Comparison of Firefly algorithm and Artificial Immune System algorithm for lot streaming in -machine flow shop scheduling

DOI

10.1080/18756891.2012.747713How to use a DOI?

Keywords

Flow shop, Lot streaming, Scheduling, Firefly Algorithm, Artificial Immune System Algorithm

Abstract

Lot streaming is a technique used to split the processing of lots into several sublots (transfer batches) to allow the overlapping of operations in a multistage manufacturing systems thereby shortening the production time (makespan). The objective of this paper is to minimize the makespan and total flow time of -job, -machine lot streaming problem in a flow shop with equal and variable size sublots and also to determine the optimal sublot size. In recent times researchers are concentrating and applying intelligent heuristics to solve flow shop problems with lot streaming. In this research, Firefly Algorithm (FA) and Artificial Immune System (AIS) algorithms are used to solve the problem. The results obtained by the proposed algorithms are also compared with the performance of other worked out traditional heuristics. The computational results shows that the identified algorithms are more efficient, effective and better than the algorithms already tested for this problem.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - G. Vijay Chakaravarthy
AU  - S. Marimuthu
AU  - A. Naveen Sait
PY  - 2012
DA  - 2012/11/01
TI  - Comparison of Firefly algorithm and Artificial Immune System algorithm for lot streaming in -machine flow shop scheduling
JO  - International Journal of Computational Intelligence Systems
SP  - 1184
EP  - 1199
VL  - 5
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.747713
DO  - 10.1080/18756891.2012.747713
ID  - Chakaravarthy2012
ER  -