检索结果-内蒙古大学图书馆

Annual Reliability and Maintainability Symposium (RAMS)

作者： Zuo, Xiaorong Xiao, Yiyong Zhu, Chuan You, Meng Beihang Univ Sch Reliabil & Syst Engn 37 Xueyuan Rd Beijing 100191 Peoples R China

ISBN: (纸本)9781538628690

The paper studies the Electric vehicle routing problem with time-window (EVRPTW) in the field of logistics maintenance optimization. We use mixed integer linear programming techniques to model the EVRPTW considering various factors encountered in practice, including the battery's capacity limit, charge station selection, and battery's charging time determination, in order to improve the availability of electric vehicle in modern logistics system. Computational experiments are carried out to verify the feasibility of the proposed model and compare it with traditional routing model, which show that our model fits better for real-life applications and can yield better schedules that improve the utilization of electric vehicles.

关键词： vehicle routing problem with time windows time window Electric vehicle Linear charging

来源：评论

学校读者我要写书评

暂无评论

Hybrid Genetic Simulated Annealing Algorithm with its application in vehicle routing problem with time windows

Hybrid Genetic Simulated Annealing Algorithm with its applic...

引用

International Conference on Advances in Materials and Manufacturing Processes

作者： Zhang, Qiang Lin, Qingguo Zhang, Qin Fang, Jichen Wang, Zhan'gen Shi, Mengzhu Shandong Univ Sch Mech Engn Jinan 250061 Peoples R China

ISBN: (纸本)9780878492015

Under the situations of distribution center and customer demand, a mathematical model of vehicle routing problem with time windows(VRPTW) is set up, where the main factors of less total distance of vehicles driving and less delayed time of vehicles are considered. For the "premature" convergence in Genetic Algorithms, Simulated Annealing Algorithm is introduced, and GSA is designed to optimize and analyse the VRPTW examples. It is shown that the performance of GSA is better than Genetic Annealing(GA).

关键词： vehicle routing problem with time windows Heuristic Simulated annealing Genetic Annealing Genetic Simulated Annealing

来源：评论

学校读者我要写书评

暂无评论

A Parallel Algorithm for Minimizing the Number of Routes in the vehicle routing problem with time windows 1

引用

9th International Conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Blocho, Miroslaw Czech, Zbigniew J. Silesia Univ Technol Gliwice Poland

ISBN: (数字)9783642314643

ISBN: (纸本)9783642314636;9783642314643

A parallel algorithm for minimizing the number of routes in the vehicle routing problem with time windows (VRPTW) is presented. The algorithm components cooperate periodically by exchanging their best solutions with the lowest number of routes found to date. The objective of the work is to analyze speedup, achieved accuracy of solutions and scalability of the MPI implementation. For comparisons the selected VRPTW tests are used. The derived results justify the proposed parallelization concept. By making use of the parallel algorithm the twelve new best-known solutions for Gehring and Homberger's benchmarking tests were found.

关键词： parallel algorithm vehicle routing problem with time windows guided local search heuristics approximation algorithms MPI library

来源：评论

学校读者我要写书评

暂无评论

Parallel simulated annealing for the vehicle routing problem with time windows

Parallel simulated annealing for the vehicle routing problem...

引用

10th Euromicro Workshop on Parallel, Distributed and Network-based Processing (PDP 2002)

作者： Czech, ZJ Czarnas, P Silesia Univ Technol Gliwice Poland

ISBN: (纸本)0769514448

A parallel simulated annealing algorithm to solve the vehicle routing problem with time windows is presented. The objective is to find the best possible solutions to some well-known instances of the problem by using parallelism. The empirical evidence indicate that parallel simulated annealing can be applied with success to bicriterion optimization problems.

关键词： parallel simulated annealing message passing model of parallel computation vehicle routing problem with time windows bicriterion optimization

来源：评论

学校读者我要写书评

暂无评论

A neighborhood comprehensive learning particle swarm optimization for the vehicle routing problem with time windows

引用

SWARM AND EVOLUTIONARY COMPUTATION 2024年 84卷

作者： Wu, Qichao Xia, Xuewen Song, Haojie Zeng, Hui Xu, Xing Zhang, Yinglong Yu, Fei Wu, Hongrun Minnan Normal Univ Coll Phys & Informat Engn Zhangzhou 363000 Fujian Peoples R China Minnan Normal Univ Key Lab Intelligent Optimizat & Informat Zhangzhou 363000 Fujian Peoples R China XinJiang Inst Engn Urumqi 830091 Xinjiang Uygur Peoples R China

