Pub Date : 2025-01-17DOI: 10.1016/j.tre.2025.103962
Arjun Rachana Harish, Xinlai Liu, Ming Li, Ray Y. Zhong, George Q. Huang
It is well known that supply chains should leverage information sharing from stakeholders as a measure to drive business growth. However, the practice of information sharing for supply chain management has been fairly limited due to the high cost of meeting differential user needs, information-island from centralized storage, and inefficient information value capture. To address these concerns, we investigate a crypto-valuation mechanism of digital assets (DAs) inspired by a standard monopolistic screening model. Our model consists of a DAs provider with a unique cost structure of sharing DAs and users who experience participation costs. The DAs are digital replicas of physical assets (e.g., workforce, trucks, and cargo) in the supply chain. The provider produces DAs with maximum features (e.g., carbon emission, customer satisfaction, etc.) to give users differential feature access for set valuations (crypto-token payment). When the consumers experience participation costs, we find that the marginal sharing and participation costs determine the optimality of DAs versioning. By endogenizing the highest quality (or level of digitization), we find that an increase in the cost of delivering DAs results in every user getting access to fewer features. Interestingly, cost factors do not directly influence user coverage, i.e., costs do not determine who gets access to DAs. However, the provider’s decision to absorb a portion of user participation cost can contract the user coverage. Overall, this study contributes a novel valuation mechanism to the literature on blockchain adoption for information sharing in the supply chain. It also offers insights and recommendations based on critical parameters to guide supply chains that leverage the mechanism for business growth.
{"title":"The new supply chain information sharing Renaissance through crypto valuation mechanism of digital assets","authors":"Arjun Rachana Harish, Xinlai Liu, Ming Li, Ray Y. Zhong, George Q. Huang","doi":"10.1016/j.tre.2025.103962","DOIUrl":"https://doi.org/10.1016/j.tre.2025.103962","url":null,"abstract":"It is well known that supply chains should leverage information sharing from stakeholders as a measure to drive business growth. However, the practice of information sharing for supply chain management has been fairly limited due to the high cost of meeting differential user needs, information-island from centralized storage, and inefficient information value capture. To address these concerns, we investigate a crypto-valuation mechanism of digital assets (DAs) inspired by a standard monopolistic screening model. Our model consists of a DAs provider with a unique cost structure of sharing DAs and users who experience participation costs. The DAs are digital replicas of physical assets (e.g., workforce, trucks, and cargo) in the supply chain. The provider produces DAs with maximum features (e.g., carbon emission, customer satisfaction, etc.) to give users differential feature access for set valuations (crypto-token payment). When the consumers experience participation costs, we find that the marginal sharing and participation costs determine the optimality of DAs versioning. By endogenizing the highest quality (or level of digitization), we find that an increase in the cost of delivering DAs results in every user getting access to fewer features. Interestingly, cost factors do not directly influence user coverage, i.e., costs do not determine who gets access to DAs. However, the provider’s decision to absorb a portion of user participation cost can contract the user coverage. Overall, this study contributes a novel valuation mechanism to the literature on blockchain adoption for information sharing in the supply chain. It also offers insights and recommendations based on critical parameters to guide supply chains that leverage the mechanism for business growth.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"144 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-17DOI: 10.1016/j.tre.2025.103961
Yun He, Yunrong Zhang, Huaxiao Shen
In a technology-intensive supply chain, branding can significantly enhance consumers’ perception of a technology’s contribution to the final products, making it potentially beneficial for the technology provider. However, many technology providers operate behind the scenes as pure suppliers, rather than branding themselves. The reasons behind these heterogeneous branding decisions among technology providers remain unclear. Our findings suggest that without branding, the technology provider’s profitability is largely determined by the manufacturer’s quality. As a result, even if a technology provider offers technology of higher quality and possesses greater bargaining power, it may not necessarily realize higher profits. Branding can significantly mitigate this effect, allowing the technology provider to gain profit without being constrained by the manufacturer’s quality. The trade-off between bargaining power and additional branding costs plays a key role in the technology provider’s profitability. Interestingly, while one might expect that increasing the technology provider’s bargaining power would hurt the manufacturer’s profit, our findings show that when the technology provider opts for branding, an increase in bargaining power can lead to a win-win solution, provided that the branding cost is not too high. We further extend the model to investigate how the technology provider’s encroachment decision affect the competitive decision within the branding strategy. Finally, we examine the robustness of the major results by employing different decision sequences and licensing fee structures. Overall, the results of this paper offer technology providers valuable insights into the advantages and disadvantages of the branding strategy.
