Designing efficient methods for the tandem AGV network design problem using tabu search and genetic algorithm

摘要

A tandem AGV configuration connects all cells of a manufacturing facility/plant by means of non-overlapping, single-vehicle closed loops. Each loop has at least one additional P/D station, provided as an interface between adjacent loops. This study describes the development of tabu search and genetic algorithm procedures for designing tandem AGV systems. The objective is to minimize the maximum workload of the system. Both algorithms have mechanisms to prevent solutions with intersecting loops. The new algorithms and the partitioning algorithm presented by Bozer and Srinivasan are compared using randomly generated test problems. Results show that for large-scale problems, the partitioning algorithm often leads to infeasible configurations with crossed loops in spite of its shorter running time. However the newly developed algorithm avoids infeasible configurations and often yields better objective function values.