Fuzzy coordination of genetic algorithms for vehicle routing problems with time windows

This paper presents a genetic algorithm coordinated by fuzzy rule models to solve the vehicle routing problem with time windows. The fuzzy rule-based coordinators play distinct roles during the genetic algorithm execution. The aim is to trade-off exploration and exploitation behavior for route and distance minimization. Experimental results using classic benchmark test instances suggest that the fuzzy coordinated genetic approach is competitive against classic genetic algorithm.