Optimisation of distribution networks using Genetic Algorithms. Part 2 - The Genetic Algorithm and Genetic Operators

被引：1

作者：

School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes Campus, Mawson Lakes, SA 5095, Australia ^{[1
]}

不详 ^{[2
]}

机构：

[1] School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes Campus, Mawson Lakes

来源：

Int. J. Manuf. Technol. Manage. | 2008年 / 1卷 / 84-101期

关键词：

Capacitated location-allocation problem; Genetic algorithms; Genetic operators; Optimisation;

D O I：

10.1504/IJMTM.2008.018241

中图分类号：

学科分类号：

摘要：

This paper presents a methodology developed for the optimisation of distribution networks based on Genetic Algorithms (GA), specifically capacitated location-allocation problems. Due to the complexity and extent of the paper, it was split into two parts. Modelling issues and automatic generation of initial population of chromosomes were treated in the first part. This second part details the rest of the GA. Due to the intricacy of the problem, the GA was designed to work only with feasible chromosomes and modified operators were chosen to handle its highly constrained character. They are presented in detail. An example of applying the algorithm for 25 Production Facilities (PF), 10 Distribution Centres (DCs) and 25 Retailers (R)- including 520 variables, tightly interconnected - is presented, demonstrating the robustness of GA and its capacity to tackle problems of considerable size. Copyright © 2008 Inderscience Enterprises Ltd.

引用

页码：84 / 101

页数：17