Parameter setting for clonal selection algorithm in facility layout problems

Authors:
Berna Haktanirlar Ulutaş;A. Attila Işlier
Affiliations:
Eskişehir Osmangazi University, Department of Industrial Engineering, Eskişehir, Turkey;Eskişehir Osmangazi University, Department of Industrial Engineering, Eskişehir, Turkey
Venue:
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Year:
2007

Citing 11
Cited 0

Machine layout problem in flexible manufacturing systems

Operations Research
An improvement-type layout algorithm for single and multiple-floor facilities

Management Science
Simulated Annealing and Genetic Algorithms for the Facility LayoutProblem: A Survey

Computational Optimization and Applications
A solution to the facility layout problem using simulated annealing

Computers in Industry - Special issue: ASI'96: life cycle approaches to production systems: management, control and supervision
HOPE: a genetic algorithm for the unequal area facility layout problem

Computers and Operations Research
Facilities layout design by genetic algorithms

ICC&IE Selected papers from the 22nd ICC&IE conference on Computers & industrial engineering
Artificial Immune Systems: A New Computational Intelligence Paradigm

Artificial Immune Systems: A New Computational Intelligence Paradigm
A genetic algorithm for facility layout problems of different manufacturing environments

Computers and Industrial Engineering
An improved genetic algorithm for multi-floor facility layout problems having inner structure walls and passages

Computers and Operations Research
A solution to the unequal area facilities layout problem by genetic algorithm

Computers in Industry - Special issue: Application of genetics algorithms in industry
Optimal facility layout design11This study was supported in part by an Auburn College of Engineering infrastructure award made to Drs. Meller and Vance, and NSF CAREER Grants DMII 9623605 and DMII 9502502.

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

The study introduces a Clonal Selection Algorithm (CSA), which depends on Artificial Immune System principles, for traditional facility layout problems. The CSA aims to minimize the total material handling cost between departments in a single manufacturing period. The determination of the optimum parameters for artificial intelligence algorithms is vital. Therefore a design of experiments study is made. The proposed algorithm is coded and tested by means test problems from literature based on the predefined parameters. The optimum solutions for small sized (5-8 department) layout problems are found. For larger (12, 15, 20, and 30 department) problems 1,077%, 5,703%, 1,126% and 3,671% improvements are obtained respectively. Better solutions are attained within shorter times compared with enumeration and CRAFT solutions.