Computers & Operations Research最新文献

{"title":"Minimizing the expected cybersecurity loss in a software supply chain through scheduling scanning jobs","authors":"Jen-Ya Wang","doi":"10.1016/j.cor.2025.107064","DOIUrl":"10.1016/j.cor.2025.107064","url":null,"abstract":"<div><div>Third-party cybersecurity providers in a software supply chain execute scanning jobs according to business policies and government regulations, tailoring responses to each node’s unique attributes and risks. Traditionally, providers might use various tools at different times without coordination, leading to resource bottlenecks. This study introduces a novel approach to scanning job scheduling, addressing the unique challenge where the marginal benefit of scanning time varies non-linearly, unlike traditional job scheduling problems. The findings reveal that upgrading a scanning strategy by one level can quantify the reduced loss, providing a foundation for efficient resource allocation in large-scale supply chains. A branch-and-bound algorithm is developed to generate the optimal schedules, serving as a benchmark for evaluating other metaheuristic algorithms. Furthermore, this study proposes an innovative genetic algorithm incorporating dynamic crossover or mutation rates, as well as mechanisms to prevent premature convergence and improve performance. This approach demonstrates practical scalability and efficiency in scheduling scanning jobs across 300 nodes, ensuring adaptability to real-world supply chains.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107064"},"PeriodicalIF":4.1,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725702","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":"Optimizing strategic and operational decisions of car sharing systems under demand uncertainty and substitution","authors":"Beste Basciftci ,&nbsp;Esra Koca ,&nbsp;Sinan Emre Kosunda","doi":"10.1016/j.cor.2025.107052","DOIUrl":"10.1016/j.cor.2025.107052","url":null,"abstract":"<div><div>Car sharing is an efficient way to improve mobility, reduce the use of personal vehicles, and lessen the associated carbon emissions. Due to increasing environmental awareness of customers and government regulations, car sharing providers must be careful about the composition of their vehicle fleet to meet diverse customer demand through vehicle types with different carbon emission levels. In this study, for a car sharing company, we consider the problems of determining service regions and purchasing decisions with a mixed fleet of vehicles under budget and carbon emission constraints, and the deployment of these vehicles to service regions under uncertain one-way and round-trip rental requests over a multi-period planning horizon. We further introduce the concept of “substitution” to the car sharing operations that provides customers with alternative vehicle options when their preferred type is unavailable. To address this complex problem, we propose a novel two-stage stochastic mixed-integer program leveraging spatial–temporal networks and multicommodity flows to capture these strategic and operational decisions of this system over the planning horizon while allowing substitution in operations. We further prove that the corresponding second-stage problem of the proposed program has a totally unimodular constraint matrix. Taking advantage of this result, we develop a branch-and-cut-based decomposition algorithm with various computational enhancements. We present an extensive computational study that highlights the value of the proposed models from different perspectives and demonstrates the performance of the proposed solution algorithm with significant speedups. Our case study provides insights for region opening and fleet allocation plans under demand uncertainty and demonstrates the value of introducing substitution to car sharing operations and the importance of integrating strategic and operational decisions and obtaining stochastic solutions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107052"},"PeriodicalIF":4.1,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725701","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":"Optimizing blocking and starving delays in sequential zone order picking systems through time-decomposed workload balancing","authors":"Jeongwon Park ,&nbsp;Soondo Hong","doi":"10.1016/j.cor.2025.107060","DOIUrl":"10.1016/j.cor.2025.107060","url":null,"abstract":"<div><div>Sequential zone order picking systems frequently encounter blocking delays when a tote cannot proceed to the next zone because it is occupied, and starving delays when a tote remains unassigned to a zone. General approaches to minimize delays include balancing the total workload across zones, grouping the orders into batches, or optimizing the order release sequences. However, the issue of temporal workload imbalances caused by instantaneous differences in processing time between zones has not been addressed. Since temporal workload imbalances result in delays, this study proposes the decomposition of workloads into time slots and develops a temporal workload balancing model (TBM) that incorporates batching and sequencing based on time slot decomposition. We also develop an adaptive large neighborhood search (ALNS) heuristic model to tackle large-scale practical problems of temporal workload imbalance. In simulation experiments, we compare the TBM model to alternative batching strategies in an order picking environment featuring consecutive batch windows. Our findings reveal that the TBM model yields an average reduction in makespan of 27.65% and 15.99% compared to random strategy and baseline method. We conclude that temporal workload balancing can minimize blocking and starving delays and maximize order picking productivity.