Computers & Operations Research最新文献

{"title":"Replication and sequencing of unreliable jobs on m parallel machines: New results","authors":"Alessandro Agnetis ,&nbsp;Mario Benini ,&nbsp;Paolo Detti ,&nbsp;Ben Hermans ,&nbsp;Marco Pranzo ,&nbsp;Kevin Schewior","doi":"10.1016/j.cor.2025.107085","DOIUrl":"10.1016/j.cor.2025.107085","url":null,"abstract":"<div><div>This paper gives new results for the problem of sequencing <span><math><mi>m</mi></math></span> copies of <span><math><mi>n</mi></math></span> unreliable jobs (i.e., jobs that have a certain probability of being successfully carried out) on <span><math><mi>m</mi></math></span> parallel machines (one copy per machine). A job is carried out if at least one of its copies is successfully completed, in which case a certain revenue is earned. If the copy of a job fails, the corresponding machine is blocked and cannot perform the subsequently scheduled job copies. The problem is to sequence the <span><math><mi>n</mi></math></span> copies of each job on each of the <span><math><mi>m</mi></math></span> machines in order to maximize the expected revenue. For the case of <span><math><mrow><mi>m</mi><mo>=</mo><mn>2</mn></mrow></math></span>, Agnetis et al. (2022) proposed a metaheuristic approach and some upper bounding schemes. Here we address the general <span><math><mi>m</mi></math></span>-machine problem, giving a simple <span><math><mrow><mo>(</mo><mn>1</mn><mo>−</mo><mn>1</mn><mo>/</mo><mi>e</mi><mo>)</mo></mrow></math></span>-approximation algorithm, an even simpler algorithm, for which we show a tight logarithmic approximation guarantee, and an additional heuristic as well as an additional metaheuristic. We provide computational results, which, along with a new upper-bounding scheme, establish the effectiveness of our approaches in practice.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107085"},"PeriodicalIF":4.1,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating lot-sizing and pricing decisions in multi-channel markets with discrete menus of prices","authors":"Mourad Terzi ,&nbsp;Yassine Ouazene ,&nbsp;Alice Yalaoui ,&nbsp;Farouk Yalaoui","doi":"10.1016/j.cor.2025.107131","DOIUrl":"10.1016/j.cor.2025.107131","url":null,"abstract":"<div><div>This paper presents a model for coordinating lot-sizing and pricing decisions for manufacturers operating in multichannel markets with limited production capacity. Integrating these decisions is a significant challenge for manufacturers because it allows them to align their marketing and operational strategies effectively. This study addresses the application of attraction models to characterize consumers’ preferences and switching behavior between sales channels. Initially, the problem is formulated as a non-convex mixed-integer nonlinear programming (<em>MINLP</em>) model that incorporates production capacity constraints and a discrete menu of prices for each channel. To overcome the challenges of nonlinearity and nonconvexity, the problem is reformulated as an exact mixed-integer linear programming (<em>MILP</em>) model. Then, two <em>MILP</em>-based heuristics, the Fix-and-Relax and Double-Fix-and-Relax methods, are designed to solve the problem efficiently. An illustrative example demonstrates the model’s practical application and offers valuable insights for decision-makers in real-life scenarios. Furthermore, a comprehensive experimental study on 120 benchmark instances shows that the proposed solution methods achieve near-optimal solutions in less than one minute of computational time.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107131"},"PeriodicalIF":4.1,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144124051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-dependent electric vehicle-drone routing problem for scheduled deliveries and on-demand pickups considering variable drone speeds and no-fly zones","authors":"Xiaoxue Ren ,&nbsp;Houming Fan ,&nbsp;Hao Fan ,&nbsp;Mengzhi Ma","doi":"10.1016/j.cor.2025.107141","DOIUrl":"10.1016/j.cor.2025.107141","url":null,"abstract":"<div><div>This paper introduces the time-dependent electric vehicle-drone routing problem for scheduled deliveries and on-demand pickups considering variable drone speeds and no-fly zones (TDEVDRP-SDOP-VDS-NZ), involving multiple electric vehicles (EVs) and unmanned aerial vehicles (UAVs) to serve scheduled delivery customer requests (SDCRs) and on-demand pickup customer requests (OPCRs) with deadlines, while considering time-dependent EV speeds, variable drone speeds and no-fly zones. For TDEVDRP-SDOP-VDS-NZ, a route-based Markov decision