Computers & Operations Research最新文献

{"title":"Lagrangian Relaxation for Airport Gate Assignment Problem","authors":"Göksu Ece Okur ,&nbsp;Özlem Karsu ,&nbsp;Oğuz Solyalı","doi":"10.1016/j.cor.2025.107186","DOIUrl":"10.1016/j.cor.2025.107186","url":null,"abstract":"<div><div>In this paper we focus on the Airport Gate Assignment Problem that minimizes the total walking distance of passengers while ensuring that the number of aircraft assigned to apron is at its minimum. We utilize an alternative formulation for the problem compared to the ones in the literature and propose approaches based on Lagrangian relaxation so as to obtain tight lower bounds. The method also harnesses the power of a good initial upper bound and provides good quality solutions. To the best of our knowledge, the current studies in the literature rely only on upper bounds or the linear relaxation lower bounds, which are hard to obtain when the problem size is large, to assess the quality of heuristic solutions. We propose using the tighter Lagrangian relaxation-based bounds as a better reference to assess solution quality. Our computational experiments demonstrate that the new formulation we propose yields tighter lower bounds compared to previous formulations in the literature. Moreover, our Lagrangian relaxation-based method returns even stronger lower bounds than those obtained by solving mixed integer programming formulations or their linear relaxations by an off-the-shelf solver.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107186"},"PeriodicalIF":4.1,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655391","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":"Dynamic programming in inventory management: A review","authors":"Edson Antônio Gonçalves de Souza ,&nbsp;Tanja Mlinar ,&nbsp;Maud Van den Broeke ,&nbsp;Stefan Creemers","doi":"10.1016/j.cor.2025.107164","DOIUrl":"10.1016/j.cor.2025.107164","url":null,"abstract":"<div><div>Inventory Management (IM) research has significantly advanced, with increasingly complex and realistic inventory problems being investigated. Dynamic Programming (DP) plays an increasingly vital role to find viable solutions to these problems, particularly in balancing the trade-off between good-quality solutions and computational efficiency. While previous literature reviews have primarily focused on either IM or DP independently, or have studied very specific IM–DP settings, we are the first to provide a comprehensive overview of the interaction between IM and DP. By analyzing 278 relevant articles, we explore how DP methodologies are applied across various inventory problems, identifying key trends, challenges, and research gaps. We introduce a unique typology to classify these articles based on the type and structure of the inventory problem and DP methodology employed. Additionally, our review provides insights into practical applications of DP in IM, and examines the current and potential future integration of sustainability and technology topics in this area.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107164"},"PeriodicalIF":4.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678819","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":"Tight upper and lower bounds for the quadratic knapsack problem through binary decision diagrams","authors":"M. Eliass Fennich ,&nbsp;Leandro C. Coelho ,&nbsp;Franklin Djeumou Fomeni","doi":"10.1016/j.cor.2025.107197","DOIUrl":"10.1016/j.cor.2025.107197","url":null,"abstract":"<div><div>The Quadratic Knapsack Problem (QKP) is a challenging combinatorial optimization problem that has attracted significant attention due to its complexity and practical applications. In recent years, Binary Decision Diagrams (BDDs) have emerged as a powerful tool in combinatorial optimization, providing efficient bounds. In the literature of the QKP, all the exact methods are based on computing tight bounds before applying branch-and-bound (B&amp;B) schemes. We advance this literature in this work by leveraging BDDs to compute bounds more effectively. We propose a novel integration of dual-bound tightening within a BDD-based B&amp;B framework, employing a Breadth-First Search (BFS) strategy. Our approach addresses the critical limitation of existing BDD-based B&amp;B methods, which often lack robust dual-bound tightening mechanisms. Furthermore, we propose several efficient compilation techniques of BDDs for the QKP. Through extensive experimentation on several categories of QKP instances, we demonstrate that our method competes and often surpasses the bounding stages of the leading exact algorithms. Notably, our approach reduces the average duality gap by up to 10% for the class of Hidden Clique QKP instances, showcasing its potential. Furthermore, our findings indicate that the BFS B&amp;B method outperforms state-of-the-art BDD B&amp;B approaches across all tested QKP instances, highlighting its effectiveness and potential for broader application.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"184 ","pages":"Article 107197"},"PeriodicalIF":4.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714246","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":"Logic-based Benders decomposition for doctor-patient matching and scheduling considering chronic patients’ online consultation time preference","authors":"Yan-ping Jiang,&nbsp;Yan Zhang,&nbsp;Zhan Gao,&nbsp;Ting-wen Zheng","doi":"10.1016/j.cor.2025.107207","DOIUrl":"10.1016/j.cor.2025.107207","url":null,"abstract":"<div><div>We study a doctor-patient matching and scheduling problem, incorporating chronic patients’ preferences for online consultation time. We establish a multi-objective optimization model of 0–1 integer programming to solve the issue of doctor-patient matching and scheduling simultaneously. The objective is to maximize the satisfaction of doctors and patients of chronic diseases and the number of matches on the platform. To address this model, it is reconstructed into a single-objective optimization model based on the <span><math><mi>ε</mi></math></span>-constraint method. On this basis, we propose a logic-based Benders decomposition with a logic-based cutting inequality. Furthermore, the effectiveness of the proposed algorithm is verified via numerical experiments. The results show that the proposed logic-based Benders decomposition has a significant advantage in computing time. Finally, management implications are provided based on sensitivity analysis.