Title: An ant colonial optimisation approach for no-wait permutation flow shop scheduling

Authors: Ahitsham Shad Khan; Mirza Jahanzaib; Ahmad Wasim; Salman Hussain

Addresses: Industrial Engineering Department, University of Engineering and Technology Taxila, Pakistan ' Industrial Engineering Department, University of Engineering and Technology Taxila, Pakistan ' Industrial Engineering Department, University of Engineering and Technology Taxila, Pakistan ' Industrial Engineering Department, University of Engineering and Technology Taxila, Pakistan

Abstract: This research aims to address the applications of variants of ant colony optimisation (ACO) approach to solve no-wait flow shop scheduling problem (NW-FSSP). The most suitable ACO algorithm out of basic algorithms has been selected and modified to achieve more purified results. The algorithm was coded in visual basic. The varied algorithm has been applied to the bench mark problems and results were compared with the results achieved previously by other researchers using different meta-heuristics. The research covers detailed steps carried out for application of basic ACO algorithms on bench mark problems, comparison of results achieved by application of basic ACO algorithms, selection of best out of basic algorithms, modification of selected basic algorithm and generation of varied ACO algorithm. The varied ACO algorithm gave reasonably good results for almost all the problems under consideration and was able to handle fairly large sized problems with far less computational time. Comparative analysis depicted that the proposed ACO algorithm performed better than genetic algorithm on large sized problems and better than Rajendran heuristic in almost all problems under considerations.

Keywords: flow shop; ant colony optimisation; ACO; algorithm; make span; non-polynomial; NP; hard; jobs; machines.

DOI: 10.1504/IJQI.2017.090539

International Journal of Quality and Innovation, 2017 Vol.3 No.2/3/4, pp.172 - 187

Received: 09 Dec 2016
Accepted: 11 May 2017

Published online: 12 Mar 2018 *

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