“…Therefore, in order to make the algorithm more efficiently, a number of neighborhood evaluation strategies, such as exact methods and estimation methods, have been proposed. The procedure suggested by Ten Eikelder et al(1999), called bowtie, is the most efficient exact method for the JSSP, which only recalculates the head and the tail values of the operations that need to be updated after the move. However, this exact method still takes a very long computational time for the larger instances.…”
“…Therefore, in order to make the algorithm more efficiently, a number of neighborhood evaluation strategies, such as exact methods and estimation methods, have been proposed. The procedure suggested by Ten Eikelder et al(1999), called bowtie, is the most efficient exact method for the JSSP, which only recalculates the head and the tail values of the operations that need to be updated after the move. However, this exact method still takes a very long computational time for the larger instances.…”
“…Neighborhood structures play a very important role in local search as the time complexity of a search depends on the size of the neighborhood and the computational cost of the moves (Ten Eikelder et al 1997). In the history of JSP problems, many neighborhood structures have been identified.…”
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.