Bee Colony Optimization algorithm with Big Valley landscape exploitation for Job Shop Scheduling problems

Scheduling is a crucial activity in semiconductor manufacturing industry. Effective scheduling in its operations leads to improvement in the efficiency and utilization of its equipment. Job shop scheduling is an NP-hard problem which is closely related to some of the scheduling activities in this industry. This paper presents an improved bee colony optimization algorithm with big valley landscape exploitation as a biologically inspired approach to solve the job shop scheduling problem. Experimental results comparing our proposed algorithm with shifting bottleneck heuristic, tabu search algorithm and bee colony algorithm with neighborhood search on Taillard JSSP benchmark show that it is comparable to these approaches.