{"title":"Behind the scenes or front? Branding strategy of technology provider in a technology-intensive supply chain","authors":"Yun He, Yunrong Zhang, Huaxiao Shen","doi":"10.1016/j.tre.2025.103961","DOIUrl":"https://doi.org/10.1016/j.tre.2025.103961","url":null,"abstract":"In a technology-intensive supply chain, branding can significantly enhance consumers’ perception of a technology’s contribution to the final products, making it potentially beneficial for the technology provider. However, many technology providers operate behind the scenes as pure suppliers, rather than branding themselves. The reasons behind these heterogeneous branding decisions among technology providers remain unclear. Our findings suggest that without branding, the technology provider’s profitability is largely determined by the manufacturer’s quality. As a result, even if a technology provider offers technology of higher quality and possesses greater bargaining power, it may not necessarily realize higher profits. Branding can significantly mitigate this effect, allowing the technology provider to gain profit without being constrained by the manufacturer’s quality. The trade-off between bargaining power and additional branding costs plays a key role in the technology provider’s profitability. Interestingly, while one might expect that increasing the technology provider’s bargaining power would hurt the manufacturer’s profit, our findings show that when the technology provider opts for branding, an increase in bargaining power can lead to a win-win solution, provided that the branding cost is not too high. We further extend the model to investigate how the technology provider’s encroachment decision affect the competitive decision within the branding strategy. Finally, we examine the robustness of the major results by employing different decision sequences and licensing fee structures. Overall, the results of this paper offer technology providers valuable insights into the advantages and disadvantages of the branding strategy.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"49 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-16DOI: 10.1016/j.tre.2024.103959
Ying Cao, Guang Li, Kai Meng, Xianghui Peng
Remanufacturing is a viable and indispensable method to restore used electronics to near-new condition, combating the alarming rise of end-of-life (EOL) products, particularly in the field of electronic waste. It aligns with Environmental, Social, and Governance (ESG) principles, emphasizing sustainability and responsible resource management. In this paper, we consider a remanufacturer’s problem in choosing various technologies to form a Remanufacturing Technology Portfolio (RTP), a strategic decision affecting remanufacturers’ efficiency, productivity, and contributions to societal and environmental welfare. To address the unique challenges posed by the variability of EOL product quality, substitutability among candidate technologies, and other considerations in the RTP problem, we employ a discrete choice modeling framework, specifically the multinomial logit model, to characterize the technology assignment process of unprocessed EOL cores. This application is novel in the remanufacturing industry. We reveal that the optimal RTP balances remanufacturing capability and profitability, consisting of a set of the most profitable technologies. Moreover, we identify conditions under which technologies are included or excluded from the optimal RTP and explore the impact of various factors such as selling price, salvage values, and production and material costs on the composition of the optimal RTP and the remanufacturing yield. This study provides valuable guidance for remanufacturers in strategically selecting technologies to enhance their performance and competitiveness in the volatile remanufacturing market, while advancing their ESG objectives. In a broader supply chain context, the findings suggest strategies to encourage other supply chain stakeholders to engage in ESG practices and offer insights on how government incentives promoting remanufacturing can be more effectively structured based on technological considerations.
