Minimizing the Sum of Makespan and Total Weighted Tardiness in a No-Wait Flowshop

This paper presents a cloud theory-based iterated greedy (CTIG) algorithm for solving the no-wait flowshop scheduling problem (NWFSP) with the objective of minimizing the sum of makespan and total weighted tardiness. The performance of the proposed CTIG algorithm is evaluated by comparing its computational results to those of the best-to-date meta-heuristic algorithm, particle swarm optimization (PSO), as presented in this paper. The experimental results concerning two sets of benchmark problem instances in this paper demonstrate that the CTIG algorithm obtains more (near) optimal solution in less computational time than the PSO algorithm. The computational results in this paper fill the research gap in the development of a novel algorithm to improve the solution quality in the case of the NWFSP with the objective of minimizing the sum of makespan and total weighted tardiness.