Pareto Optimal Based Evolutionary Approach for Solving Multi-Objective Facility Layout Problem

Over the years, various evolutionary approaches have been proposed in efforts to solve the facility layout problem (FLP). Unfortunately, most of these approaches are limited to a single objective only, and often fail to meet the requirements for real-world applications. To date, there are only a few multi-objective FLP approaches have been proposed. However, they are implemented using weighted sum method and inherit the customary problems of this method. In this paper, we propose an evolutionary approach for solving multi-objective FLP using multi-objective genetic algorithm that presents the layout as a set of Pareto optimal solutions optimizing both quantitative and qualitative objective simultaneously. Experimental results obtained with the proposed algorithm on test problems taken from the literature are promising.

[1]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[2]  Ajith Abraham,et al.  How to Solve a Multicriterion Problem for Which Pareto Dominance Relationship Cannot Be Applied? A Case Study from Medicine , 2006, KES.

[3]  D. Sha,et al.  Heuristic approach for solving the multi-objective facility layout problem , 2005 .

[4]  Rrk Sharma,et al.  A review of different approaches to the facility layout problems , 2006 .

[5]  S. Sahu,et al.  A genetic algorithm for facility layout , 1995 .

[6]  Marcos Ribeiro Pereira Barretto,et al.  A solution to the facility layout problem using simulated annealing , 1998 .

[7]  L. A. Al-Hakim,et al.  On solving facility layout problems using genetic algorithms , 2000 .

[8]  Andrew Kusiak,et al.  The facility layout problem , 1987 .

[9]  Wen-Chyuan Chiang,et al.  An improved tabu search heuristic for solving facility layout design problems , 1996 .

[10]  Kulendran Balamurugan,et al.  Manufacturing facilities layout design using Genetic Algorithm , 2008, Int. J. Manuf. Technol. Manag..

[11]  Thomas E. Vollmann,et al.  An Experimental Comparison of Techniques for the Assignment of Facilities to Locations , 1968, Oper. Res..

[12]  S. Sahu,et al.  A multigoal heuristic for facilities design problems: MUGHAL , 1982 .

[13]  Charles Gide,et al.  Cours d'économie politique , 1911 .

[14]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[15]  Michael H. Hu,et al.  Using genetic algorithms on facilities layout problems , 2004 .

[16]  E. Shayan,et al.  Facilities layout design by genetic algorithms , 1998 .

[17]  M. Ye,et al.  A local genetic approach to multi-objective, facility layout problems with fixed aisles , 2007 .

[18]  Lakhmi C. Jain,et al.  Knowledge-Based Intelligent Information and Engineering Systems , 2004, Lecture Notes in Computer Science.

[19]  Surya Prakash Singh,et al.  An improved heuristic approach for multi-objective facility layout problem , 2010 .

[20]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[21]  K. C. Chan,et al.  A study of genetic crossover operations on the facilities layout problem , 1994 .