{"title":"Managerial decisions of remanufacturing technology portfolio under a discrete choice model","authors":"Ying Cao, Guang Li, Kai Meng, Xianghui Peng","doi":"10.1016/j.tre.2024.103959","DOIUrl":"https://doi.org/10.1016/j.tre.2024.103959","url":null,"abstract":"Remanufacturing is a viable and indispensable method to restore used electronics to near-new condition, combating the alarming rise of end-of-life (EOL) products, particularly in the field of electronic waste. It aligns with Environmental, Social, and Governance (ESG) principles, emphasizing sustainability and responsible resource management. In this paper, we consider a remanufacturer’s problem in choosing various technologies to form a Remanufacturing Technology Portfolio (RTP), a strategic decision affecting remanufacturers’ efficiency, productivity, and contributions to societal and environmental welfare. To address the unique challenges posed by the variability of EOL product quality, substitutability among candidate technologies, and other considerations in the RTP problem, we employ a discrete choice modeling framework, specifically the multinomial logit model, to characterize the technology assignment process of unprocessed EOL cores. This application is novel in the remanufacturing industry. We reveal that the optimal RTP balances remanufacturing capability and profitability, consisting of a set of the most profitable technologies. Moreover, we identify conditions under which technologies are included or excluded from the optimal RTP and explore the impact of various factors such as selling price, salvage values, and production and material costs on the composition of the optimal RTP and the remanufacturing yield. This study provides valuable guidance for remanufacturers in strategically selecting technologies to enhance their performance and competitiveness in the volatile remanufacturing market, while advancing their ESG objectives. In a broader supply chain context, the findings suggest strategies to encourage other supply chain stakeholders to engage in ESG practices and offer insights on how government incentives promoting remanufacturing can be more effectively structured based on technological considerations.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"17 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-16DOI: 10.1016/j.tre.2025.103960
Mohammad S. Moshtagh, Yun Zhou, Manish Verma
This paper investigates a dynamic inventory-pricing system with perishable products of multiple freshness levels. The firm may set different prices for items of different freshness levels, and customers either balk or choose to buy the freshness level that maximizes their utility. We model this inventory-pricing problem as a Markov decision process, where the assortment dynamically changes based on the freshness levels of the available items. Using the concept of anti-multimodularity, we characterize the structure of the optimal policy. Specifically, we show that the optimal production policy has a state-dependent threshold-based structure. The production decisions are more sensitive to the inventory of fresher items than less fresh ones. Moreover, the optimal price of a freshness level is nonincreasing in the inventory of items of any freshness level, and it is more sensitive to those of a closer freshness level. The structural properties enable us to devise three novel heuristic policies with good performance. We further extend the model by considering donations and a system with multiple freshness phases. Our research suggests that freshness-dependent pricing and dynamic pricing are two substitutable strategies, while freshness-dependent pricing and donation are strategic complements. The results further imply that the firm can benefit from high variability in freshness among items under dynamic pricing, but such variability may lead to a significant loss when single, static pricing is used. The results of our heuristic policies show that considering inventory and pricing decisions as a parametrized function of the inventory state leads to nearly optimal solutions.