vehicle routing problem with time windows (VRPTW), which is a typical NP-hard combinatorial optimization problem, plays an important role in modern logistics and transportation systems. Recent years, heuristic and meta-heuristic algorithms have attracted many researchers' attentions to solve the VRPTW problems. As an outstanding meta-heuristic algorithm, particle swarm optimization (PSO) algorithm exhibits very promising performance on continuous problems. However, how to adapt PSO to efficiently deal with VRPTW is still challenging work. In this paper, we propose a neighborhood comprehensive learning particle swarm optimization (N-CLPSO) to solve VRPTW. To improve the exploitation capability of N-CLPSO, we introduce a new remove-reinsert neighborhood search mechanism, which consists of the removed operator and the reinsert operator. When performing the removed operator, the probability of adjacency between two customers is calculated by an information matrix (IM), which is constructed based on the customers' time-space information and elite individuals' local information. When executing the reinsert operator, the IM and a cost matrix (CM), which is introduced to record the cost of customer insertion, are used to find an optimal insert position. Moreover, to enhance the exploration of N-CLPSO, a semi-random disturbance strategy is proposed, in which elites' longest common sequences (LCS) are saved, aiming to prevent population degradation. The N-CLPSO algorithm is tested on 56 Solomon benchmark instances, and it attains the optimal solutions on 29 instances. The simulation results and comparison results illustrate that the proposed algorithm outperforms or can compete with the majority of other 3 PSO variants as well as other 12 state-of-the-art algorithms.

关键词： vehicle routing problem with time windows Particle swarm optimization Neighborhood search Longest common sequence

来源：评论

学校读者我要写书评

暂无评论

Two evolutionary approaches with objective-specific variation operators for vehicle routing problem with time windows and quality of service objectives

引用

APPLIED SOFT COMPUTING 2023年 134卷

作者： Srivastava, Gaurav Singh, Alok Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Telangana India

This paper addresses a variant of the vehicle routing problem with time windows where the goal is to maximize the quality of service delivered to the customer. In the literature, this problem contains three objectives targeted at improving the quality of service. In this paper, we have proposed two evolutionary approaches, viz., a steady-state grouping genetic algorithm and a discrete differential evolution algorithm, to address this problem. The crossover and mutation operators are designed by considering the characteristics of each objective. The proposed approaches are incorporated with various heuristics that provide a set of better initial solutions in comparison to purely random initial solutions. We have also proposed two bounds for each objective. The approaches presented in this paper are tested on the Solomon instances which are considered as the standard benchmark instances for the vehicle routing problem with time windows in the literature. The proposed approaches are compared with the state-of-the-art approach available in the literature. The computational results demonstrate that our approaches are better in terms of solution quality and execution time than the state-of-the-art approach.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Grouping genetic algorithm Discrete differential evolution vehicle routing problem with time windows Quality of service Heuristics

来源：评论

学校读者我要写书评

暂无评论

Hybrid multiobjective evolutionary algorithm considering combination timing for multi-type vehicle routing problem with time windows

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2022年 171卷

作者： Zhang, Wenqiang Li, Haoran Yang, Weidong Zhang, Guohui Gen, Mitsuo Henan Univ Technol Key Lab Grain Informat Proc & Control Zhengzhou Peoples R China Henan Univ Technol Coll Informat Sci & Engn Zhengzhou Peoples R China Zhengzhou Univ Aeronaut Sch Management Engn Zhengzhou Peoples R China Tokyo Univ Sci Fuzzy Logic Syst Inst Tokyo Japan

vehicle routing problem (VRP) has been a classical combinatorial optimization challenge, which has been extensively investigated in recent decades. As a VRP typical variant, multi-type vehicle routing problem with time windows (MT-VRPTW) has been concerned with multiple types of heterogeneous fleets of vehicles, within the delivery time window and limited capacity constraints. For such complicated multiobjective optimization problems, hybrid multiobjective evolutionary algorithm (HMOEA) has become an effective method, however, the research on hybrid algorithms and combination timing is still challenging. This study proposes a hybrid multiobjective evolutionary algorithm based on combination timing (HMOEA-CT) to solve MT-VRPTW with the criteria of minimizing the number of vehicles and wasting time simultaneously. The HMOEA-CT combines a fast convergence in multiple directions (FCMDs)-based global search and a problem-specific difference (PSD)-based local search in different evolutionary stages. The FCMD is assumed to be the global exploration search strategy, which converges faster at the center and edge regions of the Pareto front. The PSD is used to improve the local exploitation search ability by directing poor-performing individuals closer to better-performing individuals. Furthermore, the PSD cooperates with FCMD at the right time according to the different evolutionary stages to improve efficiency. Experimental results on Solomon benchmark problems demonstrate the competitive performance comparison of the HMOEA-CT with traditional multiobjective evolutionary algorithms.

