A local genetic approach to multi-objective, facility layout problems with fixed aisles

Abstract

We develop a new local genetic algorithm hybridized tabu search, to solve multi-criteria facility layout problems. Within these types of problems, we consider two objectives involving material handling costs and non-material relationship requirements according to the idea of systematic layout planning. Our focus is on a particular case which involves the explicit consideration of fixed aisles and transverse passageways between sections. Numerical experiments as well as comparative tests show the great effectiveness of the proposed method in dealing with multi-criteria facility layout problems up to some moderate scales.

Keywords:

• Facility layout problem
• Multi-criteria decision making
• Genetic algorithm
• Tabu search
• Systematic layout planning

Acknowledgements

This research work was partially supported by the Grant numberY104171 from Zhejiang Provincial Nature Science Foundation and the Number NX05GL07 from Zhejiang Provincial Philosophical and Social Science Foundation. The authors wish to acknowledge the special contribution of Dr. Soundar R.T. Kumara of the Pennsylvania State University who edited the paper for English.