Volume 2, Issue 3, December 2009, Pages 236 - 247
A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems
Cengiz Kahraman, Orhan Engin, Mustafa Kerim Yilmaz
Available Online 1 December 2009.
- https://doi.org/10.2991/ijcis.2009.2.3.5How to use a DOI?
- Fuzzy flow shop, new artificial immune system, multi objective, engine cylinder liner manufacturing process.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Cengiz Kahraman AU - Orhan Engin AU - Mustafa Kerim Yilmaz PY - 2009 DA - 2009/12 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 - https://doi.org/10.2991/ijcis.2009.2.3.5 ID - Kahraman2009 ER -