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This research focuses on the multi-objective optimization of the Traveling Salesman Problem (TSP) considering the cities of Iran. The objective is to minimize both the length of the path and the traffic congestion. To achieve this, a Feasibility-Enhanced Particle Swarm Optimization (FEPSO) algorithm is implemented. The FEPSO algorithm incorporates a feasibility-based approach to enhance the performance of the traditional Particle Swarm Optimization (PSO) algorithm in handling multiple objectives. The algorithm is designed to find optimal routes for salespeople visiting all cities in Iran while considering the shortest path, traffic congestion, safety, and facility. The results demonstrate the effectiveness of the FEPSO algorithm in obtaining well-balanced solutions in terms of path length and traffic congestion for the TSP.

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Multi-objective Routing Optimization of the Traveling Salesman Problem Using Feasibility-Enhanced Particle Swarm Optimization Algorithm

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  • 发表日期：

    2025年

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  • Salar Farahmand-Tabar,
  • Parastoo Afrasyabi

摘要

This research focuses on the multi-objective optimization of the Traveling Salesman Problem (TSP) considering the cities of Iran. The objective is to minimize both the length of the path and the traffic congestion. To achieve this, a Feasibility-Enhanced Particle Swarm Optimization (FEPSO) algorithm is implemented. The FEPSO algorithm incorporates a feasibility-based approach to enhance the performance of the traditional Particle Swarm Optimization (PSO) algorithm in handling multiple objectives. The algorithm is designed to find optimal routes for salespeople visiting all cities in Iran while considering the shortest path, traffic congestion, safety, and facility. The results demonstrate the effectiveness of the FEPSO algorithm in obtaining well-balanced solutions in terms of path length and traffic congestion for the TSP.