Pub Date : 2025-01-25DOI: 10.1016/j.ejor.2025.01.029
Luciano Ferreira , Marcos Vinicius Milan Maciel , José Valério de Carvalho , Elsa Silva , Filipe Pereira Alvelos
The Prisoner Transportation Problem is an NP-hard combinatorial problem and a complex variant of the Dial-a-Ride Problem. Given a set of requests for pick-up and delivery and a homogeneous fleet, it consists of assigning requests to vehicles to serve all requests, respecting the problem constraints such as route duration, capacity, ride time, time windows, multi-compartment assignment of conflicting prisoners and simultaneous services in order to optimize a given objective function.
In this paper, we present a new solution framework to address this problem that leads to an efficient heuristic. A comparison with computational results from previous papers shows that the heuristic is very competitive for some classes of benchmark instances from the literature and clearly superior in the remaining cases. Finally, suggestions for future studies are presented.
{"title":"A new effective heuristic for the Prisoner Transportation Problem","authors":"Luciano Ferreira , Marcos Vinicius Milan Maciel , José Valério de Carvalho , Elsa Silva , Filipe Pereira Alvelos","doi":"10.1016/j.ejor.2025.01.029","DOIUrl":"10.1016/j.ejor.2025.01.029","url":null,"abstract":"<div><div>The Prisoner Transportation Problem is an NP-hard combinatorial problem and a complex variant of the Dial-a-Ride Problem. Given a set of requests for pick-up and delivery and a homogeneous fleet, it consists of assigning requests to vehicles to serve all requests, respecting the problem constraints such as route duration, capacity, ride time, time windows, multi-compartment assignment of conflicting prisoners and simultaneous services in order to optimize a given objective function.</div><div>In this paper, we present a new solution framework to address this problem that leads to an efficient heuristic. A comparison with computational results from previous papers shows that the heuristic is very competitive for some classes of benchmark instances from the literature and clearly superior in the remaining cases. Finally, suggestions for future studies are presented.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"323 3","pages":"Pages 753-766"},"PeriodicalIF":6.0,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1016/j.ejor.2025.01.012
Dongni Li, Hongbo Jin, Yaoxin Zhang
Following the rapid evolution of manufacturing industries, customer demands may change dramatically, which challenges the conventional production systems. Seru production system (SPS) is a key to deal with uncertain varieties and fluctuating volumes. In dynamic scenarios, orders with uncertain demands arrive over time. For each arriving order, appropriate workers should be allocated to assemble it. This study investigates the dynamic worker allocation problem with the objective of maximizing the revenue obtained by the SPS. To tackle this problem, a novel algorithm that integrates actor–critic and pointer networks is proposed. The global-and-local attention mechanism and twin focus encoders are particularly designed to address the dynamic and uncertain properties of the problem. The algorithm is compared to three approaches, including the standard actor–critic algorithm, proximal policy optimization algorithm, and the approximation algorithm with the best approximation ratio, in different scenarios, i.e., small, medium, and large factories. The proposed algorithm outperforms the standard actor–critic approach and proximal policy optimization algorithm, showing performance gaps ranging from 7.23% to 37.44%. It also outperforms the approximation algorithm, with gaps between 56.73% and 96.94%. Numerical results of the three scenarios show that the proposed algorithm is more efficient and effective in handling uncertainty and dynamics, making it a promising solution for real-world manufacturing production systems.
