Computers & Operations Research最新文献

英文中文

Optimization of passenger flow control and customized bus bridging in urban rail transit network

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-02-06 DOI: 10.1016/j.cor.2025.106997

Qingqing Zhao , Jinjin Tang , Chao Li , Qiuhan Dong , Tao Feng , Xingwei Yang

When dealing with large passenger flows in urban rail transit, developing reasonable passenger flow control plans is a crucial aspect of operational management. When many passengers wait outside the stations, customized buses can serve as an effective way to alleviate passenger pressure. To obtain reasonable passenger flow control and customized bus connection plans, we propose an optimization method for passenger flow control and customized bus connections. Firstly, we construct a two-stage model. The first-stage model formulates the passenger flow control plan to minimize the number of waiting passengers inside and outside the station considering factors such as passenger arrivals and urban rail transit train departures and arrivals. The second-stage model develops the customized bus plan based on a time–space-state network. According to the characteristics of the model, the CPLEX solver is used to solve the first-stage model, and a Lagrange relaxation-based solution method is designed to solve the second-stage model. To verify the effectiveness of the model, a small-scale case study including two lines and five stations is designed, and the results show that the proposed method can achieve effective passenger flow control and bus connection plans. Additionally, actual data from the Chengdu Metro is used to further validate the feasibility of the method. The results indicate that the passenger flow control and bus bridging plans can effectively reduce passenger waiting time. The proposed method can effectively alleviate passenger pressure, ensure passenger travel safety, and further promote the coordinated development of public transportation.

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引用次数: 0

Multi-neighborhood simulated annealing for the oven scheduling problem

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-02-05 DOI: 10.1016/j.cor.2025.106999

Francesca Da Ros , Luca Di Gaspero , Marie-Louise Lackner , Nysret Musliu , Felix Winter

The Oven Scheduling Problem (OSP) is an NP-hard real-world parallel batch scheduling problem that arises in the semiconductor manufacturing sector. It aims to group compatible jobs in batches and to find an optimal schedule in order to reduce oven runtime, setup costs, and job tardiness. This work proposes a Simulated Annealing (SA) algorithm for the OSP, encompassing a unique combination of four neighborhoods and a construction heuristic as initial solution. An extensive experimental evaluation is performed, benchmarking the proposed SA algorithm against state-of-the-art methods. The results show that this approach consistently finds new upper bounds for large instances, while for smaller instances, it achieves solutions of comparable quality to state-of-the-art methods. These results are delivered in significantly less time than the literature approaches require. Additionally, the SA is extended to tackle a related batch scheduling problem from the literature. Even in this case, the algorithm confirms its effectiveness and robustness across different problem formulations by improving results for many instances.

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引用次数: 0

Knowledge graph based question-answering model with subgraph retrieval optimization

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-02-01 DOI: 10.1016/j.cor.2025.106995

Rui Zhu , Bo Liu , Qiuyu Tian , Ruwen Zhang , Shengxiang Zhang , Yanna Hu , Jiuxin Cao

Knowledge graph-based question answering (QA) is a critical domain within natural language processing, aimed at delivering precise and efficient responses to user queries. Current research predominantly focuses on minimizing subgraph sizes to enhance the efficiency and compactness of the search space. However, natural language queries often exhibit ambiguities, and merely reducing subgraph sizes may overlook relevant answer entities. Additionally, redundant relationships among entities in the knowledge graph can adversely affect QA model performance. To address these limitations, this paper introduces a novel QA model that optimizes subgraph retrieval. The proposed model enhances entity linking and subgraph retrieval by leveraging contextual features from both questions and entities. It disambiguates entities using relevant contextual features and refines the search process through entity relation merging and entity ranking strategies. This methodology improves entity recognition and linking, reduces subgraph dimensions, and broadens answer coverage, resulting in substantial improvements in QA performance. Experimental results on the CCKS2019-CKBQA dataset demonstrate the modelś effectiveness, showing an average F1 score improvement of 2.99% over the leading baseline model. Furthermore, the model’s application in the field of ocean engineering underscores its practical utility and significance.

{"title":"Knowledge graph based question-answering model with subgraph retrieval optimization","authors":"Rui Zhu , Bo Liu , Qiuyu Tian , Ruwen Zhang , Shengxiang Zhang , Yanna Hu , Jiuxin Cao","doi":"10.1016/j.cor.2025.106995","DOIUrl":"10.1016/j.cor.2025.106995","url":null,"abstract":"<div><div>Knowledge graph-based question answering (QA) is a critical domain within natural language processing, aimed at delivering precise and efficient responses to user queries. Current research predominantly focuses on minimizing subgraph sizes to enhance the efficiency and compactness of the search space. However, natural language queries often exhibit ambiguities, and merely reducing subgraph sizes may overlook relevant answer entities. Additionally, redundant relationships among entities in the knowledge graph can adversely affect QA model performance. To address these limitations, this paper introduces a novel QA model that optimizes subgraph retrieval. The proposed model enhances entity linking and subgraph retrieval by leveraging contextual features from both questions and entities. It disambiguates entities using relevant contextual features and refines the search process through entity relation merging and entity ranking strategies. This methodology improves entity recognition and linking, reduces subgraph dimensions, and broadens answer coverage, resulting in substantial improvements in QA performance. Experimental results on the CCKS2019-CKBQA dataset demonstrate the modelś effectiveness, showing an average F1 score improvement of 2.99% over the leading baseline model. Furthermore, the model’s application in the field of ocean engineering underscores its practical utility and significance.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"177 ","pages":"Article 106995"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132610","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

Improved A* algorithm incorporating RRT* thought: A path planning algorithm for AGV in digitalised workshops

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-01-31 DOI: 10.1016/j.cor.2025.106993

Na Liu, Zihang Hu, Min Wei, Pengfei Guo, Shuhan Zhang, Aodi Zhang

The implementation of efficient path planning algorithms can facilitate enhanced transport efficiency in AGVs (Automated Guided Vehicles). However, the current path planning algorithms used in the workshop can determine the shortest path, but there are problems such as low search efficiency, long search time, and many path inflection points. Such issues have the potential to negatively impact the transport efficiency of the AGV, rendering them unsuitable for actual workshop conditions. This paper proposes a new algorithm, named IA-RRT* (Improved A* Algorithm Integrating RRT* Thought), for path planning of AGV in digitalised workshops. The algorithm modifies the cost evaluation function of the A* algorithm to provide a less strong direction for the search, narrowing the search scope and preventing the algorithm from converging too quickly and getting stuck in a local optimal path. Meanwhile, the IA-RRT* algorithm combines the randomness concept of the RRT* algorithm with an inflection point penalty term. The objective is to find a path with fewer inflection points, making it more practical for production. Simulation experiments have shown that the IA-RRT* algorithm outperforms several other path planning algorithms in terms of path length cost, algorithm calculation time, and number of inflection points. The paths generated by the IA-RRT* algorithm are applicable to the working situation of AGV and have practical significance.

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引用次数: 0

A branch-and-cut-and-price algorithm for shared mobility considering customer satisfaction

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-01-31 DOI: 10.1016/j.cor.2025.106998

Min Xu

This study determines the exact optimal fleet size, ride-matching patterns, and vehicle routes for shared mobility services (SMS) that maximize the profit of service operators considering ride-pooling and customer satisfaction. We make the first attempt to consider a nonlinear multivariate customer satisfaction function with respect to the features of the riders and the system under a ‘two riders-single vehicle’ ride-pooling scenario in a special case of dial-a-ride problem (DARP). A set packing model and a tailored branch-and-cut-and-price (BCP) approach are proposed to find the exact optimal solution of the problem. Unlike existing exact solution methods for DARP, we exploit the characteristic of the ride-pooling scenario and decompose the ride matching and vehicle routing in an effective two-phase method to solve the pricing problem of the BCP approach. Particularly, in Phase 1, feasible matching patterns subject to practical constraints are identified. In Phase 2, a heuristic and an exact label-correcting method with a bounded bi-directional search are sequentially employed to solve a new variant of elementary shortest path problem with time window (ESPPTW) in a network constructed upon rides and feasible ride matching patterns identified in Phase 1. The labeling methods are further accelerated by a strengthened dominance test, the aggregate extension to other depots, and the decremental search space. Valid inequalities are also incorporated to further improve the upper bound. The proposed solution method is evaluated in randomly generated instances and the instances created from the real mobility data of Didi. Managerial insights are generated through impact analysis.

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引用次数: 0

Benders decomposition for the large-scale probabilistic set covering problem

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-01-30 DOI: 10.1016/j.cor.2025.106994

Jie Liang , Cheng-Yang Yu , Wei Lv , Wei-Kun Chen , Yu-Hong Dai

In this paper, we consider a probabilistic set covering problem (PSCP) in which each 0-1 row of the constraint matrix is random with a finite discrete distribution, and the objective is to minimize the total cost of the selected columns such that each row is covered with a prespecified probability. We develop an effective decomposition algorithm for the PSCP based on the Benders reformulation of a standard mixed integer programming (MIP) formulation. The proposed Benders decomposition (BD) algorithm enjoys two key advantages: (i) the number of variables in the underlying Benders reformulation is equal to the number of columns but independent of the number of scenarios of the random data; and (ii) the Benders feasibility cuts can be separated by an efficient polynomial-time algorithm, which makes it particularly suitable for solving large-scale PSCPs. We enhance the BD algorithm by using initial cuts to strengthen the relaxed master problem, implementing an effective heuristic procedure to find high-quality feasible solutions, and adding mixed integer rounding enhanced Benders feasibility cuts to tighten the problem formulation. Numerical results demonstrate the efficiency of the proposed BD algorithm over a state-of-the-art MIP solver. Moreover, the proposed BD algorithm can efficiently identify optimal solutions for instances with up to 500 rows, 5000 columns, and 2000 scenarios of the random rows.

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引用次数: 0

The vehicle routing problem with transfers

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-01-27 DOI: 10.1016/j.cor.2025.106980

Maichel M. Aguayo , Francisco N. Avilés , Subhash C. Sarin , Claudia Archetti

In the vehicle routing problem (VRP), a fleet of capacitated vehicles serves a set of customers with known demands at minimum cost. The Split Delivery VRP (SDVRP), a variant of VRP, permits customer demands to be served by different vehicles, and thereby results in a significant cost reduction. In this paper, we study the VRP with transfers (VRP-T), where, as in the SDVRP, customers can be visited by multiple vehicles. However, differently from the SDVRP, customer locations can be used as transfer locations to exchange load among vehicles. We find that the routing costs can potentially be reduced by at most 50% by allowing such transfers in the VRP. We develop a two-index mixed-integer programming (MIP) model and heuristic algorithm based on

Multi − start local search (MSLS)

. The solutions obtained by the

MSLS

are used as warm-start for the MIP and the corresponding approach is tested. Computational results indicate substantial savings in the costs incurred and the number of vehicles required when transfers are allowed. Results also suggest that transfers are at least as effective in reducing the cost as split delivery.

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引用次数: 0

Resilient downstream oil supply chain under interdiction and recovery resources allocation using a Column and Constraint Generation algorithm

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-01-25 DOI: 10.1016/j.cor.2025.106978

Leyla Ahmadpour , Rashed Sahraeian , Kourosh Eshghi

A downstream oil supply chain designates the last section of an oil supply chain, which involves the distribution of refined oil products to demand zones. We study in this paper intentional disruptions called interdictions in this supply chain to provide a secure and resilient system. Such a system, which is enabled by fortification elements, is capable of restoring its operations as fast as possible after interdictions. It is vital to take into account the product delivery times affected by interdiction, especially in critical supply chains such as the oil industry. Also, the recovery resources after an interdiction are limited. So, we propose a tri-level defender-attacker-defender model to address the problem in which product delivery time and recovery resources allocation are included. Next, we present two exact solution approaches, including Implicit Enumeration (IE) and Column and Constraint Generation (C&CG), to solve the tri-level model. C&CG provides high-quality solutions in a reasonable time compared to the IE. We apply the proposed algorithms to a case study regarding an Iranian downstream oil supply chain. We also conduct an analysis to assess the robustness of the solutions. Sensitivity analysis indicates that increasing the recovery capacity results in a cost reduction of 5 percent on average.