关键词： Multiobjective evolutionary algorithm vehicle routing problem with time windows Multi-type vehicle Hybrid algorithm Combination timing

来源：评论

学校读者我要写书评

暂无评论

The parallelization of a two-phase distributed hybrid ruin-and-recreate genetic algorithm for solving multi-objective vehicle routing problem with time windows

引用

EXPERT SYSTEMS WITH APPLICATIONS 2021年 168卷 114408-114408页

作者： Khoo, Thau Soon Mohammad, Babrdel Bonab Univ Tunku Abdul Rahman Ctr Artificial Intelligence & Comp Applicat Selangor Malaysia

Solving multi-objective vehicle routing problem with time windows (MOVRPTW) involves satisfying two or more objectives. However, not many algorithms can achieve a broader set of Pareto optimal front and consistent solutions that have the least difference in magnitude. Therefore, it is rewarding to develop a coveted algorithm that solves these shortcomings. In this paper, we propose the parallelization of a two-phase distributed hybrid ruin-and-recreate genetic algorithm (HRRGA). The algorithms in HRRGA run in either the HRRGA and the hybrid ruin-and-recreate (HRR) phase or the HRR phase. In HRRGA phase, different HRR strategies are used with the hybrid genetic algorithm (HGA) in the near-optimal solution computation. However, in the HRR phase, only the HRR strategies are used. The algorithms in HRRGA are executed in parallel and harness its power of exploitation and exploration. These strategy combinations improve the diversity of the Pareto optimal front while delivering the generated solutions with the least difference in magnitude. Our experiment with Solomon's benchmark set shows that HRRGA has superior results compared to the recently published hybrid algorithm, has diverse set of Pareto optimal fronts, and achieves several novel Pareto optimal fronts compared to the best-known solutions.

关键词： Genetic algorithm Ruin-and-recreate Combinatorial optimization Objective function vehicle routing problem with time windows

来源：评论

学校读者我要写书评

暂无评论

NSGA-II with objective-specific variation operators for multiobjective vehicle routing problem with time windows

引用

EXPERT SYSTEMS WITH APPLICATIONS 2021年 176卷 114779-114779页

作者： Srivastava, Gaurav Singh, Alok Mallipeddi, Rammohan Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Telangana India Kyungpook Natl Univ Sch Elect Engn Deaprtment Artificial Intelligence Daegu 41566 South Korea

vehicle routing problem with time windows (VRPTW) is a pivotal problem in logistics domain as it possesses multiobjective characteristics in real-world applications. Literature contains a general multiobjective VRPTW (MOVRPTW) with five objectives along with MOVRPTW benchmark instances that are derived from real-world data. In this paper, we have proposed a nondominated sorting genetic algorithm II (NSGA-II) based approach with objective-specific variation operators to address the MOVRPTW. In the proposed NSGA-II approach, the crossover and mutation operators are designed by exploiting the problem characteristics as well as the attributes of each objective. The performance of the proposed approach is evaluated on the standard benchmark instances of the problem and compared with the state-of-the-art approach available in literature. The computational results demonstrate the superiority of our approach over the state-of-the-art approach for the MOVRPTW.

关键词： Evolutionary algorithms Multiobjective optimization Nondominated sorting genetic algorithm II vehicle routing problem with time windows

来源：评论

学校读者我要写书评

暂无评论

Quality of service objectives for vehicle routing problem with time windows

引用

APPLIED SOFT COMPUTING 2019年 84卷 105707-000页

作者： Exposito, Airam Brito, Julio Moreno, Jose A. Exposito-Izquierdo, Christopher Univ La Laguna Inst Univ Desarrollo Reg Dept Ingn Informat & Sistemas San Cristobal De La Lagu Spain

In this paper we tackle a variant of the vehicle routing problem from the perspective of the quality in customer service. The proposed model corresponds to a routing planning problem where, in addition to the efficiency in the use of resources and time, the delivery process requires to reduce the response time to satisfy the customer demands. The problem includes the constraints of the well-known vehicle routing problem with time windows but incorporates objective functions aimed at optimizing the service quality. The quality is here associated with the time the vehicles reach the existing customers within their time windows. Due to the complexity of the optimization problem under analysis, approximate approaches are identified as promising candidates to obtain high-quality solutions within reasonable computational times in realistic scenarios. In this regard, we propose a hybrid metaheuristic that combines the features of the Greedy Randomized Adaptive Search Procedure and the Variable Neighbourhood Search in order to generate efficient solutions of the optimization problem. The computational experiments demonstrate our algorithmic proposal is highly effective in providing high-quality solutions of classic problem instances and requires short computational times. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Metaheuristics Transport Quality of service vehicle routing problem with time windows Greedy randomized adaptive search procedure Variable neighbourhood search

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：