{"title":"Dynamic worker allocation in Seru production systems with actor–critic and pointer networks","authors":"Dongni Li, Hongbo Jin, Yaoxin Zhang","doi":"10.1016/j.ejor.2025.01.012","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.01.012","url":null,"abstract":"Following the rapid evolution of manufacturing industries, customer demands may change dramatically, which challenges the conventional production systems. <ce:italic>Seru</ce:italic> production system (SPS) is a key to deal with uncertain varieties and fluctuating volumes. In dynamic scenarios, orders with uncertain demands arrive over time. For each arriving order, appropriate workers should be allocated to assemble it. This study investigates the dynamic worker allocation problem with the objective of maximizing the revenue obtained by the SPS. To tackle this problem, a novel algorithm that integrates actor–critic and pointer networks is proposed. The global-and-local attention mechanism and twin focus encoders are particularly designed to address the dynamic and uncertain properties of the problem. The algorithm is compared to three approaches, including the standard actor–critic algorithm, proximal policy optimization algorithm, and the approximation algorithm with the best approximation ratio, in different scenarios, i.e., small, medium, and large factories. The proposed algorithm outperforms the standard actor–critic approach and proximal policy optimization algorithm, showing performance gaps ranging from 7.23% to 37.44%. It also outperforms the approximation algorithm, with gaps between 56.73% and 96.94%. Numerical results of the three scenarios show that the proposed algorithm is more efficient and effective in handling uncertainty and dynamics, making it a promising solution for real-world manufacturing production systems.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"38 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1016/j.ejor.2024.12.047
Diego Delle Donne, Alberto Santini, Claudia Archetti
We tackle the problem of coordinating a three-echelon last-mile delivery system. In the first echelon, trucks transport parcels from distribution centres outside the city to public transport stops. In the second echelon, the parcels move on public transport and reach the city centre. In the third echelon, zero-emission vehicles pick up the parcels at public transport stops and deliver them to customers. We introduce two extended formulations for this problem. The first has two exponential sets of variables, while the second has one. We propose column generation algorithms and compare several methods to solve the pricing problems on specially constructed graphs. We also devise dual bounds, which we can compute even when the graphs are so large that not a single pricing round completes within the time limit. Compared to previous formulations, our models find 16 new best known solutions out of an existing dataset of 24 instances from the literature.
{"title":"Integrating public transport in sustainable last-mile delivery: Column generation approaches","authors":"Diego Delle Donne, Alberto Santini, Claudia Archetti","doi":"10.1016/j.ejor.2024.12.047","DOIUrl":"https://doi.org/10.1016/j.ejor.2024.12.047","url":null,"abstract":"We tackle the problem of coordinating a three-echelon last-mile delivery system. In the first echelon, trucks transport parcels from distribution centres outside the city to public transport stops. In the second echelon, the parcels move on public transport and reach the city centre. In the third echelon, zero-emission vehicles pick up the parcels at public transport stops and deliver them to customers. We introduce two extended formulations for this problem. The first has two exponential sets of variables, while the second has one. We propose column generation algorithms and compare several methods to solve the pricing problems on specially constructed graphs. We also devise dual bounds, which we can compute even when the graphs are so large that not a single pricing round completes within the time limit. Compared to previous formulations, our models find 16 new best known solutions out of an existing dataset of 24 instances from the literature.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"34 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1016/j.ejor.2025.01.020
Jana Ralfs, Dai T. Pham, Gudrun P. Kiesmüller
This paper examines a single-echelon inventory system that fulfills stochastic orders from a production facility using a time-based shipment consolidation strategy. In this system, the production facility provides advance demand information to the warehouse, ensuring that all orders are placed with a positive demand lead time. Using value iteration, we identify the optimal outbound shipment quantities while accounting for costs related to early deliveries, late deliveries, and shipments. Additionally, this research highlights the impact of advance demand information on transportation capacity planning and the optimization of load factors
{"title":"Optimal outbound shipment policy for an inventory system with advance demand information","authors":"Jana Ralfs, Dai T. Pham, Gudrun P. Kiesmüller","doi":"10.1016/j.ejor.2025.01.020","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.01.020","url":null,"abstract":"This paper examines a single-echelon inventory system that fulfills stochastic orders from a production facility using a time-based shipment consolidation strategy. In this system, the production facility provides advance demand information to the warehouse, ensuring that all orders are placed with a positive demand lead time. Using value iteration, we identify the optimal outbound shipment quantities while accounting for costs related to early deliveries, late deliveries, and shipments. Additionally, this research highlights the impact of advance demand information on transportation capacity planning and the optimization of load factors","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"16 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143385314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1016/j.ejor.2025.01.024
