Abstract
A procedure for solving stochastic two-stage programming problems has been developed. The approach consists of genetic algorithm optimization with point estimate procedures. It has several advantages over traditional methods, such as evaluating function values only, no continuous or gradient requirements and it can solve integer or continuous problems. To improve the performance of the method, a modification of a standard genetic algorithm is suggested and coded. Point estimation methods are used to efficiently evaluate the second stage expected value objective function. Finally, the overall procedure is applied to several linear and nonlinear problems.
Original language | English (US) |
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Pages (from-to) | 279-302 |
Number of pages | 24 |
Journal | Engineering Optimization |
Volume | 33 |
Issue number | 3 |
DOIs | |
State | Published - Feb 2001 |
Keywords
- Genetic algorithms
- Point estimation methods
- Stochastic optimization
ASJC Scopus subject areas
- Computer Science Applications
- Control and Optimization
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Applied Mathematics