Abstract
This paper reports a study of the flowshop scheduling problem with two machines where a set of tasks must be scheduled on a set of machines respecting the same fixed order. The objective was to design the best schedule optimizing the sum of completion times for the job criteria while respecting the release dates (i.e. start times) and the classical blocking constraint, whereby a job remains blocked on a machine as long as the next machine in execution is unavailable or the buffer cannot receive the job. We examine several metaheuristics based on simulated annealing, local search, discrete differential evolution, and genetic algorithms. The experimental results compare the performance of the proposed metaheuristics with each other.