Genetic algorithms for solving a class of constrained nonlinear integer programs

Genetic algorithms for solving a class of constrained nonlinear integer programs

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Article ID: iaor20022010
Country: United Kingdom
Volume: 8
Issue: 1
Start Page Number: 61
End Page Number: 74
Publication Date: Jan 2001
Journal: International Transactions in Operational Research
Authors: , ,
Keywords: genetic algorithms, batch size
Abstract:

We consider a class of constrained nonlinear integer programs, which arise in manufacturing batch-sizing problems with multiple raw materials. In this paper, we investigate the use of genetic algorithms (GAs) for solving these models. Both binary and real coded genetic algorithms with six different penalty functions are developed. The real coded genetic algorithm works well for all six penalty functions compared to binary coding. A new method to calculate the penalty coefficient is also discussed. Numerical examples are provided and computational experiences are discussed.

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