Computers & Operations Research最新文献_第2页

Integrated electric ground vehicle and drone with blockchain-driven approach for routing delivery 集成电动地面车辆和无人机，采用区块链驱动的路线交付方法

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-04-02 DOI: 10.1016/j.cor.2025.107057

Ramdhan Nugraha , Adriansyah Dwi Rendragraha , Soo Young Shin

引用次数: 0

Developing reward-risk aversion distributionally robust contract design models under ambiguous output probabilities 在模糊输出概率下建立报酬-风险厌恶分布鲁棒契约设计模型

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-04-01 DOI: 10.1016/j.cor.2025.107061

Naiqi Liu, Wansheng Tang, Yanfei Lan

{"title":"Developing reward-risk aversion distributionally robust contract design models under ambiguous output probabilities","authors":"Naiqi Liu, Wansheng Tang, Yanfei Lan","doi":"10.1016/j.cor.2025.107061","DOIUrl":"10.1016/j.cor.2025.107061","url":null,"abstract":"<div><div>In this study, we address robust contract design problem, where the principal is ambiguous about effort-contingent multi-output probability distribution of the agent. To model this type of distributionally robust contract design problem, the Wasserstein ambiguity set is employed to characterize the ambiguous multi-output probability distribution. Two decision criteria are adopted by the principal to evaluate the designed robust contract under partial distribution information, the first is the worst-case expected criterion, and the second is the worst-case risk criterion. Furthermore, the concept of distributionally robust incentive compatibility is defined with respect to a pair of ambiguity sets. In virtue of two decision criteria, this paper develops a new reward-risk distributionally robust contract design model as well as its extension models based on different risk measures and globalized distributionally robust incentive compatibility condition. The distributionally robust counterpart and globalized distributionally robust counterpart problems of the developed distributionally robust contract design models are linear programming or mixed-integer linear programming models. According to the structural characteristic of the resulting mixed-integer linear programming model, a new tailored Benders decomposition algorithm is designed. At the end of this paper, an inventory decision with backorder problem is addressed and some numerical experiments are performed to demonstrate the influences of three risk measures on robust optimal contracts. The computational results demonstrate that the developed distributionally robust contract design models can facilitate the principal to make the informed contract decisions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107061"},"PeriodicalIF":4.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759494","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

An ILP-based exact approach for solving the variable cost and size bin packing problem with time-dependent cost modeling the shared satellite-based last-mile delivery 基于ilp的基于时间依赖成本建模的最后一英里共享卫星配送变成本和尺寸装箱问题精确求解方法

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-29 DOI: 10.1016/j.cor.2025.107075

Roberto Bargetto , Maria Elena Bruni , Guido Perboli

{"title":"An ILP-based exact approach for solving the variable cost and size bin packing problem with time-dependent cost modeling the shared satellite-based last-mile delivery","authors":"Roberto Bargetto , Maria Elena Bruni , Guido Perboli","doi":"10.1016/j.cor.2025.107075","DOIUrl":"10.1016/j.cor.2025.107075","url":null,"abstract":"<div><div>In the nowadays common two-tier logistic systems for delivering products in urban areas, the last leg of the distribution chain, the so-called last mile, is by far the most problematic. The modeling of the last-mile delivery problem as a variable cost and size bin packing problem with time-dependent costs emerged recently as the best solution for planning the delivery operations. No exact solution has been yet proposed for efficiently solving this variant of the bin packing problem. In this paper, we present a new problem formulation and devise an exact branch-and-bound method for effective and efficient problem resolution. Upon the resulting tailored solution approach, we devise a procedure to speed up the problem resolution further. Numerical results collected on large-sized instances reveal the dramatic reduction of the computation time obtained with our solution approach, which turns out to be up to ten times faster than the commercial solver. The improvement in solving large-sized instances with a relatively easy-to-implement approach is remarkably relevant for real-world applications.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107075"},"PeriodicalIF":4.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777497","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

Integration of decision levels in operating room scheduling problems: Systematic review and proposition of a decision support framework 手术室调度问题中决策层次的整合：一个决策支持框架的系统回顾与提出

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-29 DOI: 10.1016/j.cor.2025.107063

Igor Eduardo Santos de Melo, Flavio Sanson Fogliatto

{"title":"Integration of decision levels in operating room scheduling problems: Systematic review and proposition of a decision support framework","authors":"Igor Eduardo Santos de Melo, Flavio Sanson Fogliatto","doi":"10.1016/j.cor.2025.107063","DOIUrl":"10.1016/j.cor.2025.107063","url":null,"abstract":"<div><div>Resource allocation problems are a significant subset of optimization problems widely present in the healthcare industry. Notably, the Operating Room Scheduling Problem (ORSP) is prominent in literature due to its substantial cost and revenue implications. ORSP is structured into three hierarchical decision levels: strategic, tactical and operational, with higher-level decisions influencing subsequent ones. While most studies focus on single decision levels, there has been a growing interest in integrated models, as these offer a more holistic view and often result in better outcomes, despite their complexity of resolution. Although various literature reviews have explored different aspects of ORSP, few have focused on models integrating multiple decision levels. This study addresses that gap by systematically reviewing the literature focusing on contributions presenting mathematical programming models and optimization algorithms that simultaneously address multiple decision levels of the ORSP. Following the PRISMA 2020 protocol, the review spans works published until October 2024, totaling 46 articles. It outlines objectives, characteristics, solution approaches, and identifies gaps in literature. Additionally, a decision framework summarizing the identified integration levels is proposed.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107063"},"PeriodicalIF":4.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759496","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

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