Abstract:
An Ikeda map embedded genetic algorithm is introduced in this research in order to solve the order picking problem. The chaos based algorithm is compared against the cano...Show MoreMetadata
Abstract:
An Ikeda map embedded genetic algorithm is introduced in this research in order to solve the order picking problem. The chaos based algorithm is compared against the canonical pseudo-random number based genetic algorithm over thirty test instances of varying complexity. From the results, the chaos based genetic algorithm is shown to have better overall performance, especially for larger sized problem instances. The statistical paired t-test comparison of the results further reinforces the fact that the chaos based genetic algorithm is significantly better performing.
Published in: 2014 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS)
Date of Conference: 09-12 December 2014
Date Added to IEEE Xplore: 15 January 2015
Electronic ISBN:978-1-4799-4500-9