Computers & Operations Research最新文献_第4页

A Stackelberg approach to transportation infrastructure planning: Integrating User Decision-making 交通基础设施规划的Stackelberg方法：整合用户决策

IF 4.3 2区工程技术

Computers & Operations Research Pub Date : 2025-07-24 DOI: 10.1016/j.cor.2025.107211

Oscar-Mauricio Cepeda-Valero , Jose-Fidel Torres-Delgado , Andres D. González

{"title":"A Stackelberg approach to transportation infrastructure planning: Integrating User Decision-making","authors":"Oscar-Mauricio Cepeda-Valero , Jose-Fidel Torres-Delgado , Andres D. González","doi":"10.1016/j.cor.2025.107211","DOIUrl":"10.1016/j.cor.2025.107211","url":null,"abstract":"<div><div>The design of transportation networks is an intriguing and complex subject, primarily driven by the high costs and existing deficiencies in transit systems. Effective network design necessitates the consideration of multiple factors, including the rapid growth of urban centers, the demand for new routes, and the evolving preferences of citizens. A poorly designed network can result in significant drawbacks, such as delays, congestion, and escalated air pollution levels. Consequently, addressing this challenge requires the implementation of targeted modifications in the transport infrastructure, such as constructing new streets, expanding existing roads, enhancing capacity, and improving coverage. The paper introduces a Stackelberg model that addresses the planning of transport infrastructure, focusing on incorporate the user decisions. The model functions on two levels: the upper level captures the decision-making process of users, influenced by factors like time savings and transport system accessibility. Conversely, the lower level relates to the planner’s responsibility in designing and configuring the transport network to align with user demands and preferences while minimizing costs. Four types of transport networks were evaluated based on criteria such as used capacity, network growth, system cost, and unmet user needs. The evaluation revealed that mesh networks perform better due to their ability to distribute user flow across multiple lines, reducing dependency on a few edges. Additionally, the versatility of the procedure is demonstrated through its implementation in the Lausanne metro network.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"184 ","pages":"Article 107211"},"PeriodicalIF":4.3,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144756819","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

Augmentation search for integer programming over a polyhedron 多面体上整数规划的增广搜索

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-22 DOI: 10.1016/j.cor.2025.107204

Tolga Bektaş

引用次数: 0

A deep reinforcement learning method for solving Two-Echelon Location-Routing Problem 求解两梯队位置路由问题的深度强化学习方法

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-21 DOI: 10.1016/j.cor.2025.107210

Shuo Huang , Yaoxin Wu , Zhiguang Cao , Xuexi Zhang

{"title":"A deep reinforcement learning method for solving Two-Echelon Location-Routing Problem","authors":"Shuo Huang , Yaoxin Wu , Zhiguang Cao , Xuexi Zhang","doi":"10.1016/j.cor.2025.107210","DOIUrl":"10.1016/j.cor.2025.107210","url":null,"abstract":"<div><div>In the domain of logistics and supply chain management, optimizing distribution networks is a crucial task for improving efficiency and reducing operational costs. This paper focuses on addressing the Two-Echelon Location-Routing Problem (2E-LRP), with the aim to concurrently optimize the facility (i.e., the transfer station and depot) placement, and vehicle routing for transporting goods between depots, transfer stations, and customers. We propose a method based on deep reinforcement learning to minimize the total costs associated with the operational cost of facilities, the cost of vehicle usage, and transportation cost. Specifically, we design an encoder–decoder structured two-stage attention model that constructs solutions of location-routing problems in two echelons, respectively. A simple yet effective recurrent unit is used in decoder to capture context embeddings, allowing the model to selectively incorporate beneficial information from previous construction steps. The contexts are then used for attention computation to select facilities and customers and thus determine their placements and the routes. The model is trained by REINFORCE algorithm with a shared baseline, and its performance is validated through comparisons with Gurobi solver and typical heuristic algorithms. Extensive results showcase the favorable performance of our model on both synthetic and benchmark instances, which offers a competitive alternative to traditional solutions. Specifically, our model achieves up to 1.5% cost reduction and over 99% computation time savings compared to traditional heuristic algorithms in large instance. In addition, the generalization is fairly good to cope with instances of different scales and distributions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107210"},"PeriodicalIF":4.1,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704129","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

Integrated and sequential algorithms for the robust two-echelon location-routing problem under demand uncertainty 需求不确定条件下鲁棒两梯队定位路由问题的集成序列算法

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-19 DOI: 10.1016/j.cor.2025.107198