{"title":"Dynamic inventory and pricing control of a perishable product with multiple shelf life phases","authors":"Mohammad S. Moshtagh, Yun Zhou, Manish Verma","doi":"10.1016/j.tre.2025.103960","DOIUrl":"https://doi.org/10.1016/j.tre.2025.103960","url":null,"abstract":"This paper investigates a dynamic inventory-pricing system with perishable products of multiple freshness levels. The firm may set different prices for items of different freshness levels, and customers either balk or choose to buy the freshness level that maximizes their utility. We model this inventory-pricing problem as a Markov decision process, where the assortment dynamically changes based on the freshness levels of the available items. Using the concept of anti-multimodularity, we characterize the structure of the optimal policy. Specifically, we show that the optimal production policy has a state-dependent threshold-based structure. The production decisions are more sensitive to the inventory of fresher items than less fresh ones. Moreover, the optimal price of a freshness level is nonincreasing in the inventory of items of any freshness level, and it is more sensitive to those of a closer freshness level. The structural properties enable us to devise three novel heuristic policies with good performance. We further extend the model by considering donations and a system with multiple freshness phases. Our research suggests that freshness-dependent pricing and dynamic pricing are two substitutable strategies, while freshness-dependent pricing and donation are strategic complements. The results further imply that the firm can benefit from high variability in freshness among items under dynamic pricing, but such variability may lead to a significant loss when single, static pricing is used. The results of our heuristic policies show that considering inventory and pricing decisions as a parametrized function of the inventory state leads to nearly optimal solutions.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"94 1 Suppl 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-10DOI: 10.1016/j.tre.2024.103924
Jawad Hyder, Elkafi Hassini
This study develops a model to optimize warehouse space allocation to maximize throughput based on the capabilities of the delivery company. A bounded knapsack model is suggested for strategic customer selection. It integrates the customer’s inputs and the delivery company’s capabilities to determine a subset of customers and the respective volume amounts that need to be selected from each customer to maximize the company’s profit. The aim is to enhance profit by choosing customers with high profitability, considering penalties, and ensuring the total processed volume does not exceed the facility’s capacity. A heuristic method is suggested and tested. This method enables postal organizations to leverage their current assets and procedures to gain an edge in the expanding e-commerce sector. Numerical analyses indicate that the proposed greedy heuristic results in penalty values that are comparable to or lower than those of traditional methods, and it enhances the overall profitability of the postal organization.
{"title":"Optimizing warehouse space allocation to maximize profit in the postal industry","authors":"Jawad Hyder, Elkafi Hassini","doi":"10.1016/j.tre.2024.103924","DOIUrl":"https://doi.org/10.1016/j.tre.2024.103924","url":null,"abstract":"This study develops a model to optimize warehouse space allocation to maximize throughput based on the capabilities of the delivery company. A bounded knapsack model is suggested for strategic customer selection. It integrates the customer’s inputs and the delivery company’s capabilities to determine a subset of customers and the respective volume amounts that need to be selected from each customer to maximize the company’s profit. The aim is to enhance profit by choosing customers with high profitability, considering penalties, and ensuring the total processed volume does not exceed the facility’s capacity. A heuristic method is suggested and tested. This method enables postal organizations to leverage their current assets and procedures to gain an edge in the expanding e-commerce sector. Numerical analyses indicate that the proposed greedy heuristic results in penalty values that are comparable to or lower than those of traditional methods, and it enhances the overall profitability of the postal organization.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"35 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-09DOI: 10.1016/j.tre.2024.103958
Ningning Du, Yingchen Yan, Zhongfeng Qin
Retailer financing has gained popularity as a means to alleviate capital constraints and enhance supply chain operations. However, its implementation poses significant challenges, particularly in supply chains characterized by asymmetric information, where varying levels of knowledge about product quality complicate decision-making and often diminish the potential benefits of financing. To address this issue, we develop an analytical model to examine the benefits that retailer financing can bring to all parties, especially whether it can incentivize an informed firm to initiatively share information in the presence of asymmetric quality information. First, we present that retailer financing can lead to a “win–win–win” situation for the manufacturer, retailer and consumers, as the firms’ capital flows within the whole supply chain and boosts the production output. Second, we find that, in the presence of asymmetric quality information between the retailer and manufacturer, the retailer may provide financing services to motivate an informed manufacturer to initiatively share quality information. The strategic information sharing becomes dominant when the manufacturer’s production cost is high and initial capital is moderate. Third, our analysis indicates that the retailer’s willingness to provide financing and the manufacturer’s willingness to initiatively share quality information exert a mutual promotion effect, enhancing information transparency in the supply chain. We also extend our analysis to an alternative game sequence and a competition environment.
