Minimizing makespan for the distributed hybrid flowshop scheduling problem with multiprocessor tasks

Abstract

The trend of globalization has recently seen the study of distributed scheduling problems. This study attempts to solve the distributed hybrid flowshop scheduling problem with multiprocessor tasks, and is the first attempt to address this problem. To solve this strongly NP-hard problem, a mixed integer linear programming formulation and self-tuning iterated greedy (SIG) algorithm that incorporates an adaptive cocktail decoding mechanism are presented to minimize the makespan. Comprehensive computational results demonstrate that the proposed SIG algorithm is extremely efficient and effective. This paper successfully expands the research area of distributed scheduling problems.