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Can I read Adaptive Genetic Algorithm for Lot-sizing Problem with Self-adjustment Operation Rate on EtoBox?
Adaptive Genetic Algorithm for Lot-sizing Problem with Self-adjustment Operation Rate by Nguyen Van Hop; Mario T. Tabucanon is a Business, Management and Accounting article available to read on EtoBox.
What is Adaptive Genetic Algorithm for Lot-sizing Problem with Self-adjustment Operation Rate about?
This paper presents a new adaptive genetic algorithm (GA) to escape local optimum solutions of the traditional lotsizing rules. In this GA, the timing of replenishment is encoded as a string of binary digits (a chromosome). Each gene in that chromosome stands for a period. Standard GA operators are used to generate new populations. These populations are evaluated by a fitness function using the replenishment scheme of solution based on the total cost. Through this evaluation, the rates of GA operators for the next generation are automatically adjusted based on the rate of survivor offsprings, which are generated by corresponding operators. The oriented search procedure using these selfadjustment rates of operator schemes can give faster and better solutions. Some experimental results confirm the theoretical judgment.
Who reads Adaptive Genetic Algorithm for Lot-sizing Problem with Self-adjustment Operation Rate?
It is typically read by researchers, students, and practitioners in Business, Management and Accounting.
- Author
- Nguyen Van Hop; Mario T. Tabucanon
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0925-5273)
- Published
- 2005
- Language
- EN
- Field
- Business, Management and Accounting (Social Sciences)