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107207"},"PeriodicalIF":4.1,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672271","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":"Ranking methods based on the dominance degree. An investigation of rank reversal","authors":"Roumeissa Kerboui ,&nbsp;Moncef Abbas ,&nbsp;Marc Pirlot","doi":"10.1016/j.cor.2025.107196","DOIUrl":"10.1016/j.cor.2025.107196","url":null,"abstract":"<div><div>Multi-criteria decision making methods have been used in many applications to derive a ranking of objects evaluated on several criteria. In case these evaluations are imprecise, integrating imprecision in the overall assessment is a further issue. In this paper, we deal with imprecise evaluations in the form of intervals. Therefore, the problem is to rank multi-dimensional interval data.</div><div>In recent years, a scoring method using the dominance degree has been proposed in order to rank interval data. This index is ordinal in the sense that it takes only into account the ordering of the endpoints of the evaluation intervals. It is computed by considering the evaluations of all the other objects to be ranked. This implies that the dominance degree, hence the ranking, may change when the set of objects to be ranked is altered. This phenomenon is known as <em>rank reversal</em> in the literature.</div><div>We analyze the occurrence of rank reversal when we remove an object from (or add one to) the set of objects to be ranked. We introduce variants of the dominance degree rule and analyze them similarly. This is done both analytically and by simulation. We then compare the dominance degree approach with an adaptation of the Borda rule. We also examine how the presence of a set of reference points can reduce the rank reversal phenomenon and enhance the discrimination power of the method.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107196"},"PeriodicalIF":4.1,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614225","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":"Robust schedule for the bi-objective discrete time/resource trade-off problem","authors":"Yan Zhao ,&nbsp;Yongchao Ding ,&nbsp;Wendi Tian","doi":"10.1016/j.cor.2025.107205","DOIUrl":"10.1016/j.cor.2025.107205","url":null,"abstract":"<div><div>The Discrete Time/Resource Trade-Off Problem (DTRTP), a subproblem of the multi-mode resource-constrained project scheduling problem, is prevalent in fields such as construction and software development, where project uncertainties often impact schedule stability. This paper proposes a bi-objective DTRTP model designed both to minimize project duration and to enhance robustness against disruptions. To solve this model, we develop several optimization algorithms, including the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Variable Neighborhood Search (VNS) and three hybrid algorithms that combine NSGA-II with VNS to improve robustness and solution quality. The performance of these algorithms is evaluated through computational experiments, which involve algorithm performance analysis, Pareto optimality analysis and uncertainty analysis. The results show that both NSGA-II and the hybrid algorithms generate robust schedules that effectively minimize project duration and maximize robustness, providing a promising approach for managing uncertainties in complex project scheduling.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107205"},"PeriodicalIF":4.1,"publicationDate":"2025-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614224","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":"Variants of Harsanyi’s tracing procedures for selecting a perfect stationary equilibrium in stochastic games","authors":"Yiyin Cao ,&nbsp;Peixuan Li ,&nbsp;Chuangyin Dang","doi":"10.1016/j.cor.2025.107161","DOIUrl":"10.1016/j.cor.2025.107161","url":null,"abstract":"<div><div>The concept of perfect stationary equilibrium (PSE) is defined to eliminate some counterintuitive subgame perfect equilibria in stationary strategies (SSPEs) for stochastic games. While computational tools are vital to the practical applications of stochastic games, there are limited methods available for computing PSEs in the existing literature. A stochastic version of Harsanyi’s linear tracing procedure (SLTP) was developed by Herings and Peeters for selecting an SSPE. Nonetheless, their method fails to find a PSE directly. In this paper, we develop a variant of the SLTP by formulating a perturbed stochastic game in which each player maximizes her payoff in a state against a convex linear combination of a prior-belief profile and a mixed strategy profile of other players. Furthermore, by integrating logarithmic-barrier terms into the payoff functions of the perturbed game, we formulate a stochastic version of Harsanyi’s logarithmic tracing procedure (SLogTP) and then develop a variant of the SLogTP. We prove the variants of the SLTP and SLogTP globally converge to a PSE for any stochastic game. Extensive numerical experiments are carried out, and the numerical results illustrate the effectiveness and efficiency of the proposed methods.