Computers & Operations Research最新文献

{"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}

{"title":"A supervised learning approach to rankability","authors":"Nathan McJames ,&nbsp;David Malone ,&nbsp;Oliver Mason","doi":"10.1016/j.cor.2025.107049","DOIUrl":"10.1016/j.cor.2025.107049","url":null,"abstract":"<div><div>The rankability of data is a novel problem that considers the ability of a dataset, represented as a graph, to produce a <em>meaningful</em> ranking of the items it contains. To study this concept, a number of rankability measures have been proposed, based on comparisons to a complete dominance graph via combinatorial and linear algebraic methods. Interest in this field has been steadily expanding, with a growing appreciation for the significance of evaluating rankability across diverse applications. Consequently, the validation of these rankability methodologies in different scenarios holds paramount importance. In this paper, we review existing measures of rankability and highlight some questions to which they give rise. We go on to introduce a new framework designed to evaluate rankability with a tailored approach, one that allows for efficient estimation in specific problem domains. Finally, we present a comparative analysis of these metrics by applying them to both synthetic and real-life sports data.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107049"},"PeriodicalIF":4.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637573","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":"Ship emission monitoring with a joint mode of motherships and unmanned aerial vehicles","authors":"Dan Zhuge ,&nbsp;Jianhui Du ,&nbsp;Lu Zhen ,&nbsp;Shuaian Wang ,&nbsp;Peng Wu","doi":"10.1016/j.cor.2025.107012","DOIUrl":"10.1016/j.cor.2025.107012","url":null,"abstract":"<div><div>Ship emission monitoring is crucial for improving compliance with emission control area (ECA) policies. To address the limitations of traditional base station-based monitoring methods, we propose a highly maneuverable mothership-based unmanned aerial vehicle (UAV) monitoring mode. We develop a mixed integer non-linear programming model to maximize the total profit (i.e., the revenues of ship emission monitoring minus the fixed costs of motherships and UAVs, the fuel cost of motherships, and the electricity cost of UAVs). Three types of integer variables are relaxed to continuous variables based on the model properties. We then design a tailored Benders decomposition algorithm to solve the model. Moreover, to improve the performance of the algorithm, we also present a variety of acceleration strategies, including lower bound limit inequalities and knapsack inequalities. Finally, we verify the effectiveness of the proposed algorithm using experimental instances based on the North American ECA. We also find a relationship between the width of emission inspection area and the total monitoring cost.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"179 ","pages":"Article 107012"},"PeriodicalIF":4.1,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610810","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 local search enhanced logic-based Benders decomposition approach for order acceptance and scheduling problem with preemption","authors":"Lin Wang ,&nbsp;Ziqing Zhang ,&nbsp;Sirui Wang","doi":"10.1016/j.cor.2025.107047","DOIUrl":"10.1016/j.cor.2025.107047","url":null,"abstract":"<div><div>This paper addresses an order acceptance and scheduling problem (OAS) that incorporates the allowance for preemption. We introduce a novel continuous-time mixed-integer linear programming (MILP) formulation for the problem. Allowing preemption greatly increases the complexity of the MILP model by requiring a larger number of variables and constraints to sequence order parts, rather than merely orders. Consequently, the performance of the MILP formulation rapidly deteriorates as the problem size grows. To efficiently solve the problem, we propose an approach based on the logic-based Benders decomposition (LBBD). The preemptive Earliest Due Date (EDD) rule is utilized to efficiently solve the subproblem in LBBD. Additionally, a local search heuristic is developed to construct high-quality solutions based on the LBBD master problem solutions. This local search-enhanced LBBD approach (LS-LBBD) is capable of solving instances with up to 200 orders to optimality within 3600 s, achieving an average optimality gap of only 3.02% across 200-order instances with various parameters. The effectiveness of the local search heuristic has been validated by comparative experiments. For instances where the optimal solution was not obtained, the solutions from LS-LBBD were on average 6.57% better than those from the original LBBD</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107047"},"PeriodicalIF":4.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767726","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 methods for the distributed permutation flow shop scheduling problem with production and transportation cost","authors":"Fuli Xiong,&nbsp;Jiangbo Shi,&nbsp;Lin Jing,&nbsp;An Ping","doi":"10.1016/j.cor.2025.107044","DOIUrl":"10.1016/j.cor.2025.107044","url":null,"abstract":"<div><div>Distributed manufacturing mode can significantly enhance production flexibility and efficiency. Considering that factories and customers in distributed manufacturing environments may be geographically dispersed, we address a distributed permutation flow shop scheduling problem (DPFSP) with direct transportation under different cost of production and transportation while the goal is to minimize of weighted sum cost and makespan (DPFSP-PTM). First, we formulate two mixed-integer linear programming (MILP) models and one constraint programming (CP) model to optimize the objective simultaneously. Then, by decomposing DPFSP-PTM into an order assignment master problem (AMP) and a series of scheduling subproblems (SSPs), we develop two exact methods based on logic-based Benders decomposition (LBBD) and Branch-and-Check (BCH). To accelerate convergence, we propose three strong SSP relaxations based on the single-machine bottleneck to enhance the MILP models and AMP. Additionally, we introduce an initial solution generated by the iterated greedy (IG) algorithm to warm-start the LBBD. Finally, we demonstrate the effectiveness of the proposed methods in achieving competitive average optimality gaps and lower bounds across both small-scale and large-scale instances.