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It is very difficult to accurately predict genetic algorithm evolutions and estimate the effects of any change in the operator and parameter settings. So, the setting of the parameter values is guesswork largely. This research applied the concept of orthogonal arrays as a tool for identifying the optimal operator and parameter settings for a genetic algorithm. This approach was based on the method...
Optimising variables in the quality control of production can be a complex issue, as it may involve many different constraints and expectations on the quality of products which are normally provided from different organisations to form a multiple supply chain. The challenge of measuring product interdependence across various supply chains and identifying a trade-off between quality and cost is not...
Genetic algorithm (GA) technique is a promising approach to identify an optimum manufacturing cost by concurrently considering significant number of related variables. It is a superior technique for discovering optimal alternative solutions for multiple objective optimization problems. In GA, however, the setting of operators and the selections of their parameters could affect the output significantly,...
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