Computers & Operations Research最新文献_第4页

A capacitated collection-and-delivery-point location problem with random utility maximizing customers 随机效用最大化下的有容量取货点选址问题

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-05 DOI: 10.1016/j.cor.2025.107349

David Pinzon Ulloa , Ammar Metnani , Emma Frejinger

{"title":"A capacitated collection-and-delivery-point location problem with random utility maximizing customers","authors":"David Pinzon Ulloa , Ammar Metnani , Emma Frejinger","doi":"10.1016/j.cor.2025.107349","DOIUrl":"10.1016/j.cor.2025.107349","url":null,"abstract":"<div><div>We consider a strategic decision-making problem where a logistics provider (LP) seeks to locate collection and delivery points (CDPs) with the objective of reducing total logistics costs. The customers maximize utility based on their perception of home delivery service as well as the characteristics of the CDPs, including their location. At the strategic planning level, the LP does not have complete information about customers’ preferences and their exact location. We introduce a mixed integer non-linear formulation of the problem and propose two linear reformulations. The latter involve sample average approximations and closest assignment constraints, and in one of the formulations we use scenario aggregation to reduce its size. We solve the formulations with a general-purpose solver using a standard Benders decomposition method. Based on extensive computational results and a realistic case study, we find that the problem can be solved efficiently. However, the level of uncertainty in the instances determines which approach is the most efficient. We use an entropy measure to capture the level of uncertainty, which can be computed prior to solving. Furthermore, the results highlight the value of accurate demand modeling, as customer preferences have an important impact on the solutions and associated costs.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107349"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734830","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}

引用次数: 0

A near-real-time reduction-based algorithm for coloring massive graphs 一种近实时的基于约简的海量图着色算法

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-26 DOI: 10.1016/j.cor.2025.107378

Chenghao Zhu, Yi Zhou

{"title":"A near-real-time reduction-based algorithm for coloring massive graphs","authors":"Chenghao Zhu, Yi Zhou","doi":"10.1016/j.cor.2025.107378","DOIUrl":"10.1016/j.cor.2025.107378","url":null,"abstract":"<div><div>The graph coloring problem is a classical combinatorial optimization problem with important applications such as register allocation and task scheduling, and it has been extensively studied for decades. However, near-real-time algorithms that can deliver high-quality solutions for very large real-world graphs within a strict time frame remain relatively underexplored. In this paper, we address this gap by developing an practical framework that integrates reduction rules, including degree, domination, complement crown, and independent set reductions. Building on this framework, we propose RECOL, a reduction-based algorithm that alternates between fast estimation of lower and upper bounds, graph reductions, and heuristic coloring. We evaluate RECOL on a wide range of benchmark datasets, including SNAP, the Network Repository, DIMACS10, and DIMACS2. Experimental results demonstrate that RECOL consistently outperforms state-of-the-art algorithms on three major benchmark sets of very large, sparse graphs (SNAP, the Network Repository, and DIMACS10) within one-minute time limit. Additional experiments further highlight the pivotal role of reduction techniques in achieving this performance.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107378"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880780","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}

引用次数: 0

A branch-price-and-cut algorithm for sustainable milk-run vehicle scheduling problem with cross-dimensional integration 跨维整合可持续牛奶车调度问题的分支价格削减算法

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-11 DOI: 10.1016/j.cor.2025.107361

Kaiyuan Zhang , Shijin Wang , Binghai Zhou

{"title":"A branch-price-and-cut algorithm for sustainable milk-run vehicle scheduling problem with cross-dimensional integration","authors":"Kaiyuan Zhang , Shijin Wang , Binghai Zhou","doi":"10.1016/j.cor.2025.107361","DOIUrl":"10.1016/j.cor.2025.107361","url":null,"abstract":"<div><div>In response to environmental deterioration and increasingly stringent regulations, this paper investigates a sustainable milk-run vehicle scheduling problem with cross-dimensional integration (SMVSPCI). The problem extends traditional milk-run models by integrating transportation tasks across bidirectional, temporal, and horizontal dimensions, while jointly considering returnable transport item (RTI) management and quantity decisions over multiple periods. To account for demand uncertainty, a scenario-based stochastic framework is adopted, allowing the model to capture multiple possible demand realizations and their associated probabilities. To effectively solve this complex problem, a tailored branch-price-and-cut (BPC) algorithm is proposed, incorporating innovative strategies such as pseudo-dominance, column combination, and column refinement to enhance computational efficiency. Extensive computational experiments on 270 instances demonstrate that the proposed algorithm efficiently handles medium-scale instances while achieving competitive results for larger cases. Comparative analyses further validate the effectiveness of the proposed strategies in improving solution quality and reducing computational time, providing valuable insights for sustainable logistics planning.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107361"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787980","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}

引用次数: 0

Seru order acceptance and scheduling in the distributed production network considering preventive maintenance 考虑预防性维护的分布式生产网络中批量订单的接收与调度

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-11-19 DOI: 10.1016/j.cor.2025.107329

P. Hajipour, J. Behnamian

{"title":"Seru order acceptance and scheduling in the distributed production network considering preventive maintenance","authors":"P. Hajipour, J. Behnamian","doi":"10.1016/j.cor.2025.107329","DOIUrl":"10.1016/j.cor.2025.107329","url":null,"abstract":"<div><div>In today’s globalized manufacturing environment, producers encounter unprecedented challenges stemming from intense competition, volatile customer demands, and the imperative to deliver high-quality, customized products. Collaborative production within multi-factory networks has emerged as a vital strategy for optimizing workflows and increasing flexibility. Complementing this approach, seru systems—which segment production lines into smaller, autonomous units—enhance responsiveness to fluctuating demand patterns. However, coordinating and scheduling operations across such networks introduces significant complexity, posing a substantial challenge for production-optimization research. Moreover, preventive maintenance is essential for sustaining system productivity by minimizing unplanned downtime and extending equipment lifespan. This study examines scheduling and order acceptance in a distributed production network that integrates seru systems, requiring customer orders to be allocated among factories—some of which operate under seru configurations. A mixed‑integer nonlinear programming (MINLP) model is proposed and implemented in GAMS. For larger-scale instances, the study introduces two memetic algorithms, each integrating a distinct local-search strategy: one utilizing simulated annealing and the other applying hill-climbing. Comparative analysis against a genetic algorithm demonstrates the superior efficiency of both memetic approaches in solving complex instances. The findings offer significant practical implications, such as reduced operational costs, increased production flexibility, and accelerated order fulfillment. Results further demonstrate that integrating seru systems with preventive maintenance strategies in multi-factory networks enhances system stability and efficiency, supports customized manufacturing, and mitigates downtime.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107329"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145683735","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}

引用次数: 0

Comparing approximations and heuristics over different time horizons for a production-inventory system under the base-stock policy and conditional value-at-risk objective 在基础库存政策和条件风险价值目标下，比较生产库存系统在不同时间范围内的近似和启发式

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-24 DOI: 10.1016/j.cor.2025.107369

Zhenyang Shi , Bo Li , Xue Zhang

{"title":"Comparing approximations and heuristics over different time horizons for a production-inventory system under the base-stock policy and conditional value-at-risk objective","authors":"Zhenyang Shi , Bo Li , Xue Zhang","doi":"10.1016/j.cor.2025.107369","DOIUrl":"10.1016/j.cor.2025.107369","url":null,"abstract":"<div><div>This paper addresses the challenge of determining the optimal base-stock level in an integrated production and inventory management setting. Demand follows a Poisson process, with one unit arriving at a time and unmet demand backlogged. Each demand triggers a new production order, and unit production times are exponentially distributed. The total cost over a given time horizon comprises inventory holding and backlogging costs. Instead of minimizing the expected total cost, we focus on minimizing the conditional value-at-risk (CVaR) of the total cost. We evaluate two existing approximation methods for identifying the optimal base-stock level through simulation experiments across various time horizons. Additionally, we propose and test four new heuristic methods. We discover several results regarding how the performance of these approximations and heuristics is influenced by both the individual and combined impacts of key system factors, such as time horizons, capacity utilization, and operational costs, thereby enabling a richer understanding of risk measures in production–inventory systems across different time horizons. Our findings provide tailored recommendations for choosing among approximation and heuristic methods under various scenarios.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107369"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837145","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}

