Sexual Selection for Genetic Algorithms

• Main Authors: GOH, Kai Song, LIM, Andrew, Rodrigues, Brian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2003
• Subjects: Genetic algorithm; Scheduling; Selection; Operations and Supply Chain Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/2147; https://doi.org/10.1023/A:1022692631328
• Institution: Singapore Management University

Genetic Algorithms (GA) have been widely used in operations research and optimization since first proposed. A typical GA comprises three stages, the encoding, the selection and the recombination stages. In this work, we focus our attention on the selection stage of GA, and review a few commonly employed selection schemes and their associated scaling functions.We also examine common problems and solution methods for such selection schemes. We then propose a new selection scheme inspired by sexual selection principles through female choice selection, and compare the performance of this new scheme with commonly used selection methods in solving some well-known problems including the Royal Road Problem, the Open Shop Scheduling Problem and the Job Shop Scheduling Problem.