{"title":"Retailer financing: On the dual advantages of profit and information transparency","authors":"Ningning Du, Yingchen Yan, Zhongfeng Qin","doi":"10.1016/j.tre.2024.103958","DOIUrl":"https://doi.org/10.1016/j.tre.2024.103958","url":null,"abstract":"Retailer financing has gained popularity as a means to alleviate capital constraints and enhance supply chain operations. However, its implementation poses significant challenges, particularly in supply chains characterized by asymmetric information, where varying levels of knowledge about product quality complicate decision-making and often diminish the potential benefits of financing. To address this issue, we develop an analytical model to examine the benefits that retailer financing can bring to all parties, especially whether it can incentivize an informed firm to initiatively share information in the presence of asymmetric quality information. First, we present that retailer financing can lead to a “win–win–win” situation for the manufacturer, retailer and consumers, as the firms’ capital flows within the whole supply chain and boosts the production output. Second, we find that, in the presence of asymmetric quality information between the retailer and manufacturer, the retailer may provide financing services to motivate an informed manufacturer to initiatively share quality information. The strategic information sharing becomes dominant when the manufacturer’s production cost is high and initial capital is moderate. Third, our analysis indicates that the retailer’s willingness to provide financing and the manufacturer’s willingness to initiatively share quality information exert a mutual promotion effect, enhancing information transparency in the supply chain. We also extend our analysis to an alternative game sequence and a competition environment.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"131 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-08DOI: 10.1016/j.tre.2024.103954
Yuanhan Wei, Yong Wang, Xiangpei Hu
With the rapid expansion of e-commerce and the resulting surge in parcel delivery demands, the integration of trucks and unmanned ground vehicles (UGVs) in last-mile package delivery provides a more efficient and sustainable venue for a logistics system. However, coordinating trucks and UGVs in the context of fluctuating traffic conditions, especially with varying travel times, continues to be a significant challenge. This study addresses this issue by proposing and solving a two-echelon truck-UGV routing problem with time-dependent travel times. The first echelon encompasses transporting goods from the warehouse to satellites using trucks, considering time-dependent travel times. The second echelon involves distributing goods from satellites to customers using UGVs. Initially, a continuous-time time-dependent travel model is proposed based on the fluid queueing model to estimate vehicle travel times under varying traffic conditions. We then develop a multiobjective mixed integer linear programming model that aims to minimize total operating costs and the number of UGVs used. Subsequently, a novel hybrid algorithm combining an improved three dimension k-nearest neighbor clustering algorithm with an improved multiobjective adaptive large neighborhood search method is developed to solve the model. This algorithm incorporates the adaptive score adjustment and Pareto solution selection strategies to enhance algorithm convergence and evaluate solution quality. The acceptance criterion for new solutions is redesigned based on multiobjective function values to explore the search space more thoroughly. Additionally, the algorithm’s computational performance is verified by comparing it with the CPLEX solver for small-scale problems and with multiobjective ant colony optimization, multiobjective evolutionary algorithms, multiobjective particle swarm optimization, multiobjective monarch butterfly optimization, and multiobjective harmony search algorithms for medium-to-large problems. The results demonstrate the superior convergence, uniformity, and spread of the proposed algorithm. Furthermore, a real-world case study employing traffic information of Dalian city, China, supports that the proposed method enhances the efficiency of delivery. Four different time-dependent travel times model are proposed to analyze the outperformance of the time-dependent travel model in this study. Finally, the sensitivity analysis considers different road congestion states and UGV capacities, aiming to reduce transportation costs, and overcome high coordination and congestion costs in the network. This study offers robust methodologies for theoretically and practically addressing the two-echelon truck-UGV routing problem with time-dependent travel times, providing essential insights for promoting development, enhancing smart city integration, and boosting operational efficiency.
