In this paper we present a general genetic algorithm to address a wide variety o f sequencing and... more In this paper we present a general genetic algorithm to address a wide variety o f sequencing and optimization problems including multiple machine scheduling, reso urce allocation and the quadratic assignment problem. When addressing such probl ems, genetic algorithms typically have difficulty maintaining feasibility from parent to offs pring. This is overcome with a robust representation technique called random keys. Computati onal results are shown for multiple machine scheduling, resource allocation and quadr atic assignment problems.
In this paper we present a general genetic algorithm to address a wide variety o f sequencing and... more In this paper we present a general genetic algorithm to address a wide variety o f sequencing and optimization problems including multiple machine scheduling, reso urce allocation and the quadratic assignment problem. When addressing such probl ems, genetic algorithms typically have difficulty maintaining feasibility from parent to offs pring. This is overcome with a robust representation technique called random keys. Computati onal results are shown for multiple machine scheduling, resource allocation and quadr atic assignment problems.
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Papers by james bean