Computers & Operations Research最新文献_第10页

Q-learning-driven multi-population cooperative evolutionary algorithm with local search for scheduling of network-shared manufacturing resources 基于q学习驱动的多种群局部搜索协同进化算法的网络共享制造资源调度

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-29 DOI: 10.1016/j.cor.2025.107076

Liping Xu , Tao Zhou , Kai Li , Jianfu Chen , Han Zhang

{"title":"Q-learning-driven multi-population cooperative evolutionary algorithm with local search for scheduling of network-shared manufacturing resources","authors":"Liping Xu , Tao Zhou , Kai Li , Jianfu Chen , Han Zhang","doi":"10.1016/j.cor.2025.107076","DOIUrl":"10.1016/j.cor.2025.107076","url":null,"abstract":"<div><div>The variability in the availability of network-shared manufacturing resources and the release times of orders pose challenges to the operational decision-making of industrial internet platforms. This paper addresses these characteristics by studying the identical parallel machine scheduling problem, aiming to minimize total weighted tardiness under constraints of arbitrary release times and multiple machine unavailability periods. To address this research problem, a decoding mechanism based on machine idle periods is first proposed, effectively solving the impact of machine unavailability periods on the scheduling scheme. Secondly, a multi-population cooperative evolutionary algorithm is designed in which the mechanisms of selection, crossover, mutation, and information exchange between populations are improved. The optimal scheduling properties of two jobs on the same machine and different machines are analyzed, resulting in the design of two local search mechanisms. Additionally, Q-learning is introduced to enhance the adaptability of algorithm parameters by dynamically adjusting them within the multi-population cooperative evolutionary algorithm, resulting in a Q-learning-driven multi-population cooperative evolutionary algorithm with local search (Q-MPCEA-LS). Finally, comparative experiments between the Q-MPCEA-LS algorithm and various metaheuristic algorithms are conducted. The experimental results show that, across all instances, the average relative error in the average value metric of the Q-MPCEA-LS algorithm is 40.0%, 0.1%, 44.2%, and 75.9% lower than that of Q-MPCEA-LS without local search, Q-MPCEA-LS without Q-learning-based dynamic parameter adjustment, the iterative hybrid metaheuristic algorithm, and the hybrid genetic immune algorithm, respectively. These results validate the effectiveness of the individual components and the overall effectiveness of the Q-MPCEA-LS algorithm.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107076"},"PeriodicalIF":4.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739565","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 trajectory-based algorithm enhanced by Q-learning and cloud integration for hybrid flexible flowshop scheduling problem with sequence-dependent setup times: A case study 基于q -学习和云集成的基于轨迹的混合灵活流水车间调度问题的案例研究

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-28 DOI: 10.1016/j.cor.2025.107079

Fehmi Burcin Ozsoydan

{"title":"A trajectory-based algorithm enhanced by Q-learning and cloud integration for hybrid flexible flowshop scheduling problem with sequence-dependent setup times: A case study","authors":"Fehmi Burcin Ozsoydan","doi":"10.1016/j.cor.2025.107079","DOIUrl":"10.1016/j.cor.2025.107079","url":null,"abstract":"<div><div>Eliminating non-production times in scheduling systems has seized attention for decades. Since scheduling problems have discrete search spaces with complex constraints, metaheuristic algorithms are commonly used by a notable number of researchers and practitioners. Although these algorithms do not guarantee optimality, they offer notable opportunities. Moreover, employing machine learning methods in such algorithms draws significant attention due to their promising capabilities such as learning patterns out from data for autonomous decision-making. Accordingly, this study introduces an Iterated Greedy Search algorithm enhanced by Q-learning method. In this regard, a new state evaluation method so as to process inputs in an aggregated fashion is proposed first. Different modifications of this function are adopted by two distinct Q-learning mechanisms. Accordingly, the proposed method autonomously tunes both algorithm parameters and local search procedures. Secondarily, a cloud-integrated scheduler adopting the proposed method is developed as a prototype model. Thus, information derived out from data can be shared among devices and plants at any location. The proposed strategy is tested on a hybrid flexible flowshop scheduling problem with sequence-dependent setup times and release times, which has numerous applications in industry. The performance of the proposed approach is compared to a number of well-regarded and commonly used algorithms. In this context, synthetic problem data is used first. Subsequent to demonstration of the superiority of the proposed approach in these problems and conducting comparisons with CPLEX solver, it is tested on production data. Comprehensive experimental study and statistically verified results point out the efficiency of the proposed approach.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107079"},"PeriodicalIF":4.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825678","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

Scheduling optimization for laminated door machining shop based on improved genetic algorithm 基于改进遗传算法的层合门加工车间调度优化

