Locust swarm optimisation for the permutation flow shop scheduling problem

The permutation flow shop scheduling problem (PFSP) is one of the most prominent types of combinatorial optimisation problems. The fact comes from its wide applications in manufactures and industries. In this paper, the locust swarm optimisation algorithm (LO) is proposed to find high quality solution for the PFSP, it simulates the behaviour of locust swarm. In this work, the LO algorithm is adapted to solve the PFSP with the objective of minimising the makespan where a heuristic rule called smallest position value (SPV) is triggered to transform the random numbers into sequences of jobs. Then the NEH heuristic of Nawaz-Enscore-Ham is applied to generate good quality initial population. Also, a simple and efficient iterated local search method is employed to explore the solution space efficiently. An experimental study is discussed in this paper to evaluate the performance of the introduced algorithm. Different well-known PFSP benchmarks of small, medium and large size instances are used for this purpose. The computational and statistical studies demonstrate that the proposed algorithm is evidently outperforming the recent algorithms in obtaining better solutions.