{"title":"The two-echelon truck-unmanned ground vehicle routing problem with time-dependent travel times","authors":"Yuanhan Wei, Yong Wang, Xiangpei Hu","doi":"10.1016/j.tre.2024.103954","DOIUrl":"https://doi.org/10.1016/j.tre.2024.103954","url":null,"abstract":"With the rapid expansion of e-commerce and the resulting surge in parcel delivery demands, the integration of trucks and unmanned ground vehicles (UGVs) in last-mile package delivery provides a more efficient and sustainable venue for a logistics system. However, coordinating trucks and UGVs in the context of fluctuating traffic conditions, especially with varying travel times, continues to be a significant challenge. This study addresses this issue by proposing and solving a two-echelon truck-UGV routing problem with time-dependent travel times. The first echelon encompasses transporting goods from the warehouse to satellites using trucks, considering time-dependent travel times. The second echelon involves distributing goods from satellites to customers using UGVs. Initially, a continuous-time time-dependent travel model is proposed based on the fluid queueing model to estimate vehicle travel times under varying traffic conditions. We then develop a multiobjective mixed integer linear programming model that aims to minimize total operating costs and the number of UGVs used. Subsequently, a novel hybrid algorithm combining an improved three dimension <ce:italic>k</ce:italic>-nearest neighbor clustering algorithm with an improved multiobjective adaptive large neighborhood search method is developed to solve the model. This algorithm incorporates the adaptive score adjustment and Pareto solution selection strategies to enhance algorithm convergence and evaluate solution quality. The acceptance criterion for new solutions is redesigned based on multiobjective function values to explore the search space more thoroughly. Additionally, the algorithm’s computational performance is verified by comparing it with the CPLEX solver for small-scale problems and with multiobjective ant colony optimization, multiobjective evolutionary algorithms, multiobjective particle swarm optimization, multiobjective monarch butterfly optimization, and multiobjective harmony search algorithms for medium-to-large problems. The results demonstrate the superior convergence, uniformity, and spread of the proposed algorithm. Furthermore, a real-world case study employing traffic information of Dalian city, China, supports that the proposed method enhances the efficiency of delivery. Four different time-dependent travel times model are proposed to analyze the outperformance of the time-dependent travel model in this study. Finally, the sensitivity analysis considers different road congestion states and UGV capacities, aiming to reduce transportation costs, and overcome high coordination and congestion costs in the network. This study offers robust methodologies for theoretically and practically addressing the two-echelon truck-UGV routing problem with time-dependent travel times, providing essential insights for promoting development, enhancing smart city integration, and boosting operational efficiency.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"35 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-07DOI: 10.1016/j.tre.2024.103946
Huichang Dong, Zhixing Luo, Nan Huang, Hongjian Hu, Hu Qin
This paper investigates The Electric Vehicle Dial-a-Ride Problem: Integrating Ride-Sharing and Time-of-Use Electricity Pricing (DAR-RSTOU), which involves designing a set of minimum-cost routes to service all customers for a fleet of electric vehicles (EVs). The characteristics of the problem include: (1) the use of EVs and consideration of partial charging strategies; (2) a maximum ride time duration limit for each customer; (3) the possibility of ride-sharing among customers; (4) accounting for Time-of-Use (TOU) electricity pricing policies. We propose a novel mixed integer programming model to describe the problem, aiming to minimize the weighted sum of the charging, total travel, and detour penalty costs. Additionally, we have devised a customized adaptive large neighborhood search heuristic with an enhanced feasibility-checking method for rapid solution evaluation and dynamic programming to optimize the charging strategy for the fleet. Computational experiments on adapted benchmark instances from DARP literature and on instances based on real data from electric taxis in Shenzhen assess the validity of the DAR-RSTOU formulation and the heuristic algorithm. Parameter experiments highlight the algorithm’s acceleration strategy effectiveness. Valuable managerial insights are derived from policy-oriented research on different electricity pricing strategies.