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-28 DOI: 10.1016/j.cor.2025.107078

Xiaomin Zhou, Rongrong Li, Zhihui Wu

{"title":"Scheduling optimization for laminated door machining shop based on improved genetic algorithm","authors":"Xiaomin Zhou, Rongrong Li, Zhihui Wu","doi":"10.1016/j.cor.2025.107078","DOIUrl":"10.1016/j.cor.2025.107078","url":null,"abstract":"<div><div>In the digital transformation of the wooden-door manufacturing industry, material preparation planning and production scheduling directly influence the stability and effectiveness of the manufacturing system. Constructive problem-specific algorithms have been instrumental in solving real-world laminated door machining shop scheduling problem (LDMSSP). LDMSSP is a complex problem that combines a distributed permutation flow-shop scheduling problem and distributed hybrid flow-shop scheduling problem. An improved genetic algorithm fused with the strategies of the improved heuristic algorithm, the local search, variable neighborhood search with multiple critical paths, and the iterated greedy search (IGGA) was proposed for application in the material preparation planning and scheduling optimization to minimize the makespan. Comprehensive design of experiments and statistical analyses were conducted to determine appropriate algorithm parameters and verify the substantial improvement of the IGGA. Experiments conducted on various benchmark instances indicated that IGGA outperformed other metaheuristics in both the best relative deviation index and the average relative deviation index. In the end, the minimal makespan for a real-world case involving the production of 74 laminated doors was 1.1 h with a 17.91% reduction, which further demonstrated the effectiveness of the proposed model and algorithm in solving LDMSSP. It also provided a valuable reference for the rational arrangement of material preparation planning and machining scheduling sequences.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107078"},"PeriodicalIF":4.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759493","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

Container slot allocation policy in vessel pool alliance under stochastic demand 随机需求下船池联盟集装箱舱位分配策略

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-28 DOI: 10.1016/j.cor.2025.107074

Jinpeng Liang, Yuhang Zhou, Shuang Wang, Jianfeng Zheng

{"title":"Container slot allocation policy in vessel pool alliance under stochastic demand","authors":"Jinpeng Liang, Yuhang Zhou, Shuang Wang, Jianfeng Zheng","doi":"10.1016/j.cor.2025.107074","DOIUrl":"10.1016/j.cor.2025.107074","url":null,"abstract":"<div><div>The vessel pool alliance is a prominent cooperation model within the liner shipping industry, where a joint operator manages the collective shipping capacities of all alliance members. The primary challenge for the alliance manager is the efficient allocation of container slots among cargoes with stochastic demand. This study addresses this complex problem by formulating it as a stochastic linear programming model aimed at maximizing the alliance’s total freight revenue while simultaneously ensuring adequate revenue for each member operator, thereby maintaining long-term alliance stability. To solve this problem, we first employ an enhanced Depth-First Search algorithm to identify a set of feasible transportation paths for each cargo. Subsequently, we develop an efficient policy to determine the optimal slot allocation for each realized demand scenario. Numerical experiments using both synthetic and real-world data demonstrate that our proposed policy significantly outperforms the container slot exchange alliance and independent operation modes currently prevalent in practice. Our approach notably enhances revenues for both the alliance as a whole and individual member operators by optimizing the utilization of slot resources.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107074"},"PeriodicalIF":4.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746340","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

Optimization of ship-deployed AUVs synergisticscheduling for offshore wind turbines underwater foundations inspection 海上风力机水下基础检测舰载auv协同调度优化

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-28 DOI: 10.1016/j.cor.2025.107080

Yuzhen Hu , Xu Han , Min Wang , Valery F. Lukinykh , Jianxia Liu , Xiaotian Zhuang

{"title":"Optimization of ship-deployed AUVs synergisticscheduling for offshore wind turbines underwater foundations inspection","authors":"Yuzhen Hu , Xu Han , Min Wang , Valery F. Lukinykh , Jianxia Liu , Xiaotian Zhuang","doi":"10.1016/j.cor.2025.107080","DOIUrl":"10.1016/j.cor.2025.107080","url":null,"abstract":"<div><div>Guided by the IMO’s GHG reduction strategy and the “dual-carbon” goal, offshore wind power has become vital in renewable energy, and more attention has been paid to the regular inspection of offshore wind turbines (OWTs). The Autonomous Underwater Vehicle (AUV) has significantly improved inspection, but the current technology limits it to independently perform long-distance and complex tasks. We propose a ship-deployed AUVs synergistic mode to cover larger area inspections in a shorter period. A mixed-integer programming model is developed to optimize the ships’ routes and schedule AUVs’ drop and pick-up time. An adaptive large neighborhood search heuristic based on constraint programming (ALNSCP) is developed for large-scale instances. The simulation instances-based computational experiments verify the superiority of the synergistic mode and solution method in improving inspection efficiency. Sensitivity analysis further reveals how AUV debugging time and allowed float time affect inspection efficiency and cost. The analysis of variants with limited deployable AUVs and soft time windows enhances the applicability of the proposed solution. This study can realize the efficiency of AUV utilization and provide decision support for OWTs underwater foundations inspection.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"181 ","pages":"Article 107080"},"PeriodicalIF":4.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143824149","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

