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 the physical layout of the manufacturing system and that of the material flow path and material handling system are carried out in isolation. In this work, an attempt was made on the integrated layout design, that is, to concurrently design the physical layout and the material handling system using a Genetic Algorithm-based methodology. The proposed algorithm was employed to simultaneously optimize two contradicting objectives viz., 1. Total material handling cost 2. Distance-weighted cost of closeness rating score. The algorithm was tested on four different benchmark layouts and with different initial problem data sets. It was found that the proposed algorithm is able to produce satisfactory solutions consistently within a reasonable computational limit.