Bi-objective simulated annealing and adaptive memory procedure approaches to solve a hybrid flow shop scheduling problem with unrelated parallel machines

Abstract

In this paper, a novel hybrid flow shop scheduling problem with respect to the both objectives of total setup time and cost is investigated. Since the problem is NP-hard, we focus on suboptimal scheduling solutions for the hybrid flow shop with unrelated parallel machines, sequence and machine-dependent setup time, eligibility constraint and release time. In this research, total sequence and machine-dependent setup time and cost are used as the objective functions. We present a multi-objective simulated annealing (MOSA) and an adaptive memory procedure (MOAMP) in order to find a set of non-dominated solutions. The problem solved with different number of jobs and stages using MOSA and MOAMP algorithms. Computational results showed that the proposed MOAMP approach is more effective and efficient than the simulated annealing algorithm in terms of reduced setup criterions for the attempted problem.