Swarm-based neighborhood search algorithm for job shop scheduling with batch processing machines

Job shop scheduling problem with batch processing machines frequently exists in the real lift production process; however, the problem is seldom investigated. This paper proposes a scheduling algorithm based on swarm-based neighborhood search to solve the problem. A batch based representation is used after batches are formed by using lots of the same product and a decoding procedure with batching decision is proposed. Then a swap operator is applied to some individuals and an insertion is done on other individuals. The worst solution of the swarm is replaced with the elite solution every iterations. The computational experiment verifies the feasibility and efficiency of the algorithm.