A plant growth simulation algorithm for permutation flow shop scheduling to minimize makespan

Abstract

The flow shop scheduling problem is a branch of production scheduling, which is among the hardest combinatorial optimization problem, and represents an important area in production scheduling. In this paper, a new effective hybrid algorithm is proposed which is based on plant growth simulation algorithm for permutation flow shop scheduling with the criterion to minimize the maximum completion time (makespan). In the algorithm, a directed graph which is based on the characteristic of flow shop scheduling problem representation is developed, and an efficient exchangeable node set is proposed and incorporated into plant growth simulation algorithm. Simulation results based on well-known benchmarks and comparisons with standard genetic algorithm demonstrate the effectiveness of the proposed bionic algorithm.