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"179 ","pages":"Article 107044"},"PeriodicalIF":4.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593075","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":"Scheduling moldable tasks on homogeneous multi-cluster platforms with GPUs","authors":"Fangfang Wu ,&nbsp;Run Zhang ,&nbsp;Xiandong Zhang","doi":"10.1016/j.cor.2025.107041","DOIUrl":"10.1016/j.cor.2025.107041","url":null,"abstract":"<div><div>This paper examines task scheduling in homogeneous multi-cluster platforms, equipped with Graphics Processing Units (GPUs), with the aim of minimizing the makespan. We assume that tasks can be parallelized across these platforms under the moldable model. Recognizing the NP-hard nature of the problem, our goal is to develop algorithms that provide approximation ratios. While existing research has established algorithms for single-cluster GPU environments, scaling these to multi-cluster platforms introduces new challenges, especially due to the restriction that tasks cannot use processors from different clusters. We propose an integer programming-based algorithm that achieves an approximation ratio of <span><math><mrow><mfrac><mrow><mn>3</mn></mrow><mrow><mn>2</mn></mrow></mfrac><mo>+</mo><mi>ϵ</mi></mrow></math></span>, trading off runtime for an improved approximation ratio. Additionally, leveraging recent theoretical advancements, we have created a polynomial-time algorithm with an approximation ratio of <span><math><mrow><mn>2</mn><mo>+</mo><mi>ϵ</mi></mrow></math></span>. Empirical computational experiments show that our algorithms surpass their counterparts in empirical approximation ratios.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"179 ","pages":"Article 107041"},"PeriodicalIF":4.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601282","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":"Online order acceptance and scheduling in a single machine environment","authors":"Chunyan Zheng,&nbsp;Jin Yu,&nbsp;Guohua Wan","doi":"10.1016/j.cor.2025.107028","DOIUrl":"10.1016/j.cor.2025.107028","url":null,"abstract":"<div><div>We consider the online order acceptance and scheduling (OAS) problem, a widely studied problem in its offline counterpart, where orders arrive online sequentially with associated rewards, arrival times, and due dates in a finite planning horizon. The objective is to make real-time order acceptance and scheduling decisions so as to maximize the total profit. To tackle this problem, we derive an upper bound on the competitive ratio of any online algorithm for the online OAS problem and introduce three algorithms (online greedy, online learning, and delay). For the online greedy algorithm, we provide a performance guarantee under the mild conditions via theoretical analysis. Furthermore, through computational studies we highlight that both the urgency of due dates of the orders and the workload level of the system can significantly influence the performance of the online algorithms. Since each proposed algorithm has its advantages and disadvantages, we categorize different scenarios for using the suitable algorithm, aiming at offering managerial insights for firms to make informed decisions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"179 ","pages":"Article 107028"},"PeriodicalIF":4.1,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601350","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":"Multi-armed bandit for the cyclic minimum sitting arrangement problem","authors":"Marcos Robles ,&nbsp;Sergio Cavero ,&nbsp;Eduardo G. Pardo ,&nbsp;Oscar Cordón","doi":"10.1016/j.cor.2025.107034","DOIUrl":"10.1016/j.cor.2025.107034","url":null,"abstract":"<div><div>Graphs are commonly used to represent related elements and relationships among them. Signed graphs are a special type of graphs that can represent more complex structures, such as positive or negative connections in a social network. In this work, we address a combinatorial optimization problem, known as the Cyclic Minimum Sitting Arrangement, that consists of embedding a signed input graph into a cycle host graph, trying to locate in the embedding positive connected vertices closer than negative ones. This problem is a variant of the well-known Minimum Sitting Arrangement where the host graph has the structure of a path graph. To tackle the problem, we propose an algorithm based on the Multi-Armed Bandit method that combines three greedy-randomized constructive procedures with a Variable Neighborhood Descent local search algorithm. To assess the merit of our proposal, we compare it with the state-of-the-art method. Our experiments show that our algorithm outperforms the best-known method in the literature to date, and the results are statistically significant, establishing itself as the new state of the art for the problem.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"179 ","pages":"Article 107034"},"PeriodicalIF":4.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548515","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}