Using a Bee Colony Algorithm for Neighborhood Search in Job Shop Scheduling Problems

This paper describes a population-based approach that uses a honey bees foraging model to solve job shop scheduling problems. The algorithm applies an efficient neighborhood structure to search for feasible solutions and iteratively improve on prior solutions. The initial solutions are generated using a set of priority dispatching rules. Experimental results comparing the proposed honey bee colony approach with existing approaches such as ant colony, tabu search and shifting bottleneck procedure on a set of job shop problems are presented. The results indicate the performance of the proposed approach is comparable to other efficient scheduling approaches.