{"title":"The electric vehicle dial-a-ride problem: Integrating ride-sharing and time-of-use electricity pricing","authors":"Huichang Dong, Zhixing Luo, Nan Huang, Hongjian Hu, Hu Qin","doi":"10.1016/j.tre.2024.103946","DOIUrl":"https://doi.org/10.1016/j.tre.2024.103946","url":null,"abstract":"This paper investigates The Electric Vehicle Dial-a-Ride Problem: Integrating Ride-Sharing and Time-of-Use Electricity Pricing (DAR-RSTOU), which involves designing a set of minimum-cost routes to service all customers for a fleet of electric vehicles (EVs). The characteristics of the problem include: (1) the use of EVs and consideration of partial charging strategies; (2) a maximum ride time duration limit for each customer; (3) the possibility of ride-sharing among customers; (4) accounting for Time-of-Use (TOU) electricity pricing policies. We propose a novel mixed integer programming model to describe the problem, aiming to minimize the weighted sum of the charging, total travel, and detour penalty costs. Additionally, we have devised a customized adaptive large neighborhood search heuristic with an enhanced feasibility-checking method for rapid solution evaluation and dynamic programming to optimize the charging strategy for the fleet. Computational experiments on adapted benchmark instances from DARP literature and on instances based on real data from electric taxis in Shenzhen assess the validity of the DAR-RSTOU formulation and the heuristic algorithm. Parameter experiments highlight the algorithm’s acceleration strategy effectiveness. Valuable managerial insights are derived from policy-oriented research on different electricity pricing strategies.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"20 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-07DOI: 10.1016/j.tre.2024.103953
Qiang Zhou, Xiaolong Guo, Can Sun
Augmented Reality (AR) has been increasingly applied in e-commerce to facilitate consumer purchasing. This paper characterizes and models two features of AR: the Accuracy Effect and Entertainment Effect. The former refers to AR mitigating consumer valuation bias, while the latter refers to the psychological entertainment consumers obtain when using AR to facilitate their purchasing. Although AR mitigates consumer valuation bias (Accuracy Effect), AR may also reduce the consumers’ prior valuation of products. In addition, despite AR increasing the consumers’ willingness to pay (through the Entertainment Effect), it exacerbates the bias between the products’ true value and the value perceived by consumers. This research investigates the question that whether the platform should adopt AR, and clarifies AR’s value to the platform, consumers, and integrated supply chain. First, we find that AR does not necessarily benefit the platform, while it can favor the platform only if the Accuracy Effect is large and the Entertainment Effect is small. Second, a large Entertainment Effect always hurts consumers. However, the impact of the Accuracy Effect on consumers is ambiguous and differentiated by a threshold influenced by the Entertainment Effect, where a larger Entertainment Effect narrows the range in which the Accuracy Effect favors consumers. Third, the integrated supply chain performance can be enhanced by adopting AR because the manufacturer can benefit from a larger Entertainment Effect while the platform can be more profitable with a larger Accuracy Effect. In extensions, we particularly find that product publicity can make AR more likely to favor the platform only when the publicity effectiveness reaches a certain level, and consumer return cost can be a driving force for the platform to adopt AR.
