The distributed no-idle permutation flowshop scheduling problem with due windows algorithms

"The Distributed No-Idle Flowshop Scheduling Problem with Due Windows (DNIFSPDW)" addresses an extension of the Distributed Permutation Flowshop Scheduling Problem with No-Idle and Due Window constraints. The objective of DNIFSPDW is to determine the optimal sequence of job assignments to factories and the sequence in which they should be performed in each factory. This optimal sequence should ensure the minimum total weighted earliness and tardiness (TWET) penalties while also taking into account the due windows. The inclusion of a total weighted tardiness objective in the flowshop scheduling problem (FSP), a known NP-hard issue, means that the DNIPFSPDW also inherits this computational complexity, classifying it under the NP-hard category. As a result, exact solution methods are not efficient for large-scale instances of this problem. For such intricate challenges, metaheuristic approaches are more appropriate as they can achieve high-quality solutions in reasonable computation times. Notably, the iterated greedy metaheuristic has proven effective for most PFSPs. Therefore, two hybrid iterated greedy algorithms namely hybrid iterated greedy-tabu search and hybrid iterated greedy-local search are developed for the DNIPFSPDW.
The two attached documents contain the codes for the algorithms discussed. Each file includes the data developed and used to evaluate the distributed no-idle flowshop scheduling problem with due windows. For detailed instructions on executing these codes, please refer to the enclosed Readme file. The document titled "Java Codes" houses the executable codes.