process (MDP) model is formulated to maximize rewards, and the offline-online heuristic algorithm (OOHA) is proposed, combining the static EV-UAV joint delivery routes with online OPCR insertions. Experimental results show a 0.23 % decrease in average reward compared to the perfect-information counterpart, with deterministic scenarios achieving an average reward higher than uncertain scenarios. OOHA outperforms two benchmark algorithms, with gaps ranging from −6.57 % to −0.31 %. As the degree of dynamism increases, both rewards and OPCR acceptance ratios decrease. Rewards drop by over 10% when the degree of dynamism rises from 0.2 to 0.5, while higher variability leads to an increase in rewards. The average online processing time remains under 0.2 s, allowing the system to quickly respond to new OPCRs in real-time. OOHA demonstrates strong stability across different customer distributions. Sensitivity analysis reveals that an increase in the number of no-fly zones decreases both rewards and the ratio of OPCRs served by UAVs, particularly the ratio, which drops by over 16%. Sensitivity analysis of UAV flight speeds finds that variable drone speeds outperform maximum and minimum speeds, with maximum and minimum speeds leading to a more than 60% drop in the ratio of OPCRs served by UAVs. TDEVDRP-SDOP-VDS-NZ, although having a longer average online processing time compared to the model of <span><span>Gu et al. (2023)</span></span>, is more in line with the actual distribution.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107141"},"PeriodicalIF":4.1,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Home health care routing and scheduling problems considering patient classification and outsourcing: Modeling and a solution algorithm","authors":"Xiaomeng Ma ,&nbsp;Xujin Pu ,&nbsp;Yaping Fu ,&nbsp;Kaizhou Gao ,&nbsp;Yuchen Xu","doi":"10.1016/j.cor.2025.107143","DOIUrl":"10.1016/j.cor.2025.107143","url":null,"abstract":"<div><div>Home health care (HHC) is treated as a substitute for hospitalization and plays a crucial role in relieving the pressure of medical resources resulting from population aging. HHC routing and scheduling problems have received much attention in modeling and optimization fields. This paper proposes a multi-objective HHC routing and scheduling problem considering patient classification and outsourcing operation, in which patients are classified into two types, i.e., VIP patients and ordinary patients. All the patients are assigned to an HHC center or outsourced to third-party service providers. Then, the caregivers in the HHC center are scheduled to provide services for the assigned patients. First, a mixed integer programming model with minimizing total operation cost and minimizing total tardiness is established. Second, a Q-learning-based multi-objective evolutionary algorithm with problem-specific knowledge (QMEA-K) is specially devised. At last, numerous experiments are carried out by making comparisons between QMEA-K and four algorithms and an exact solver CPLEX. The acquired results prove the effectiveness and advantages of QMEA-K in tackling the concerned problem.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107143"},"PeriodicalIF":4.1,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint location and pricing for recycling service planning","authors":"Qihang Liu ,&nbsp;Jichang Dong ,&nbsp;Ying Liu ,&nbsp;Luming Yang","doi":"10.1016/j.cor.2025.107114","DOIUrl":"10.1016/j.cor.2025.107114","url":null,"abstract":"<div><div>This paper explores an emerging business model for Waste Recycling Platforms that collect users’ recycling demands online and provide door-to-door recycling services offline. Unlike existing literature, which typically assumes constant user demand, we account for demand uncertainty and develop a location optimization model using two-stage stochastic programming. By analyzing the relationship between random demand and recycling prices, we extend this model to a joint location-pricing model. We also design a Benders Decomposition-based algorithm to solve the model using actual operational data from a Waste Recycling Platform in Beijing. Our findings reveal that incorporating both location and pricing decisions into the model makes it more realistic and capable of yielding better optimal profits. Additionally, parameter analysis suggests that the platform could benefit from moderately relaxing the confidence level of its random constraints and focusing more on controlling operating costs.