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107060"},"PeriodicalIF":4.1,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697805","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":"A distributionally robust optimisation with joint chance constraints approach for location-routing problem in urban search and rescue operations","authors":"Kamran Sarmadi ,&nbsp;Mehdi Amiri-Aref","doi":"10.1016/j.cor.2025.107051","DOIUrl":"10.1016/j.cor.2025.107051","url":null,"abstract":"<div><div>This paper examines a multi-period location-routing problem with uncertain demand and travel times in the context of disaster management. We propose an optimisation model that integrates strategic location decisions with multi-period routing decisions to navigate search-and-rescue teams in the aftermath of a disaster within an uncertain environment. To model this problem, we apply a distributionally robust optimisation approach with joint chance constraints. We enhance computational tractability by reformulating the problem using Bonferroni’s inequality and approximating the chance constraints. The proposed methodology is evaluated in a hypothetical case study of Santa Cruz County, California, USA, a region highly susceptible to earthquakes. We tested multiple instances of this case study to demonstrate the effectiveness of the proposed method compared to the sample average approximation approach. Numerical experiments reveal that the methodology developed in this paper aids decision-makers in strategically locating facilities to deploy search-and-rescue teams and efficiently directing them towards affected sites, achieving a maximal rescue rate.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107051"},"PeriodicalIF":4.1,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Periodic and aperiodic train timetabling and rolling stock circulation planning using an efficient Lagrangian relaxation decomposition","authors":"Naijie Chai ,&nbsp;Ziyu Chen ,&nbsp;Wenliang Zhou","doi":"10.1016/j.cor.2025.107062","DOIUrl":"10.1016/j.cor.2025.107062","url":null,"abstract":"<div><div>Train timetabling and rolling stock circulation planning are problems of crucial importance for integrated planning. Often, these problems are separately solved in a sequential way without consideration of periodic train schedule. However, a notable drawback of this layered planning process is poor coordination and efficiency between train and rolling stock timetables, as well as lack of regularity. To this end, we explore the joint optimization problem of periodic and aperiodic train timetabling and rolling stock circulation planning in this paper. To address this comprehensive problem, an integer programming model is initially established by incorporating rolling stock circulation into optimizing periodic and aperiodic train timetabling. Due to the model-solving complexity, a three-dimensional space–time-state network is constructed to reformulate this model. Within this three-dimensional network, states are used to represent trains served by rolling stocks. Subsequently, the problem is transformed into a minimum-cost multi-commodity network flow problem with incompatible arcs based on the space–time-state network. And an efficient Lagrangian relaxation decomposition algorithm is proposed to solve this network flow problem. The effectiveness of the algorithm is verified through a series of case studies.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107062"},"PeriodicalIF":4.1,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683216","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":"A note on “Self-adaptive General Variable Neighborhood Search algorithm for parallel machine scheduling with unrelated servers”","authors":"Andrea Grosso ,&nbsp;Fabio Salassa","doi":"10.1016/j.cor.2025.107055","DOIUrl":"10.1016/j.cor.2025.107055","url":null,"abstract":"<div><div>In a recent paper a two-machines two-servers scheduling problem with identical machines but unrelated servers and makespan objective is studied and solved via sophisticated Variable-Neighbourhood Search procedures, for instances up to 120 jobs in size. We show that the same problem can be transformed to a pretty standard problem with unrelated machines that can be efficiently solved to optimality, up to much larger instances.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107055"},"PeriodicalIF":4.1,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683214","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 interval two-stage robust stochastic programming under a bi-level multi-objective framework toward river basin water resources allocation","authors":"Yan Tu ,&nbsp;Yongzheng Lu ,&nbsp;Benjamin Lev","doi":"10.1016/j.cor.2025.107045","DOIUrl":"10.1016/j.cor.2025.107045","url":null,"abstract":"<div><div>The uncertainty stemming from hydrological variables and socio-economic parameters poses new challenges to river basin water resources allocation (RBWRA). Given the pressing need for efficient, environmentally friendly, and equitable solutions in RBWRA, a bi-level multi-objective interval two-stage robust stochastic programming (BLMOITRSP) model is proposed. This model aims to achieve the optimal balance among efficiency, eco-friendliness, and equity, collectively called the “3E”. A novel hierarchical mixed water allocation mechanism is introduced within this model. The basin authority pursues the “3E” objectives at the macro-control level through administrative water allocation. Conversely, sub-areas as followers prioritize economic interests, striving for economic benefit maximization through water market allocation. Furthermore, uncertain parameters (e.g., water demand) are treated as interval parameters, employing interval two-stage robust stochastic programming (ITRSP) to address uncertainty issues and control systemic risks in the model. To solve the BLMOITRSP model, we present a bi-level interactive global equilibrium optimization algorithm, fusing with the modified particle swarm optimization (PSO) algorithm. The bi-level algorithm provides solutions tailored to the preferences of different decision-makers. The proposed model and method are also applied to the Hanjing River Basin in China to demonstrate its feasibility and effectiveness. The results indicate that the proposed model effectively ensures the “3E” balance. The introduction of the hierarchical mixed water allocation mechanism proves conducive to promoting water distribution and enhancing economic benefits. ITRSP effectively controls the systemic risks of the model’s impact on the basin’s total economic benefit. The economic performance of each sub-area varies in response to different decision preferences under RBWRA schemes. Finally, the conclusions and future research directions are provided.