Ousmane Ali , Jean-François Côté , Leandro C. Coelho

{"title":"Integrated and sequential algorithms for the robust two-echelon location-routing problem under demand uncertainty","authors":"Ousmane Ali , Jean-François Côté , Leandro C. Coelho","doi":"10.1016/j.cor.2025.107198","DOIUrl":"10.1016/j.cor.2025.107198","url":null,"abstract":"<div><div>This paper addresses the two-echelon capacitated location-routing problem (2E-CLRP) when faced with demand uncertainty. We assume that the customer’s demands at the second echelon are uncertain and design a two-echelon distribution network where open satellites, served from a single depot, have sufficient capacities to handle the variation in demand. At the same time, the planned routes must remain feasible for all values of demand within an uncertainty set. We propose a robust counterpart for an integrated model of the 2E-CLRP and solve it using an adaptive large neighborhood search heuristic and a branch-and-cut algorithm. We also design four non-integrated solution approaches based on the robust counterparts for the 2E-CLRP subproblems, including the vehicle routing problem (VRP), the facility location problem (FLP), the location-routing problem (LRP), and the two-echelon FLP (2E-FLP). The importance of an integrated approach to 2E-CLRP is demonstrated by comparing it to non-integrated approaches. Results show that early integration of location and routing decisions leads to better location and total costs. We also evaluate the price of robustness and the trade-off between conservative and riskier robust solutions using a Monte Carlo simulation. We perform a series of computational experiments to validate the proposed algorithms using benchmark instances for the deterministic 2E-CLRP, LRP and robust VRP.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107198"},"PeriodicalIF":4.1,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687171","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

Two-dimensional bin packing, cutting stock, and open dimension problems: A survey of practical requirements 二维料仓包装、切料和开维问题：实际要求调查

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-15 DOI: 10.1016/j.cor.2025.107209

Matheus Francescatto, Alvaro Neuenfeldt Júnior

{"title":"Two-dimensional bin packing, cutting stock, and open dimension problems: A survey of practical requirements","authors":"Matheus Francescatto, Alvaro Neuenfeldt Júnior","doi":"10.1016/j.cor.2025.107209","DOIUrl":"10.1016/j.cor.2025.107209","url":null,"abstract":"<div><div>Two-dimensional cutting and packing (C&P) problems involve cutting one or more objects into a set of items, resulting in cutting patterns. C&P problems are found in various real-life applications such as the steel, wood, paper, and glass industries, where industrial aspects like raw material reuse, defective objects, trim distance, cutting patterns based on item similarity, and/or demand uncertainty influence the development of solving methods. This article presents a systematic literature review of industrial aspects addressed in cutting-related applications of C&P problems, with a specific focus on two-dimensional bin packing, cutting stock, and open dimension problems. From a sample of 100 articles, 13 key industrial aspects were identified across 13 industry sectors, highlighting how these aspects are incorporated into solving methods. The review also outlines practical benefits observed in real-life applications and proposes a framework to support the implementation of solving methods. Emerging research trends in the C&P area are also discussed. Considering industrial aspects in the design of solving methods contributes to advances in manufacturing, improving production efficiency by reducing raw material waste, cutting costs, and minimizing the time required to generate cutting patterns.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107209"},"PeriodicalIF":4.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655406","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

Probabilistic Vector Machines 概率向量机

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-15 DOI: 10.1016/j.cor.2025.107203

A. Pedro Duarte Silva

引用次数: 0

A decentralised genetic algorithm with sub-objectives for the transit network design problem 交通网络设计问题的分散子目标遗传算法

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-15 DOI: 10.1016/j.cor.2025.107191

Maarten Wens, Pieter Vansteenwegen

{"title":"A decentralised genetic algorithm with sub-objectives for the transit network design problem","authors":"Maarten Wens, Pieter Vansteenwegen","doi":"10.1016/j.cor.2025.107191","DOIUrl":"10.1016/j.cor.2025.107191","url":null,"abstract":"<div><div>This paper introduces a novel approach to the transit network design problem. This technique, based on a genetic algorithm, uses multiple sub-populations in parallel, each prioritising different aspects of the optimal solution. These aspects include minimising transfers, reducing detours, and addressing specific parts of the demand. All of these aspects are important in minimising average passenger travel time, and artificially changing each weight factor in the objective function allows us to escape local optima efficiently. Our algorithm demonstrates improved performance when tested on well-known benchmark instances by diversifying the population and letting each sub-population focus on different parts of a qualitative solution. This algorithm reduces average travel times by more than 2% compared to the current state-of-the-art. Additionally, our approach generates a range of high-quality and distinct solutions, offering valuable insights for decision-makers. The algorithm is also tested on a large, complex instance based on a rural area in Belgium and shows the capability to find improvements over the current transit network.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107191"},"PeriodicalIF":4.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672270","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 weighted Maximum Satisfiability with Branch and Bound and clause learning 用分支定界和子句学习求解加权最大可满足性