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107114"},"PeriodicalIF":4.1,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating a Simulated Annealing metaheuristic for the Heterogeneous On-Demand Bus Routing Problem with a novel experimental setup","authors":"Michell Queiroz,&nbsp;Kenneth Sörensen","doi":"10.1016/j.cor.2025.107116","DOIUrl":"10.1016/j.cor.2025.107116","url":null,"abstract":"<div><div>This work addresses the Heterogeneous On-Demand Bus Routing Problem (H-ODBRP), a problem involving the efficient management of transportation requests in an urban setting. Passengers are picked up and dropped off at designated stations near their origin and destination points by a fleet of heterogeneous vehicles. The primary objective is to minimize the total user ride time (URT) for all passengers. A metaheuristic, based on the Simulated Annealing framework, is introduced to provide effective solutions to this problem. A new Integer Programming formulation is also proposed and used to evaluate the solution quality of the proposed metaheuristic on small instances with up to 14 requests. This study contributes to the literature by providing the first insights into the On-Demand Bus Routing Problem using a heterogeneous fleet of vehicles. The results show that, in the instances examined, vehicles with 12 or more seats are rarely utilized. Furthermore, introducing some degree of randomness in selecting vehicle capacity for assigning passengers to empty vehicles proves to be more beneficial than choosing capacity strictly based on demand. A distinctive feature of this study is its focus on the impact of different instance properties, offering a novel experimental setup that could provide fresh insights into on-demand transportation problems.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107116"},"PeriodicalIF":4.1,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144106835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An approximation algorithm for multi-allocation hub location problems","authors":"Niklas Jost","doi":"10.1016/j.cor.2025.107118","DOIUrl":"10.1016/j.cor.2025.107118","url":null,"abstract":"<div><div>The multi allocation <span><math><mi>p</mi></math></span>-hub median problem (MApHM), the multi allocation uncapacitated hub location problem (MAuHLP) and the multi allocation <span><math><mi>p</mi></math></span>-hub location problem (MApHLP) are common hub location problems with several practical applications. HLPs combine the task of constructing a network and solving a routing on that network. Specifically, a set of hubs must be chosen and each routing must be performed using one or two hubs as stopovers. The costs between two hubs are discounted by a parameter <span><math><mi>α</mi></math></span>. The objective is to minimize the total transportation cost in the MApHM and additionally to minimize the set-up costs for the hubs in the MAuHLP and MApHLP. In this paper, an approximation algorithm to solve these problems is developed, which improves the approximation bound for MAuHLP to 2.408.</div><div>The proposed algorithm reduces the HLPs to Facility Location Problems (FLPs), incorporating the idea of preferring hubs in the direction of the destination. Depending on the HLP, different FLP approximation algorithms with approximation bound <span><math><mi>γ</mi></math></span> are used. In cases where the discount factor satisfies <span><math><mrow><mn>0</mn><mo>&lt;</mo><mi>α</mi><mo>&lt;</mo><mfrac><mrow><mn>1</mn></mrow><mrow><mi>γ</mi></mrow></mfrac></mrow></math></span> or <span><math><mrow><mi>α</mi><mo>≥</mo><mn>0</mn><mo>.</mo><mn>619</mn></mrow></math></span>, the resulting approximation bound still improves upon the current state of the art.</div><div>The proposed algorithm is capable of solving much bigger instances than any exact algorithm in the literature. New benchmark instances have been created and published, such that HLP algorithms can be tested and compared on standardized huge instances. There, the proposed algorithm outperformed the previous best approximation algorithm in nearly all test instances.