Scholarlink

This paper explores the Capacitated Vehicle Routing Problem (CVRP) and introduces an Improved Particle Swarm Optimization (IPSO) algorithm, a metaheuristic method based on Particle Swarm Optimization (PSO). The proposed IPSO algorithm is evaluated through comparative experiments against the original PSO, the Max-Min Ant System (MMAS), and Variable Neighborhood Search (VNS), Multi-strategy Partheno-genetic Algorithm Based on Dynamic Reduction Mechanism (DRM-MSPGA), New spotted hyena intelligent algorithm (ISHO). The results highlight the IPSO algorithm’s superior performance in solving various CVRP instances. Specifically, the experimental findings show that IPSO achieves results that are either better than or comparable to known optimal solutions across multiple datasets. This demonstrates the effectiveness, robustness, and competitive edge of the IPSO algorithm in addressing the complex CVRP and optimizing vehicle routing solutions in capacitated scenarios.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Vehicle Scheduling Optimization with Capacity Constraints Based on Improved Particle Swarm Algorithm

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Dan Zhang,
  • Jin Xu,
  • Guang-long Zeng

摘要

This paper explores the Capacitated Vehicle Routing Problem (CVRP) and introduces an Improved Particle Swarm Optimization (IPSO) algorithm, a metaheuristic method based on Particle Swarm Optimization (PSO). The proposed IPSO algorithm is evaluated through comparative experiments against the original PSO, the Max-Min Ant System (MMAS), and Variable Neighborhood Search (VNS), Multi-strategy Partheno-genetic Algorithm Based on Dynamic Reduction Mechanism (DRM-MSPGA), New spotted hyena intelligent algorithm (ISHO). The results highlight the IPSO algorithm’s superior performance in solving various CVRP instances. Specifically, the experimental findings show that IPSO achieves results that are either better than or comparable to known optimal solutions across multiple datasets. This demonstrates the effectiveness, robustness, and competitive edge of the IPSO algorithm in addressing the complex CVRP and optimizing vehicle routing solutions in capacitated scenarios.