{"title":"Resilient downstream oil supply chain under interdiction and recovery resources allocation using a Column and Constraint Generation algorithm","authors":"Leyla Ahmadpour , Rashed Sahraeian , Kourosh Eshghi","doi":"10.1016/j.cor.2025.106978","DOIUrl":"10.1016/j.cor.2025.106978","url":null,"abstract":"<div><div>A downstream oil supply chain designates the last section of an oil supply chain, which involves the distribution of refined oil products to demand zones. We study in this paper intentional disruptions called interdictions in this supply chain to provide a secure and resilient system. Such a system, which is enabled by fortification elements, is capable of restoring its operations as fast as possible after interdictions. It is vital to take into account the product delivery times affected by interdiction, especially in critical supply chains such as the oil industry. Also, the recovery resources after an interdiction are limited. So, we propose a tri-level defender-attacker-defender model to address the problem in which product delivery time and recovery resources allocation are included. Next, we present two exact solution approaches, including Implicit Enumeration (IE) and Column and Constraint Generation (C&CG), to solve the tri-level model. C&CG provides high-quality solutions in a reasonable time compared to the IE. We apply the proposed algorithms to a case study regarding an Iranian downstream oil supply chain. We also conduct an analysis to assess the robustness of the solutions. Sensitivity analysis indicates that increasing the recovery capacity results in a cost reduction of 5 percent on average.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"177 ","pages":"Article 106978"},"PeriodicalIF":4.1,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132607","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

Operations routing and scheduling problem: Concept, graphing and notation systems

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-01-25 DOI: 10.1016/j.cor.2025.106992

Zhaoqin Jiang, Zhenyuan Liu, Zinuo Zhou, Yeqing Huang, Jingchen Li

Operational demands drive operators, machines, and objects to undertake time–space transfers and execute tasks to optimize system objectives in various engineering, manufacturing, and service scenarios such as prefabricated construction, roadbed construction, open-pit mining, pipe casting, steel processing, IT maintenance, airport shuttle service, and community virus elimination service. Establishing a unified concept model framework for the operations routing and scheduling problem by generalizing the characteristics of the problems portrayed by research in various fields, not only integrates research in multiple fields and connects the methods, but also provides a systematic and in-depth portrayal of the elemental structure of the problem. This unification enhances understanding of related research and forms a synergy in the field.

This paper explores the establishment of a unified modeling framework for the problem, using a concept system based on elemental analysis, a graphing system based on time–space network, a problem taxonomy and a notation system. The elements in the problem, including the operators, operation machines, operation objects, operation time–space, and operation relations, are analyzed. A unified graphing system is designed for each element and scenario to organize in a time–space network diagram, including a time–space transfer diagram, a operation space diagram, and an operation network diagram. Based on the type, quantity, function, and structure of each element, a taxonomy and a four-domain notation system for the problem are established. The unified modeling framework is then applied to describe eight typical scenarios, demonstrating its wide applicability.

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引用次数: 0

A novel communication-efficient heterogeneous federated positive and unlabeled learning method for credit scoring

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research

Pub Date : 2025-01-18 DOI: 10.1016/j.cor.2025.106982

Yongqin Qiu , Yuanxing Chen , Kan Fang , Kuangnan Fang

Customer records include only customers in default (positive samples) and rejected customers (unlabeled samples), or positive and unlabeled (PU) data, which is a common scenario in emerging financial institutions. However, building credit scoring models using multiple small sample PU datasets with high dimensionality poses significant challenges, especially in light of the privacy constraints associated with transferring raw data. To tackle these challenges, this paper introduces a novel methodology called heterogeneous federated PU learning. This approach utilizes a fused penalty function to automatically divide coefficients into multiple clusters, while an efficient proximal gradient descent algorithm is introduced for model training, relying solely on gradients from local servers. Theoretical analysis establishes the oracle property of our proposed estimator. The simulation results show that, in terms of variable selection, parameter estimation, and prediction performance, our method is close to the Oracle estimator and outperforms the other alternatives. Empirical results indicate that our method can improve prediction performance and facilitate the identification of heterogeneity across datasets. Moreover, the estimated clustering structures further reveal that provinces that are geographically closer exhibit greater similarity in credit risk. This implies that the proposed methodology can effectively assist nascent financial institutions in identifying differences in risk factors across datasets and enhancing predictive accuracy.

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