TWO-STAGE ASSEMBLY FLOWSHOP SCHEDULING PROBLEM WITH MAXIMUM LATENESS AND MAKESPAN

We consider a two-stage assembly flowshop scheduling problem with the objective of minimizing a weighted sum of makespan and maximum lateness. The problem is known to be NP-hard, and therefore, we propose heuristics to solve the problem. The proposed heuristics are Tabu search (Tabu), particle swarm optimization (PSO), and self-adaptive differential evolution (SDE). An extensive computational experiment is conducted to compare the performance of the proposed heuristics. The computational experiment reveals that both PSO and SDE are much superior to Tabu. Moreover, it is statistically shown that PSO perform better than and SDE. The computation time of both PSO and SDE are close to each other and it is less than 45 seconds for the largest size problem considered.