引用次数: 0

Solving a large-scale 3D packing problem with robot constraints 求解具有机器人约束的大规模三维装箱问题

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-17 DOI: 10.1016/j.cor.2025.107373

Liang Chen, Sheng Zhang, Mengmeng Ding, Huimin Chen, Jiacheng Ren, Xiaoli Yue

引用次数: 0

Multi-project scheduling and material ordering with time varying supplier capacities 多项目调度和物料订购随时间变化的供应商能力

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-18 DOI: 10.1016/j.cor.2025.107362

Xuejun Hu , Shuyuan Liu , Erik Demeulemeester , Zhongbao Zhou

{"title":"Multi-project scheduling and material ordering with time varying supplier capacities","authors":"Xuejun Hu , Shuyuan Liu , Erik Demeulemeester , Zhongbao Zhou","doi":"10.1016/j.cor.2025.107362","DOIUrl":"10.1016/j.cor.2025.107362","url":null,"abstract":"<div><div>In project management practice, activity scheduling and material supply are interdependent and mutually restrictive. These two decision-making areas require coordinated management and planning, a challenge known in the literature as the project scheduling and material ordering problem (PSMOP). This research contributes to the field by formulating a comprehensive PSMOP model for multi-project, multi-supplier settings, incorporating real-world characteristics such as renewable resources, time-varying supplier capacities and supplier lead times. The proposed model adopts a period-based ordering strategy to optimize decisions related to activity sequencing, supplier selection, order timing and order quantities. To solve this complex model, an efficient population-based hybrid heuristic algorithm (PHHA) is designed, employing priority rules, a genetic algorithm combined with local search and simulated annealing to explore the solution space and to avoid local optima. Extensive numerical experiments validate the effectiveness of the proposed algorithm and model, demonstrating advantages over traditional methods and established algorithms in both small-scale and large-scale instances. This research provides valuable insights into the practical challenges of project management and contributes to the development of more efficient and effective project scheduling and material ordering strategies in multi-project, multi-supplier environments.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107362"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837148","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}

引用次数: 0

A hybrid primal heuristic for solving an integrated patient case-mix planning problem 求解综合病人病例混合计划问题的混合原始启发式算法

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-23 DOI: 10.1016/j.cor.2025.107377

Samuel Bakker , Babak Akbarzadeh , Broos Maenhout , Kristof Eeckloo

{"title":"A hybrid primal heuristic for solving an integrated patient case-mix planning problem","authors":"Samuel Bakker , Babak Akbarzadeh , Broos Maenhout , Kristof Eeckloo","doi":"10.1016/j.cor.2025.107377","DOIUrl":"10.1016/j.cor.2025.107377","url":null,"abstract":"<div><div>This study introduces a novel general-purpose mixed-integer programming heuristic designed for problems decomposable into a column-based formulation. The method encompasses a hybrid primal heuristic that alternates between two phases, i.e., column generation and the iterative solving of hybrid optimization models using mixed-integer programming. The hybrid models incorporate original (compact) and column variables, leveraging the advantages of both. The elements of the compact model ensure flexibility and the generation of new columns for one of the subproblems in search for improved integer feasible solutions. For the other subproblems, the solution space is constrained by only considering previously generated columns, uplifting tractability of the optimization search. To demonstrate the benefits of this approach, it is applied to a complex operating room planning problem that determines the case-mix and capacity planning, integrating the strategic decision-making with tactical admission planning of patients and relevant operational considerations related to the sequencing of surgical procedures. For solving the problem under study efficiently, the algorithm is accelerated using dedicated optimization mechanisms. The methodology is assessed using a dataset inspired by real-life settings. In the computational experiments, we validate the algorithm design choices and demonstrate that the proposed heuristic consistently outperforms alternative primal heuristics and mathematical programming.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107377"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837147","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}

