多指标固定收费运输问题的混合粒子群优化算法

Bikramjit Singh, Amarinder Singh
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引用次数: 0

摘要

将多种产品从产地运输到目的地,并且在运输路线上收取一定的固定费用的运输问题称为多指标固定收费运输问题(MIFCTP)。这个NP-hard离散优化问题已经被许多研究者解决,并提出了一个最优性条件。本文采用粒子群算法与三种新算法相结合的方法解决了这一问题。粒子群算法是一种基于群体的算法,它通过粒子的相互作用来寻找最优解。本文提出的三种算法解决了不同初始种群的问题,并获得了问题的非负积分解。该混合粒子群算法提高了最优运输成本,从而解决了MIFCTP的现有最优条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Particle Swarm Optimization Algorithm to Solve Multi-Index Fixed Charge Transportation Problem
The transportation problem in which multiple products are transported from sources to destinations and some fixed-charge is levied on the transportation routes is called a Multi-Index Fixed Charge Transportation Problem (MIFCTP). This NP-hard discrete optimization problem has been solved by many researchers and an optimality condition was proposed. This paper solves the problem through a Particle Swarm Optimization (PSO) based procedure that is hybridized with three new algorithms. PSO is a population-based algorithm that searches for an optimal solution through an interaction of the particles. The three algorithms proposed in this paper address the issues of diverse initial population and obtaining non-negative integral solutions of the problem. This Hybrid PSO improves the optimal transportation cost thereby addressing the existing optimality condition for MIFCTP.
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