Beyond location modeling and GIS: Integration and bridging 超越位置建模与地理信息系统：整合与衔接

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-27 DOI: 10.1016/j.cor.2025.107073

Alan T. Murray

{"title":"Beyond location modeling and GIS: Integration and bridging","authors":"Alan T. Murray","doi":"10.1016/j.cor.2025.107073","DOIUrl":"10.1016/j.cor.2025.107073","url":null,"abstract":"<div><div>The importance of good locational decision making cannot be understated. In many cases it is quite literally a question of life and death, whether in the context of safety and security or associated with the viability of business activity. As a result, location modeling has become essential in system understanding, designing or extension in whatever way spatial choice is considered. Location modeling too is central in addressing sustainability, resilience, efficiency and effectiveness across a range of urban and environmental contexts. Over the past three decades geographic information systems, and more generally GIScience, has emerged as a critical complement to location modeling. This paper seeks to articulate and demonstrate how GIScience is now a central component of location modeling, one that fundamentally bridges geographic information systems and optimization in many ways. GIScience primitives are formally structured and specified in order to make linkages explicit in the context of location modeling. This is significant as GIScience helps to further establish locational theory and principles that form the basis of model extension as well as enables better solution approaches to be developed. Because of this, continued integration of location modeling and GIS is anticipated in the coming years and decades.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107073"},"PeriodicalIF":4.1,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767725","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}

引用次数: 0

Periodic chains scheduling on dedicated resources - A crucial problem in time-sensitive networks 专用资源上的周期链调度——时间敏感网络中的一个关键问题

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-27 DOI: 10.1016/j.cor.2025.107072

Josef Grus , Claire Hanen , Zdeněk Hanzálek

{"title":"Periodic chains scheduling on dedicated resources - A crucial problem in time-sensitive networks","authors":"Josef Grus , Claire Hanen , Zdeněk Hanzálek","doi":"10.1016/j.cor.2025.107072","DOIUrl":"10.1016/j.cor.2025.107072","url":null,"abstract":"<div><div>Periodic messages transfer data from sensors to actuators in cars, planes, and complex production machines. When considering a given routing, the unicast message starts at its source and goes over several dedicated resources to reach its destination. Such unicast message can be represented as a chain of point-to-point communications. Thus, the scheduling of the periodic chains is a principal problem in time-triggered Ethernet, like IEEE 802.1Qbv Time-Sensitive Networks. This paper studies a strongly NP-hard periodic scheduling problem with harmonic periods, task chains, and dedicated resources. We analyze the problem on several levels and provide proofs of complexity and approximation algorithms for several special cases. We describe a solution methodology to find a feasible schedule that minimizes the chains’ degeneracy related to start-to-end latency normalized in the number of periods. We use the local search with the first fit scheduling heuristic, which we warm-start with a constraint programming model. This notably improves the schedulability of instances with up to 100% utilization and thousands (and more) of tasks, with high-quality solutions found in minutes. An efficient constraint programming matheuristic significantly reduces the degeneracy of the found schedules even further. The method is evaluated on sets of industrial-, avionic-, and automotive-inspired instances.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107072"},"PeriodicalIF":4.1,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746341","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}

引用次数: 0

A hybrid approach using ant colony optimisation for integrated scheduling of production and transportation tasks within flexible manufacturing systems 在柔性制造系统中使用蚁群优化集成调度生产和运输任务的混合方法

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-26 DOI: 10.1016/j.cor.2025.107059

