A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems

DOI

10.2991/ijcis.2009.2.3.5How to use a DOI?

Keywords

Fuzzy flow shop, new artificial immune system, multi objective, engine cylinder liner manufacturing process.

Abstract

In this paper a new artificial immune system (AIS) algorithm is proposed to solve multi objective fuzzy flow shop scheduling problems. A new mutation operator is also described for this AIS. Fuzzy sets are used to model processing times and due dates. The objectives are to minimize the average tardiness and the number of tardy jobs. The developed new AIS algorithm is tested on real world data collected at an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed AIS is demonstrated by comparing it with genetic algorithms. Computational results demonstrate that the proposed AIS algorithm is more effective meta-heuristic for multi objective flow shop scheduling problems with fuzzy processing time and due date.

Copyright

© 2009, 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  - Cengiz Kahraman
AU  - Orhan Engin
AU  - Mustafa Kerim Yilmaz
PY  - 2009
DA  - 2009/10/01
TI  - A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems
JO  - International Journal of Computational Intelligence Systems
SP  - 236
EP  - 247
VL  - 2
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2009.2.3.5
DO  - 10.2991/ijcis.2009.2.3.5
ID  - Kahraman2009
ER  -