Genetic Algorithms and Random Keys for Sequencing and Optimization

1 May 1994

journal article
Published by Institute for Operations Research and the Management Sciences (INFORMS) in INFORMS Journal on Computing

Vol. 6 (2) , 154-160
https://doi.org/10.1287/ijoc.6.2.154

Abstract

In this paper we present a general genetic algorithm to address a wide variety of sequencing and optimization problems including multiple machine scheduling, resource allocation, and the quadratic assignment problem. When addressing such problems, genetic algorithms typically have difficulty maintaining feasibility from parent to offspring. This is overcome with a robust representation technique called random keys. Computational results are shown for multiple machine scheduling, resource allocation, and quadratic assignment problems. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.

Keywords

This publication has 0 references indexed in Scilit: