Solving the non-linear multi-index transportation problems with genetic algorithms

Tatiana Pasa
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引用次数: 0

Abstract

In this paper we study the non-linear multi-index transporta\-tion problem with concave cost functions. We solved the non-linear transportation problem on a network with 5 indices (NTPN5I) described by sources, destinations, intermediate nodes, types of products, and types of transport, that is formulated as a non-linear transportation problem on a network with 3 indices (NTPN3I) described by arcs, types of products, and types of transport. We propose a genetic algorithm for solving the large-scale problems in reasonable amount of time, which was proven by the various tests shown in this paper. The convergence theorem of the algorithm is formulated and proved. The algorithm was implemented in Wolfram Language and tested in Wolfram Mathematica.
用遗传算法求解非线性多指标运输问题
本文研究了具有凹代价函数的非线性多指标运输问题。我们解决了由来源、目的地、中间节点、产品类型和运输类型描述的具有5个指标的网络(NTPN5I)上的非线性运输问题,并将其表述为由弧线、产品类型和运输类型描述的具有3个指标的网络(NTPN3I)上的非线性运输问题。我们提出了一种遗传算法,可以在合理的时间内解决大规模问题,并通过本文所示的各种测试证明了这一点。推导并证明了该算法的收敛性定理。算法在Wolfram语言中实现,并在Wolfram Mathematica中进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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