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Home  >  Volume 25 (2013)

On The Use of Heuristics and Genetic Agorithm For Solving Line Balancing Problems by Edokpia R.O. and Okonta C. I. Vol.25 ( Nov. 2013). pp 267-280
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The problem of assembly line balancing is a non-deterministic polynomial-time (NP) - hard optimization problem. Some approximation algorithms for the problem have been proposed but most of them are either not optimal or too complex to apply. This paper utilizes the combination of longest operation time, ranked positional weight and Kilbridge-Wester heuristics and finally Genetic Algorithm to solve assembly line balancing problem solved by Ponnanbalam et al (2000) in which they used 14 heuristics and GA to solve the ALBP . The GA adopts a fitness function based on realized cycle time and a crossover based on fitness ranking. The computational effectiveness and efficiency of using genetic algorithm in solving ALBP was validated by comparison with a multi objective genetic algorithm, utilizing fourteen heuristic rules for solving simple assembly line balancing problems. The three heuristics genetic algorithm was found to perform better, from the view point of optimization giving a line efficiency of 92.59% and smoothness index of 2.45.