Dependent-chance programming: A class of stochastic optimization

Dependent-chance programming: A class of stochastic optimization

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Article ID: iaor19982987
Country: United Kingdom
Volume: 34
Issue: 12
Start Page Number: 89
End Page Number: 104
Publication Date: Dec 1997
Journal: Computers & Mathematics with Applications
Authors:
Keywords: artificial intelligence, simulation, stochastic processes
Abstract:

This paper provides a theoretical framework of dependent-chance programming, as well as dependent-chance multiobjective programming and dependent-chance goal programming which are new types of stochastic optimization. A stochastic simulation based genetic algorithm is also designed for solving dependent-chance programming models.

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