Simon Emde, Ana Alina Tudoran
Urban logistics has been recognized as one of the most complex and expensive part of e-commerce supply chains. An increasing share of this complexity comes from the first mile, where shipments are initially picked up to be fed into the transportation network. First-mile pickup volumes have become fragmented due to the enormous growth of e-commerce marketplaces, which allow even small-size vendors access to the global market. These local vendors usually cannot palletize their own shipments but instead rely on containers provided by a logistics provider. From the logistics provider’s perspective, this situation poses the following novel problem: from a given pool of containers, how many containers of what size should each vendor receive when? It is neither desirable to supply too little container capacity because undersupply leads to shipments being loose-loaded, i.e., loaded individually without consolidation in a container; nor should the assigned containers be too large because oversupply wastes precious space. We demonstrate NP-hardness of the problem and develop a matheuristic, which uses a mathematical solver to assemble partial container assignments into complete solutions. The partial assignments are generated with the help of a deep neural network (DNN), trained on realistic data from a European e-commerce logistics provider. The deep learning-assisted matheuristic allows serving the same number of vendors with about 6% fewer routes than the rule of thumb used in practice due to better vehicle utilization. We also investigate the trade-off between loose-loaded shipments and space utilization and the effect on the routes of the collection vehicles.
{"title":"The first mile is the hardest: A deep learning-assisted matheuristic for container assignment in first-mile logistics","authors":"Simon Emde, Ana Alina Tudoran","doi":"10.1016/j.ejor.2025.01.024","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.01.024","url":null,"abstract":"Urban logistics has been recognized as one of the most complex and expensive part of e-commerce supply chains. An increasing share of this complexity comes from the first mile, where shipments are initially picked up to be fed into the transportation network. First-mile pickup volumes have become fragmented due to the enormous growth of e-commerce marketplaces, which allow even small-size vendors access to the global market. These local vendors usually cannot palletize their own shipments but instead rely on containers provided by a logistics provider. From the logistics provider’s perspective, this situation poses the following novel problem: from a given pool of containers, how many containers of what size should each vendor receive when? It is neither desirable to supply too little container capacity because undersupply leads to shipments being loose-loaded, i.e., loaded individually without consolidation in a container; nor should the assigned containers be too large because oversupply wastes precious space. We demonstrate NP-hardness of the problem and develop a matheuristic, which uses a mathematical solver to assemble partial container assignments into complete solutions. The partial assignments are generated with the help of a deep neural network (DNN), trained on realistic data from a European e-commerce logistics provider. The deep learning-assisted matheuristic allows serving the same number of vendors with about 6% fewer routes than the rule of thumb used in practice due to better vehicle utilization. We also investigate the trade-off between loose-loaded shipments and space utilization and the effect on the routes of the collection vehicles.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"39 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-23DOI: 10.1016/j.ejor.2025.01.031
Chen Zhu, Georges Zaccour
Motivated by the emergence of offline and online donations, this paper explores the interplay between charitable donations and strategic choice of sales mode in a philanthropic supply chain consisting of a manufacturer and a platform. We consider two donation strategies, offline donations and both offline and online donations that are traceable by blockchain technology, and two business models, i.e., reselling sales mode and agency sales mode. Donations by the manufacturer are used to boost its charitable image, which in turn affects positively the demand. As such image can only be built over time, we adopt a differential game formalism that captures both the strategic interactions between the two players and the dynamic nature of the problem. We characterize and compare the equilibrium strategies and outcomes for different choices of selling mode and donation option. Our findings can be summarized as follows. First, we obtain that only under some conditions that online donations enhance the charitable image, members’ profits, consumer surplus, and social welfare. Second, regardless of the sales mode, the conditions for the platform to adopt online donations are the most stringent, and the conditions for the enhancement of the charitable image are the most lenient. Third, the implementation of online donations does not have much impact on the Pareto regions of the agency mode but has a much greater impact on the Pareto regions of the reselling mode, especially for medium and large online donation amounts. These changes hinge on the trade-offs for members between online and offline donations.