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107161"},"PeriodicalIF":4.1,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144569867","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":"Job shop scheduling by Deep Dual-Q Network with Prioritized Experience Replay for resilient production control in flexible manufacturing system","authors":"Chao Liu ,&nbsp;Kai Chen ,&nbsp;Hao Wang ,&nbsp;Baojun Yang ,&nbsp;Jiewu Leng","doi":"10.1016/j.cor.2025.107190","DOIUrl":"10.1016/j.cor.2025.107190","url":null,"abstract":"<div><div>The increasing demand for mass customization and intensifying market competition have made the production cycles shorter and the product iterations faster. As a result, most products are in small and medium batches, introducing both opportunities and challenges to conventional job scheduling. The resilient production control in flexible manufacturing system focuses on creating adaptive and sustainable systems that present the characteristics of multi-product-type variant-volume discrete-flow mixed-flow production, which is still challenging to balance flexibility and efficiency in production. In this paper, a Deep Dual-Q Network with Prioritized Experience Replay (DDQN-PER) approach is proposed to solve the job shop scheduling problem (JSSP). It combines the advantages of the Dueling and Double DQN architecture, utilizing prioritized replay and neural networks to approximate state–action (Q). To extract and store experience data from the experience memory more efficiently, the states of shop environment are represented as information matrices. The two-phase algorithm, comprising iterative offline training and online application (OTOA), trains scheduling policies, forming a dynamic closed loop between offline scheduling results and online real-time production control. Case study and downtime experiments conducted on key machines validate the superiority of the proposed approach. Experimental results demonstrate that using DDQN-PER with optimized hyper-parameters effectively solves the JSSP.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107190"},"PeriodicalIF":4.1,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655405","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":"Job scheduling integrated with material ordering: decision-dependent stochastic programming and information relaxation dual bounds","authors":"Yue Sha ,&nbsp;Weimiao Liu ,&nbsp;Junlong Zhang","doi":"10.1016/j.cor.2025.107194","DOIUrl":"10.1016/j.cor.2025.107194","url":null,"abstract":"<div><div>We investigate an integrated job scheduling and material ordering problem arising from one-of-a-kind production, accounting for endogenous uncertainties in material consumption. The integrated problem is formulated as a multistage stochastic program incorporating a set of linear non-anticipativity constraints, while model reduction properties are also carefully identified. To address the computational complexity, we introduce a rolling horizon procedure to generate quality feasible policies in a sequential and dynamic manner. Our primary contribution lies in the development of a penalized information relaxation duality approach, which constructs a dual bound for the proposed multistage stochastic program. This innovative method is convenient for Monte Carlo simulation and parallel resolution, offering promising potential for future research. Computational results validate the efficiency and effectiveness of our approaches in minimizing total costs compared with existing methods. Additionally, sensitivity analyses are conducted to identify factors influencing the computational performance of our algorithms, including the planning horizon, uncertainty variance, sample size, and network structure.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107194"},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588645","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":"Stochastic casualty response planning with multiple classes of patients","authors":"Pedram Farghadani-Chaharsooghi ,&nbsp;Hossein Hashemi Doulabi ,&nbsp;Walter Rei ,&nbsp;Michel Gendreau","doi":"10.1016/j.cor.2025.107165","DOIUrl":"10.1016/j.cor.2025.107165","url":null,"abstract":"<div><div>In this paper, we study the stochastic casualty response planning problem (CRP) in the context of providing treatments to multiple classes of patients with different types of injuries. In this general setting, both patients’ demands and hospitals’ treatment capacity are considered uncertain. To the best of our knowledge, this is the first time that this problem is solved. We propose a novel two-stage stochastic mixed-integer programming model which, in the first stage, determines the location of the Alternative Care Facilities (ACFs) and allocates different resources, such as rescue vehicles, medical equipment, and physicians, to them. In the second stage, this model helps decide how to allocate patients with multiple injuries to either ACFs or hospitals, considering their care itineraries and available resources. Moreover, it recommends potential patient transfers between ACFs and hospitals when required. Furthermore, we introduce an alternative two-stage stochastic model that is more compact than the first. This formulation significantly reduces solution times. We also provide an equivalency proof between the two formulations. As the solution method, we develop both the L-shaped algorithm, a pure cutting-plane method tailored to our stochastic mathematical model, and the branch-and-Benders-cut (B&amp;BC) algorithm. To further enhance the efficiency of these algorithms, we develop a wide range of acceleration techniques, including Benders dual decomposition, Lagrangian dual decomposition, a multi-cut reformulation, Pareto-optimal cuts, and the inclusion of lower bounding functional valid inequalities. We carry out extensive computational experiments demonstrating that these algorithmic enhancements dramatically improve the performance of the B&amp;BC algorithm, reducing the average optimality gap from 7898% in the standard B&amp;BC algorithm to just 0.92% in the enhanced version. Additionally, we benchmark our approach against the progressive hedging algorithm (PHA), a widely used decomposition method in disaster response operations, to further assess its effectiveness. Finally, we present a case study from the 2011 Van earthquake in Turkey, demonstrating the applicability and efficiency of our optimization methods.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107165"},"PeriodicalIF":4.1,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524296","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}