引用次数: 0

Binary kernel logistic regression: A sparsity-inducing formulation and a convergent decomposition training algorithm 二核逻辑回归：稀疏性诱导公式和收敛分解训练算法

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2025-12-24 DOI: 10.1016/j.cor.2025.107363

Antonio Consolo , Andrea Manno , Edoardo Amaldi

{"title":"Binary kernel logistic regression: A sparsity-inducing formulation and a convergent decomposition training algorithm","authors":"Antonio Consolo , Andrea Manno , Edoardo Amaldi","doi":"10.1016/j.cor.2025.107363","DOIUrl":"10.1016/j.cor.2025.107363","url":null,"abstract":"<div><div>Kernel logistic regression (KLR) is a widely used supervised learning method for binary and multi-class classification, which provides estimates of the conditional probabilities of class membership for the data points. Unlike other kernel methods such as Support Vector Machines (SVMs), KLRs are generally not sparse. Previous attempts to deal with sparsity in KLR include a heuristic method referred to as the Import Vector Machine (IVM) and ad hoc regularizations such as the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>-based one. Achieving a good trade-off between prediction accuracy and sparsity is still a challenging issue with a potential significant impact from the application point of view. In this work, we revisit binary KLR and propose an extension of the training formulation proposed by Keerthi et al., which is able to induce sparsity in the trained model, while maintaining good testing accuracy. To efficiently solve the dual of this formulation, we devise a decomposition algorithm of Sequential Minimal Optimization type which exploits second-order information, and for which we establish global convergence. Numerical experiments conducted on 12 datasets from the literature show that the proposed binary KLR approach achieves a competitive trade-off between accuracy and sparsity with respect to IVM, <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>-based regularization for KLR, and SVM while retaining the advantages of providing informative estimates of the class membership probabilities.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107363"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921618","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}

引用次数: 0

A new job insertion hybrid algorithm for distributed flexible job shop scheduling problems 求解分布式柔性作业车间调度问题的一种新的作业插入混合算法

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2026-04-01 Epub Date: 2026-01-08 DOI: 10.1016/j.cor.2026.107386

Lin Huang , Changchun Liu , Dunbing Tang , Zequn Zhang , Haihua Zhu , Shikui Zhao

{"title":"A new job insertion hybrid algorithm for distributed flexible job shop scheduling problems","authors":"Lin Huang , Changchun Liu , Dunbing Tang , Zequn Zhang , Haihua Zhu , Shikui Zhao","doi":"10.1016/j.cor.2026.107386","DOIUrl":"10.1016/j.cor.2026.107386","url":null,"abstract":"<div><div>This study focuses on the distributed flexible job shop scheduling problem (DFJSP), which integrates factory assignment, machine selection, and operation sequencing, making it more complex than conventional scheduling. To minimize makespan, we propose a job insertion algorithm based on minimum delay (JIMD) that evaluates insertion positions using delay distance and insertion range for remaining. In the JIMD process, each operation of a job adaptively selects machines and insertion positions to minimize the increase in makespan, ensuring scheduling stability and flexibility. Building on JIMD, three job-level neighborhood structures are developed to optimize both inter- and intra-factory scheduling. For the local search phase, a factory tabu list is designed, and two neighborhood structures are used to achieve scientific search of critical factories. These components are integrated into a job insertion hybrid algorithm (JIHA), which unifies job allocation and operation sequencing to balance global exploration with local exploitation. Extensive experiments on 69 small-scale and 60 large-scale benchmark instances demonstrate that JIHA not only attains all known best solutions but also discovers new ones, confirming its effectiveness and robustness.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"188 ","pages":"Article 107386"},"PeriodicalIF":4.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145921621","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}

引用次数: 0