Naihui He , M’hammed Sahnoun , David Zhang , Belgacem Bettayeb

{"title":"A hybrid approach using ant colony optimisation for integrated scheduling of production and transportation tasks within flexible manufacturing systems","authors":"Naihui He , M’hammed Sahnoun , David Zhang , Belgacem Bettayeb","doi":"10.1016/j.cor.2025.107059","DOIUrl":"10.1016/j.cor.2025.107059","url":null,"abstract":"<div><div>This paper studies the integrated scheduling problem in flexible manufacturing systems (FMS), where flexible machines and Automated Guided Vehicles (AGV) shared by production jobs are scheduled simultaneously in an integrated manner. Routing flexibility, a crucial advantage of FMS, enabling a job to be handled via alternative machine combinations, is involved. To address this problem, we propose a novel hybrid approach using Ant Colony Optimisation (ACO), which employs a two-element vector structure to model the ACO decision nodes. Each node represents an operation from a job assigned to a particular machine. During the ACO process, to decide a node for next movement, an ant first assesses potential nodes through a node scheduling procedure with two consecutive steps: firstly, using a heuristic vehicle assignment method, an AGV is designated and scheduled for the operation specified in a node. Following this, based on the established transportation timeline, the operation’s production schedule on the assigned machine is determined. Subsequently, the node selection is guided by the pheromone information on potential paths and the heuristic data of potential nodes derived from their scheduling information. To avoid local optima, multiple heuristic rules are incorporated in the ACO, with one chosen randomly for node selection each time. Numerical tests show that our proposed approach outperforms contemporary metaheuristic approaches in the literature. In addition, its efficiency of handling complex problem instances is also assessed and demonstrated.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107059"},"PeriodicalIF":4.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739680","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}

引用次数: 0

A novel decision support framework for multi-objective aircraft routing problem 一种新的多目标飞机航路决策支持框架

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-26 DOI: 10.1016/j.cor.2025.107058

Francisco López-Ramos , Francisco Benita , Nuno Antunes Ribeiro

{"title":"A novel decision support framework for multi-objective aircraft routing problem","authors":"Francisco López-Ramos , Francisco Benita , Nuno Antunes Ribeiro","doi":"10.1016/j.cor.2025.107058","DOIUrl":"10.1016/j.cor.2025.107058","url":null,"abstract":"<div><div>The aircraft routing problem has received extensive attention from researchers, prompting the utilization of diverse problem-solving approaches and the use of various metrics to inform decision-making. Despite the wealth of research, airline managers often rely heavily on their own experience when evaluating potential aircraft routing solutions. To bridge this gap and empower airline managers with a robust decision-making process, this paper proposes a novel modeling framework and decision support tool for solving the Multi-Objective Aircraft Routing Problem. Our methodological framework comprises 3 modules: (i) an efficient data handling and storage process to manage a large volume of data and ensure data tractability; (ii) a novel mixed-integer linear programming model to effectively solve the aircraft routing problem within 1 to 5 min of computation, even at large instances; (iii) a multi-objective algorithmic framework that effectively employs parallelization techniques to generate Pareto-optimal frontiers within 30 min of computation. The three components are integrated into an unified decision support tool that empowers airline managers to visualize and evaluate various aircraft routing solutions, considering multiple objectives simultaneously while leveraging the use of multi-criteria methods. To validate the proposed approach, historic data from AirAsia is used for testing. The results demonstrate the tool’s capability to generate high-quality solutions that strike a balance between conflicting objectives, affirming its practicality and effectiveness in real-world applications.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107058"},"PeriodicalIF":4.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714212","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

Modelling a capacitated location problem for designing multimodal vaccine distribution network using a novel Health Emergency Susceptibility Index 基于突发卫生事件易感性指数的多模式疫苗配送网络选址问题建模

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-26 DOI: 10.1016/j.cor.2025.107056

Biswajit Kar, Mamata Jenamani

{"title":"Modelling a capacitated location problem for designing multimodal vaccine distribution network using a novel Health Emergency Susceptibility Index","authors":"Biswajit Kar, Mamata Jenamani","doi":"10.1016/j.cor.2025.107056","DOIUrl":"10.1016/j.cor.2025.107056","url":null,"abstract":"<div><div>Health emergency due to the outbreak of a contagious virus augments the need for effective vaccine distribution strategies to control its spread. This paper suggests a two-phase strategy to solve this problem. Phase I constructs a Health Emergency Susceptibility Index for each region, considering the disease data and comorbidity situation. Phase II uses the HESI and proposes three versions of priority weights for different application scenarios. These are used as the priority weights to formulate a capacitated location problem with a multimodal network and multiple types of refrigerators. The model considers additional factors like storage capacity, locations, transportation distances (including air and ground options), costs (maintenance and transportation), and vehicle capacity. To solve the model for large networks, the paper suggests a solution approach using Benders Decomposition with extreme directions. To validate the models, we examine the case of COVID-19 vaccine distribution in India. To assess the impact of the Susceptibility Index on facility locations, proposed weightage versions are compared with a version that does not use the index. The results show that one of the three versions with weighting schemes based on the population-to-susceptibility ratio leads to the most cost-effective distribution strategy, ensuring coverage of all susceptible regions. Furthermore, the Decomposition-based solution significantly improves computational efficiency, solving the problem over fifty times faster than the commercial solver.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107056"},"PeriodicalIF":4.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725703","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