Introduction to algorithms
HOPE: a genetic algorithm for the unequal area facility layout problem
Computers and Operations Research
Fast evaluation of sequence pair in block placement by longest common subsequence computation
DATE '00 Proceedings of the conference on Design, automation and test in Europe
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The optimisation of block layout and aisle structure by a genetic algorithm
Computers and Industrial Engineering
VLSI module placement based on rectangle-packing by the sequence-pair
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Traditionally the design of Inter-cell layout and Material Handling System (MHS) of the manufacturing system is being carried out in step by step. This leads to sub-optimal solutions for facility layout problems (FLP). In this work an attempt is made to concurrently design Inter-cell layout and the MHS using a Genetic Algorithm (GA) based methodology using simulated annealing algorithm (SAA) as local search tool for a Cellular Manufacturing System (CMS) environment under open field configuration. The proposed algorithm is employed to simultaneously optimize two contradicting objectives viz. 1. Total material handling cost 2. Distance weighted cost of closeness rating score. The algorithm is tested on two different bench mark layouts and with different initial problem data sets. It is found that the proposed algorithm is able to produce approximate pareto-optimal solutions.