Abstract: With the objective of minimizing makespan, an improved niche genetic algorithm (INGA) is proposed to solve the unidirectional guided-path network design problem of automated guided vehicle system under flexible job shop environment. In the genetic algorithm, each chromosome consists of unidirectional guided-path network chromosome and operation chromosome, denoting unidirectional segment direction and feasibility scheduling respectively. Corresponding crossover and mutation operators are designed for two types of chromosome. Neighborhood search is adopted to improve the convergence speed of the algorithm. To keep a high degree of population diversity, niche technology and spirit strategy are applied. The experimental results show that the proposed NGA is effective.

Key words: Automated guided vehicle system, Flexible job shop, Genetic algorithm, Unidirectional guided-path network