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What is Evolutionary (Genetic) Algorithm

Chapter 42
Handbook of Research on Nature-Inspired Computing for Economics and Management
An evolutionary algorithm (EA) is an stochastic search procedure inspired by the evolution process in nature. In this process, a population of individuals evolve, and the fitter ones have a better chance of reproduction and survival. The reproduction mechanisms favor the characteristics of the stronger parents and hopefully produce better children, guaranteeing the presence of those characteristics in future generations.
Published in Chapter:
Solving Facility Location Problems with a Tol for Rapid Development of Multi-Objective Evolutionary Algorithms (MOEAs)
A. L. Medaglia (Universidad de los Andes, Colombia)
Copyright: © 2007 |Pages: 19
DOI: 10.4018/978-1-59140-984-7.ch042
Abstract
The low price of coffee in the international markets has forced the Federación Nacional de Cafeteros de Colombia (FNCC) to look for cost-cutting opportunities. An alternative that has been considered is the reduction of the operating infrastructure by closing some of the FNCC-owned depots. This new proposal of the coffee supplier network is supported by (uncapacitated and capacitated) facility location models that minimize operating costs while maximizing service level (coverage). These bi-objective optimization models are solved by means of NSGA II, a multi-objective evolutionary algorithm (MOEA). From a computational perspective, this chapter presents the multi-objective Java Genetic Algorithm (MO-JGA) framework, a new tool for the rapid development of MOEAs built on top of the Java Genetic Algorithm (JGA). We illustrate MO-JGA by implementing NSGA II-based solutions for the bi-objective location models.
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