MIP model and elitist strategy hybrid GA–SA algorithm for layout design

• Published in: Journal of intelligent manufacturing Vol. 29; no. 2; pp. 369 - 387
• Main Authors: Jerin Leno, I., Saravana Sankar, S., Ponnambalam, S. G.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2018; Springer Nature B.V
• Subjects: Advanced manufacturing technologies; Algorithms; Business and Management; Computer simulation; Control; Design; Distance measurement; Elitism; Facilities management; Genetic algorithms; Integer programming; Layouts; Linear programming; Machines; Manufacturing; Manufacturing cells; Manufacturing industry; Materials handling; Mechatronics; Mixed integer; Optimization; Processes; Production; Robotics; Simulated annealing; Facility layout; Manufacturing systems design; Heuristic methods; Material handling
• ISSN: 0956-5515; 1572-8145
• DOI: 10.1007/s10845-015-1113-x

It is most important for any manufacturing industry to have an efficient layout for their production environment to participate in global competition. One of the prime objectives of such an organisation is to decide an optimal arrangement of their facilities (machines or departments) in a two-dimensional planar region satisfying desired objectives, which is termed facility layout problem. To overcome the drawbacks of traditional layout design methodology, it is attempted to solve three important layout design problems such as inter-cell layout design, determination of optimum location for input/output stations and flow path layout design of material handling system simultaneously in an integrated manner. The quality of the final layout is evaluated by minimizing the total material handling cost, where the perimeter distance metric is used for the distance measurement. Sequence-pair, an elegant representation technique is used for layout encoding. The translation from sequence-pair to layout is efficiently done by longest common subsequence computation methodology. Due to the non-polynomial hard nature of the problem considered, an elitist strategy based hybrid genetic algorithm that uses simulated annealing as local search mechanism (ESHGA) is developed and tested with test problem instances available in the literature. The results indicate that proposed integrated methodology with developed mixed integer programming based mathematical model along with ESHGA could generate realistic layouts compared to reported result.