{"title":"The interplay between charitable donation strategies and sales mode selection in the platform","authors":"Chen Zhu, Georges Zaccour","doi":"10.1016/j.ejor.2025.01.031","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.01.031","url":null,"abstract":"Motivated by the emergence of offline and online donations, this paper explores the interplay between charitable donations and strategic choice of sales mode in a philanthropic supply chain consisting of a manufacturer and a platform. We consider two donation strategies, offline donations and both offline and online donations that are traceable by blockchain technology, and two business models, i.e., reselling sales mode and agency sales mode. Donations by the manufacturer are used to boost its charitable image, which in turn affects positively the demand. As such image can only be built over time, we adopt a differential game formalism that captures both the strategic interactions between the two players and the dynamic nature of the problem. We characterize and compare the equilibrium strategies and outcomes for different choices of selling mode and donation option. Our findings can be summarized as follows. First, we obtain that only under some conditions that online donations enhance the charitable image, members’ profits, consumer surplus, and social welfare. Second, regardless of the sales mode, the conditions for the platform to adopt online donations are the most stringent, and the conditions for the enhancement of the charitable image are the most lenient. Third, the implementation of online donations does not have much impact on the Pareto regions of the agency mode but has a much greater impact on the Pareto regions of the reselling mode, especially for medium and large online donation amounts. These changes hinge on the trade-offs for members between online and offline donations.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"20 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-22DOI: 10.1016/j.ejor.2024.12.048
Xiaohuan Lyu , Eduardo Lalla-Ruiz , Frederik Schulte
Recent supply chain disruptions and crisis response policies (e.g., the COVID-19 pandemic and the Red Sea crisis) have highlighted the role of container terminals as crucial and scarce resources in the global economy. To tackle these challenges, the industry increasingly aims for advanced operational collaboration among multiple stakeholders, as demonstrated by the ambitions of the recently founded Gemini alliance. Nonetheless, collaborative planning models often disregard the requirements and incentives of stakeholders or simply solve idealized small instances. Motivated by the above, we design novel and effective collaboration mechanisms among terminal operators that share the resources (berths and quay cranes). We first define the collaborative berth allocation problem and propose a mixed integer linear programming (MILP) model to minimize the total cost of all terminals, referred to as the coalitional costs. We adopt the core and the nucleolus concepts from cooperative game theory to allocate the coalitional costs such that stakeholders have stable incentives to collaborate. To obtain solutions for realistic instance sizes, we propose two exact row-generation-based core and nucleolus algorithms that are versatile and can be used for various combinatorial optimization problems. To the best of our knowledge, the proposed row-generation approach for the nucleolus is the first of its kind for combinatorial optimization problems. Extensive experiments demonstrate that the collaborative berth allocation approach achieves up to 28.44% of cost savings, increasing the solution space in disruptive situations, while the proposed core and nucleolus solutions guarantee the collaboration incentives for individual terminals.
