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Towards Merging Binary Integer Programming Techniques with Genetic Algorithms
2017
Advances in Operations Research
This paper presents a framework based on merging a binary integer programming technique with a genetic algorithm. The framework uses both lower and upper bounds to make the employed mathematical formulation of a problem as tight as possible. For problems whose optimal solutions cannot be obtained, precision is traded with speed through substituting the integrality constrains in a binary integer program with a penalty. In this way, instead of constraining a variable u with binary restriction, u
doi:10.1155/2017/7048042
fatcat:sen5jubm6jhwza5irtdefjzqae