{"title":"The value of Augmented Reality on platform-based supply chains: Impact of Accuracy Effect and Entertainment Effect","authors":"Qiang Zhou, Xiaolong Guo, Can Sun","doi":"10.1016/j.tre.2024.103953","DOIUrl":"https://doi.org/10.1016/j.tre.2024.103953","url":null,"abstract":"Augmented Reality (AR) has been increasingly applied in e-commerce to facilitate consumer purchasing. This paper characterizes and models two features of AR: the Accuracy Effect and Entertainment Effect. The former refers to AR mitigating consumer valuation bias, while the latter refers to the psychological entertainment consumers obtain when using AR to facilitate their purchasing. Although AR mitigates consumer valuation bias (Accuracy Effect), AR may also reduce the consumers’ prior valuation of products. In addition, despite AR increasing the consumers’ willingness to pay (through the Entertainment Effect), it exacerbates the bias between the products’ true value and the value perceived by consumers. This research investigates the question that whether the platform should adopt AR, and clarifies AR’s value to the platform, consumers, and integrated supply chain. First, we find that AR does not necessarily benefit the platform, while it can favor the platform only if the Accuracy Effect is large and the Entertainment Effect is small. Second, a large Entertainment Effect always hurts consumers. However, the impact of the Accuracy Effect on consumers is ambiguous and differentiated by a threshold influenced by the Entertainment Effect, where a larger Entertainment Effect narrows the range in which the Accuracy Effect favors consumers. Third, the integrated supply chain performance can be enhanced by adopting AR because the manufacturer can benefit from a larger Entertainment Effect while the platform can be more profitable with a larger Accuracy Effect. In extensions, we particularly find that product publicity can make AR more likely to favor the platform only when the publicity effectiveness reaches a certain level, and consumer return cost can be a driving force for the platform to adopt AR.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"118 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-07DOI: 10.1016/j.tre.2024.103955
Jingjing Yang, Xiaolong Guo, Ran Chen, Zhaotong Wang
We study an innovative autonomous vehicle storage and retrieval system equipped with a double-capacity lift (AVS/RS-DL), where the lift is capable of transporting two unit loads simultaneously. Therefore, given a set of retrieval requests, the retrieval sequencing problem consists of deciding which requests are paired together in the same tour and determining the sequence in which the requests are processed to minimize the makespan. The problem is proved to be NP-hard. We propose a two-step decomposition algorithm that first employs a greedy heuristic to identify pairs of retrieval requests. Subsequently, a dynamic programming approach, complemented by a rollout heuristic, is utilized to determine the sequence of these pairs. Comparative numerical experiments demonstrate that the algorithm leads to substantial makespan reduction compared to the methods proposed in the literature. Furthermore, we examine the benefits of the double-capacity lift against single-capacity alternatives and separate lifting tables that can operate in parallel but not pass each other. Real-world data analysis showcases the superiority of our proposed algorithm over the commonly employed first-come-first-served policy. Finally, we demonstrate that our algorithm can easily be extended to accommodate varying buffer sizes, a multi-capacity lift, and to simultaneously sequence both retrieval and storage requests.
{"title":"Retrieval request sequencing in a novel tier-captive AVS/RS with a double-capacity lift","authors":"Jingjing Yang, Xiaolong Guo, Ran Chen, Zhaotong Wang","doi":"10.1016/j.tre.2024.103955","DOIUrl":"https://doi.org/10.1016/j.tre.2024.103955","url":null,"abstract":"We study an innovative autonomous vehicle storage and retrieval system equipped with a double-capacity lift (AVS/RS-DL), where the lift is capable of transporting two unit loads simultaneously. Therefore, given a set of retrieval requests, the retrieval sequencing problem consists of deciding which requests are paired together in the same tour and determining the sequence in which the requests are processed to minimize the makespan. The problem is proved to be NP-hard. We propose a two-step decomposition algorithm that first employs a greedy heuristic to identify pairs of retrieval requests. Subsequently, a dynamic programming approach, complemented by a rollout heuristic, is utilized to determine the sequence of these pairs. Comparative numerical experiments demonstrate that the algorithm leads to substantial makespan reduction compared to the methods proposed in the literature. Furthermore, we examine the benefits of the double-capacity lift against single-capacity alternatives and separate lifting tables that can operate in parallel but not pass each other. Real-world data analysis showcases the superiority of our proposed algorithm over the commonly employed first-come-first-served policy. Finally, we demonstrate that our algorithm can easily be extended to accommodate varying buffer sizes, a multi-capacity lift, and to simultaneously sequence both retrieval and storage requests.","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"28 1","pages":""},"PeriodicalIF":10.6,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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