{"title":"The collaborative berth allocation problem with row-generation algorithms for stable cost allocations","authors":"Xiaohuan Lyu , Eduardo Lalla-Ruiz , Frederik Schulte","doi":"10.1016/j.ejor.2024.12.048","DOIUrl":"10.1016/j.ejor.2024.12.048","url":null,"abstract":"<div><div>Recent supply chain disruptions and crisis response policies (e.g., the COVID-19 pandemic and the Red Sea crisis) have highlighted the role of container terminals as crucial and scarce resources in the global economy. To tackle these challenges, the industry increasingly aims for advanced operational collaboration among multiple stakeholders, as demonstrated by the ambitions of the recently founded Gemini alliance. Nonetheless, collaborative planning models often disregard the requirements and incentives of stakeholders or simply solve idealized small instances. Motivated by the above, we design novel and effective collaboration mechanisms among terminal operators that share the resources (berths and quay cranes). We first define the collaborative berth allocation problem and propose a mixed integer linear programming (MILP) model to minimize the total cost of all terminals, referred to as the coalitional costs. We adopt the core and the nucleolus concepts from cooperative game theory to allocate the coalitional costs such that stakeholders have stable incentives to collaborate. To obtain solutions for realistic instance sizes, we propose two exact row-generation-based core and nucleolus algorithms that are versatile and can be used for various combinatorial optimization problems. To the best of our knowledge, the proposed row-generation approach for the nucleolus is the first of its kind for combinatorial optimization problems. Extensive experiments demonstrate that the collaborative berth allocation approach achieves up to 28.44% of cost savings, increasing the solution space in disruptive situations, while the proposed core and nucleolus solutions guarantee the collaboration incentives for individual terminals.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"323 3","pages":"Pages 888-906"},"PeriodicalIF":6.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143049752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-22DOI: 10.1016/j.ejor.2025.01.015
Sofia Henriques, Ana Paias
In this work, we address two variants of the Period Travelling Salesman Problem: one where some nodes cannot be visited consecutively over the time horizon, and another one where this restriction is not imposed. A new flow-based formulation that uses specific information about the visit patterns of nodes is studied and empirical tests show that it is able to solve test instances where a flow-based formulation based on the Single Commodity Flow formulation for the Travelling Salesman Problem reached the time limit. Non-compact formulations are studied in this work as well. We propose two new sets of exponentially-sized valid inequalities that have not been studied yet in the literature. A formulation which is based on connectivity cuts per period enhanced with these sets of valid inequalities proved to be the most efficient and it was able to solve several instances.
{"title":"Formulations and Branch-and-cut algorithms for the Period Travelling Salesman Problem","authors":"Sofia Henriques, Ana Paias","doi":"10.1016/j.ejor.2025.01.015","DOIUrl":"10.1016/j.ejor.2025.01.015","url":null,"abstract":"<div><div>In this work, we address two variants of the Period Travelling Salesman Problem: one where some nodes cannot be visited consecutively over the time horizon, and another one where this restriction is not imposed. A new flow-based formulation that uses specific information about the visit patterns of nodes is studied and empirical tests show that it is able to solve test instances where a flow-based formulation based on the Single Commodity Flow formulation for the Travelling Salesman Problem reached the time limit. Non-compact formulations are studied in this work as well. We propose two new sets of exponentially-sized valid inequalities that have not been studied yet in the literature. A formulation which is based on connectivity cuts per period enhanced with these sets of valid inequalities proved to be the most efficient and it was able to solve several instances.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"323 3","pages":"Pages 739-752"},"PeriodicalIF":6.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-22DOI: 10.1016/j.ejor.2025.01.009
Emre Kirac, Ashlea Bennett Milburn, Ridvan Gedik
This study introduces a new dynamic routing problem, namely the Dynamic Team Orienteering Problem (DTOP), which is a dynamic variant of the Team Orienteering Problem (TOP). In the DTOP, some customer locations are known a priori, while others are dynamic, with each location associated with a profit value. The goal is to maximize the sum of collected profits by visiting a set of customer locations within a time limit. This problem arises in several practical applications such as disaster relief, technician, tourist, and school bus routing problems. We adopt a Multiple Plan Approach (MPA) to solve the proposed problem, utilizing both a consensus function method and a demand-served method to select the distinguished plan—the most promising solution from a pool of alternative routing plans. To assess the effectiveness of these methods, we employ a sophisticated greedy algorithm tailored to address the unique challenges posed by the DTOP. In addition, we employ a reference offline algorithm designed for solving the static variant of the problem. To facilitate our evaluation, we introduce a comprehensive set of 1161 new benchmark instances for the DTOP, adapted from well-established TOP benchmark instances. Our comparative analysis centers on the average percentage deviation of algorithmic solutions from the reference offline solutions.