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107045"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629091","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":"A heuristic approach for the critical chain project scheduling problem based on resource flows","authors":"Wuliang Peng ,&nbsp;Ziyan Wang ,&nbsp;Fang Xie ,&nbsp;Haitao Li","doi":"10.1016/j.cor.2025.107054","DOIUrl":"10.1016/j.cor.2025.107054","url":null,"abstract":"<div><div>The Critical Chain Project Scheduling Problem (CCPSP) aims to obtain robust baseline schedules by optimizing the size and insertion of buffers for projects with uncertain activity durations. To overcome the challenge of handling new resource conflicts due to insertion of buffers, we develop a novel approach based on resource flow to add additional precedence relationships that resolve resource conflicts. Our priority-rule based heuristic is easy to implement, fast, and effective. A comprehensive computational experiment is conducted to examine the performance of a large set of priority rules and their combinations, which is then estimated using regression analysis with the problem characteristics as independent variables. Our algorithm outperforms the existing benchmark method for the addressed problem in both solution quality and efficiency, and provides project managers an efficient and effective tool to handle large-scale projects under uncertainty.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107054"},"PeriodicalIF":4.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637574","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":"A novel mathematical modeling approach for integrating a periodic vehicle routing problem and cross-docking system","authors":"Mostafa Asgharyar ,&nbsp;Nima Farmand ,&nbsp;Seyyed Nader Shetab-Boushehri","doi":"10.1016/j.cor.2025.107048","DOIUrl":"10.1016/j.cor.2025.107048","url":null,"abstract":"<div><div>To remain competitive in a globalized market, manufacturers must effectively respond to customer demands in various situations. In parallel, logistics companies have adopted cross-docking systems as a key component of lean supply chain management to handle high transportation volumes. By integrating this pivotal component in the supply chain, goods are efficiently distributed to retailers via cross-dock facilities. This article introduces, for the first time, an integrated framework for the periodic vehicle routing problem with cross-docking (PVRPCD) system between supplier and retailer locations. The goal is to optimize three key decisions: 1. Vehicle scheduling and routing for each period, 2. The loading and unloading quantities of goods at the cross-dock, and 3. The selection of a daily combination from periodic retailer demands to minimize the costs incurred by transportation and cross-docking operations. To formulate the PVRPCD, a novel mixed-integer linear programming (MILP) model is designed. Given the computational complexity of large-scale instances, a heuristic algorithm is designed to produce near-optimal initial solutions, which are then embedded into two metaheuristic algorithms: variable neighborhood search (VNS) and population-based variable neighborhood search (PBVNS). These algorithms incorporate four shaking and four local search operators to enhance solution quality and scalability. To validate the effectiveness of the metaheuristic algorithms, computational experiments are conducted using benchmark instances. The optimal solutions obtained via the CPLEX solver for small-scale instances serve as a baseline for comparison. The computational results illustrate that both algorithms effectively solve small-scale problems. Nevertheless, PBVNS consistently outperforms VNS in terms of solution quality, though it requires more computation time. Despite the increased solution time, the improvement in solution quality justifies the additional computational effort. Finally, sensitivity analyses on key PVRPCD parameters provide managerial insights for decision-makers, offering a profound understanding into the influence of model parameters on solution performance.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107048"},"PeriodicalIF":4.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759495","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":"A causal framework for stochastic local search optimization algorithms","authors":"Alberto Franzin,&nbsp;Thomas Stützle","doi":"10.1016/j.cor.2025.107050","DOIUrl":"10.1016/j.cor.2025.107050","url":null,"abstract":"<div><div>Despite the multitude of optimization algorithms available in the literature and the various approaches that study them, understanding the behaviour of an optimization algorithm and explaining its results are fundamental open questions in artificial intelligence and operations research. We argue that the body of available literature is already very rich, and the main obstacle to advancements towards answering those questions is its fragmentation.</div><div>In this work, we focus on stochastic local search algorithms, a broad class of methods to compute good quality suboptimal solutions in a short time. We propose a causal framework that relates the entities involved in the solution of an optimization problem. We demonstrate how this conceptual framework can be used to relate many approaches aimed at understanding how stochastic local search algorithms work, and how it can be utilized to address open problems, both theoretical and practical.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107050"},"PeriodicalIF":4.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637572","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}