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107118"},"PeriodicalIF":4.1,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nash equilibria and the price of anarchy under SPT-LPT mixed coordination mechanism in distributed manufacturing","authors":"Long Zhang ,&nbsp;Zhiwen Wang ,&nbsp;Wei Sheng","doi":"10.1016/j.cor.2025.107117","DOIUrl":"10.1016/j.cor.2025.107117","url":null,"abstract":"<div><div>In the distributed manufacturing of new energy vehicle components, achieving a balance between the self-interested behaviors of individual production departments and the factory’s overall objectives is critical. This paper addresses this challenge by developing game-theoretic models to analyze the impact of a mixed coordination mechanism — specifically, those combining Shortest Processing Time (SPT) and Longest Processing Time (LPT) rules — on the existence of Nash equilibria (NE) and the Price of Anarchy (PoA). We propose different algorithms tailored to the parallel and uniform equipment-models, each capable of producing NE; and provide upper bounds of the PoA from the perspective of both equipment utilization and operational efficiency in theory. We conduct simulation analyses based on randomly generated instances to evaluate the average PoAs of our algorithms, which are consistent with the theoretical results. Our findings offer valuable managerial insights by elucidating how technological parameters, such as equipment number, type, and the degree of coordination, influence production performance in distributed manufacturing systems.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107117"},"PeriodicalIF":4.1,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Syncrolift dry dock scheduling with a capacitated ship transfer system","authors":"Hao Guan,&nbsp;Mengtong Wang,&nbsp;Qiang Meng","doi":"10.1016/j.cor.2025.107138","DOIUrl":"10.1016/j.cor.2025.107138","url":null,"abstract":"<div><div>Despite the rapidly increasing maintenance demand driven by an aging fleet and the growth of global fleet size, optimizing dry dock operations remains an underexplored area in academic research. This study addresses this gap by focusing on enhancing efficiency through improved dry dock scheduling, aiming to alleviate the growing disparity between maintenance needs and limited dry dock resources. We propose a practical syncrolift dry dock scheduling problem that incorporates a capacitated ship transfer system, which requires determining the optimal sequence of ship maintenance services to minimize total waiting time. A mixed-integer linear programming (MILP) model is developed to effectively tackle the challenges of this problem, particularly the ship transfer system—a critical bottleneck involving the syncrolift and railways—by modeling it as a series of segments with varying capacities and transfer restrictions. The model accommodates the complexities of the scheduling process, such as limited transfer capacity, diverse segment characteristics, bidirectional ship transfer flows, ship compatibility constraints, and sequence-dependent setup times. Recognizing the NP-hard nature of the problem, we introduce a novel column-generation-based heuristic method to solve the MILP model efficiently. The efficacy of the proposed solution method is validated through extensive numerical experiments using real operational data from the NOSCO shipyard. Results demonstrate significant improvements in operational efficiency, with ship waiting times reduced by 32.5% compared to first-come-first-served scheduling solutions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107138"},"PeriodicalIF":4.1,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SDP-based Benders decomposition for solving p-median quadratic facility location problems","authors":"Yingying Yang,&nbsp;Hoa T. Bui,&nbsp;Ryan Loxton","doi":"10.1016/j.cor.2025.107119","DOIUrl":"10.1016/j.cor.2025.107119","url":null,"abstract":"<div><div>The <span><math><mi>p</mi></math></span>-median facility location problem involves selecting the locations for <span><math><mi>p</mi></math></span> facilities from a set of potential locations, to balance the trade-off between facility establishment costs and distance to end users. In this paper, we introduce an extension, named the <span><math><mi>p</mi></math></span>-median quadratic facility location problem, that also considers inter-facility distance—important in applications where the facilities serve as intermediate hubs linking sites in different regions. This creates a quadratic term in the objective that makes the problem nonlinear. We develop a Benders decomposition method that uses a tight semi-definite programming relaxation of the Benders master problem, instead of solving the nonlinear master problem directly. We incorporate this decomposition strategy into a branch and bound framework to ensure convergence. Our numerical results show that this method outperforms the linear reformulation and classical Benders decomposition techniques, working independently or in tandem.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"182 ","pages":"Article 107119"},"PeriodicalIF":4.1,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}