An imperialist competitive algorithm with memory for distributed unrelated parallel machines scheduling

Abstract

Distributed scheduling becomes popular with the shift of production from single factory to multiple factories and reveals new features and the increasing optimisation difficulties. In this study, distributed unrelated parallel machines scheduling problem with makespan minimisation is considered in the heterogeneous production network, which is directly simplified as an extended machine assignment. A novel imperialist competitive algorithm with memory (MICA) is presented, in which a machine assignment string is adopted and four neighbourhood structures and a global search operator are introduced. In each empire, some best colonies learn from a member of memory or imperialist and other colonies move toward imperialist or one of the best colonies, and revolution is newly implemented by using good solutions. Global search of imperialist is added into imperialist competition to avoid the addition of the weakest colony of the weakest empire into the winning empire. Lower bound is provided. Extensive experiments are conducted to test the performance of MICA and computational results show that MICA is a very competitive method for the considered problem.

Keywords:

• parallel machines
• scheduling
• imperialist competitive algorithm
• multi-factory production network

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [61573264] and the Excellent Dissertation Cultivation Funds of Wuhan University of Technology (2017-YS-068).