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-11 DOI: 10.1016/j.cor.2025.107195

Jordi Coll , Chu-Min Li , Shuolin Li , Djamal Habet , Felip Manyà

{"title":"Solving weighted Maximum Satisfiability with Branch and Bound and clause learning","authors":"Jordi Coll , Chu-Min Li , Shuolin Li , Djamal Habet , Felip Manyà","doi":"10.1016/j.cor.2025.107195","DOIUrl":"10.1016/j.cor.2025.107195","url":null,"abstract":"<div><div>MaxSAT is a widely studied NP-hard optimization problem due to its broad applicability in modeling and solving diverse real-world optimization problems. Branch-and-Bound (BnB) MaxSAT solvers have proven efficient for solving random and crafted instances but have traditionally struggled to compete with SAT-based MaxSAT solvers on industrial instances. However, this changed with the introduction of the MaxCDCL algorithm, which successfully integrates clause learning into BnB to solve unweighted MaxSAT. Despite this progress, solving Weighted MaxSAT instances remained an open challenge. In this paper, we present WMaxCDCL, the first branch-and-bound (BnB) Weighted Partial MaxSAT solver with clause learning. We describe its algorithm and implementation in detail, experimentally evaluating key aspects that are critical to achieving strong performance. Our results demonstrate that WMaxCDCL can compete with the best state-of-the-art MaxSAT solvers and, more importantly, that this new solving approach complements the existing SAT-based MaxSAT methods, which have dominated the field until now. Notably, the combination of WMaxCDCL with other techniques won the weighted track of the 2023 MaxSAT Evaluation, which is the leading annual competition for MaxSAT solvers, affiliated with the International Conference on Theory and Applications of Satisfiability Testing.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"183 ","pages":"Article 107195"},"PeriodicalIF":4.1,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634090","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

Tight upper and lower bounds for the quadratic knapsack problem through binary decision diagrams 用二元决策图求二次型背包问题的紧上界和下界

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-10 DOI: 10.1016/j.cor.2025.107197

M. Eliass Fennich , Leandro C. Coelho , Franklin Djeumou Fomeni

{"title":"Tight upper and lower bounds for the quadratic knapsack problem through binary decision diagrams","authors":"M. Eliass Fennich , Leandro C. Coelho , Franklin Djeumou Fomeni","doi":"10.1016/j.cor.2025.107197","DOIUrl":"10.1016/j.cor.2025.107197","url":null,"abstract":"<div><div>The Quadratic Knapsack Problem (QKP) is a challenging combinatorial optimization problem that has attracted significant attention due to its complexity and practical applications. In recent years, Binary Decision Diagrams (BDDs) have emerged as a powerful tool in combinatorial optimization, providing efficient bounds. In the literature of the QKP, all the exact methods are based on computing tight bounds before applying branch-and-bound (B&B) schemes. We advance this literature in this work by leveraging BDDs to compute bounds more effectively. We propose a novel integration of dual-bound tightening within a BDD-based B&B framework, employing a Breadth-First Search (BFS) strategy. Our approach addresses the critical limitation of existing BDD-based B&B methods, which often lack robust dual-bound tightening mechanisms. Furthermore, we propose several efficient compilation techniques of BDDs for the QKP. Through extensive experimentation on several categories of QKP instances, we demonstrate that our method competes and often surpasses the bounding stages of the leading exact algorithms. Notably, our approach reduces the average duality gap by up to 10% for the class of Hidden Clique QKP instances, showcasing its potential. Furthermore, our findings indicate that the BFS B&B method outperforms state-of-the-art BDD B&B approaches across all tested QKP instances, highlighting its effectiveness and potential for broader application.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"184 ","pages":"Article 107197"},"PeriodicalIF":4.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714246","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

Logic-based Benders decomposition for doctor-patient matching and scheduling considering chronic patients’ online consultation time preference 考虑慢性病患者在线咨询时间偏好的基于逻辑的Benders分解医患匹配与调度

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-07-09 DOI: 10.1016/j.cor.2025.107207

Yan-ping Jiang, Yan Zhang, Zhan Gao, Ting-wen Zheng

引用次数: 0