing the frequency of these replacements). This is especially important for a system where transport units must have high availability. Full article

In the closed-loop supply chain, many suppliers opt for self-recycling or entrust retailers to recycle. Under both recycling channels, the member responsible for recycling can undertake or outsource logistics services. This paper investigates how consumers’ environmental awareness and recycling cost-saving affect the optimal combination of recycling channel and logistics-service strategy. To this end, we mathematically formulate the supplier-led Stackelberg game theoretical-framework, and apply the Karush–Kuhn–Tucker conditions for constrained optimization. We examine the optimal combination under the impact of consumers’ environmental awareness and recycling cost-saving on profits, environmental impact and social welfare, using numerical analysis. Results demonstrate that as consumers’ environmental awareness and recycling cost-saving remain at a higher level, the supplier and retailer will both achieve maximum profits when the supplier entrusts the retailer to recycle and the retailer undertakes the logistics services. Meanwhile, the third party will choose to be entrusted with services by the supplier, rather than the retailer. To improve supply-chain performance, the retailer should assume social responsibility to recycle and build the logistics-service system. Full article