{"title":"The Dynamic Team Orienteering Problem","authors":"Emre Kirac, Ashlea Bennett Milburn, Ridvan Gedik","doi":"10.1016/j.ejor.2025.01.009","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.01.009","url":null,"abstract":"This study introduces a new dynamic routing problem, namely the Dynamic Team Orienteering Problem (DTOP), which is a dynamic variant of the Team Orienteering Problem (TOP). In the DTOP, some customer locations are known a priori, while others are dynamic, with each location associated with a profit value. The goal is to maximize the sum of collected profits by visiting a set of customer locations within a time limit. This problem arises in several practical applications such as disaster relief, technician, tourist, and school bus routing problems. We adopt a Multiple Plan Approach (MPA) to solve the proposed problem, utilizing both a consensus function method and a demand-served method to select the distinguished plan—the most promising solution from a pool of alternative routing plans. To assess the effectiveness of these methods, we employ a sophisticated greedy algorithm tailored to address the unique challenges posed by the DTOP. In addition, we employ a reference offline algorithm designed for solving the static variant of the problem. To facilitate our evaluation, we introduce a comprehensive set of 1161 new benchmark instances for the DTOP, adapted from well-established TOP benchmark instances. Our comparative analysis centers on the average percentage deviation of algorithmic solutions from the reference offline solutions.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"55 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143385315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-21DOI: 10.1016/j.ejor.2025.01.016
Jiayan Xu , Housheng Duan , Sijing Deng
Corporate social responsibility (CSR) has a strong impact on the external image of the enterprise. The violation of CSR not only harms the enterprise but also negatively affects other firms in the supply chain. This paper establishes a game-theoretical model to study the management of social responsibility efforts with considerations of violation probability. The upstream manufacturer and downstream retailer can reduce the violation probability by exerting CSR efforts. Specifically, we study the following four models, including both participants exerting efforts, only the manufacturer exerting effort, only the retailer exerting effort, and neither participant exerting effort. Our analysis shows that as the effort cost of the manufacturer increases, the retailer may increase or decrease his effort level under both participants exerting efforts, due to the complementary and substitution effects between the efforts of the manufacturer and retailer. We also find that compared with both participants exerting efforts, the retailer may increase or decrease his effort level under only the retailer exerting effort, and the effort level of the manufacturer may grow or shrink under only the manufacturer exerting effort. In addition, we study the decision matrix for the manufacturer and retailer, and find that in equilibrium the manufacturer always has incentives to exert CSR effort, while the retailer may prefer a free ride and sometimes chooses not to exert effort. Interestingly, we find that the total supply chain profit may not be the highest under both participants exerting efforts, but it is the lowest under neither participant exerting effort.
{"title":"Managing social responsibility efforts with the consideration of violation probability","authors":"Jiayan Xu , Housheng Duan , Sijing Deng","doi":"10.1016/j.ejor.2025.01.016","DOIUrl":"10.1016/j.ejor.2025.01.016","url":null,"abstract":"<div><div>Corporate social responsibility (CSR) has a strong impact on the external image of the enterprise. The violation of CSR not only harms the enterprise but also negatively affects other firms in the supply chain. This paper establishes a game-theoretical model to study the management of social responsibility efforts with considerations of violation probability. The upstream manufacturer and downstream retailer can reduce the violation probability by exerting CSR efforts. Specifically, we study the following four models, including both participants exerting efforts, only the manufacturer exerting effort, only the retailer exerting effort, and neither participant exerting effort. Our analysis shows that as the effort cost of the manufacturer increases, the retailer may increase or decrease his effort level under both participants exerting efforts, due to the complementary and substitution effects between the efforts of the manufacturer and retailer. We also find that compared with both participants exerting efforts, the retailer may increase or decrease his effort level under only the retailer exerting effort, and the effort level of the manufacturer may grow or shrink under only the manufacturer exerting effort. In addition, we study the decision matrix for the manufacturer and retailer, and find that in equilibrium the manufacturer always has incentives to exert CSR effort, while the retailer may prefer a free ride and sometimes chooses not to exert effort. Interestingly, we find that the total supply chain profit may not be the highest under both participants exerting efforts, but it is the lowest under neither participant exerting effort.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"323 3","pages":"Pages 852-867"},"PeriodicalIF":6.0,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143049754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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