Hybrid intelligent water drops algorithm to unrelated parallel machines scheduling problem: a just-in-time approach

• Published in: International journal of production research Vol. 52; no. 19; pp. 5857 - 5879
• Main Authors: Kayvanfar, Vahid, Teymourian, Ehsan
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 02.10.2014
• Subjects: Algorithms; Convergence; earliness and tardiness; Hybrid systems; intelligent water drops (IWD) algorithm; makespan; Mathematical models; Optimization; Rivers; Scheduling; sequence-dependent set-up time (SDST); unrelated parallel machines; Water drops
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2014.923124

Minimising earliness and tardiness penalties as well as maximum completion time (makespan) simultaneously on unrelated parallel machines is tackled in this research. Jobs are sequence-dependent set-up times and due dates are distinct. Since the machines are unrelated, jobs processing time/cost on different machines may vary, i.e. each job could be processed at different processing times with regard to other machines. A mathematical model which minimises the mentioned objective is proposed which is solved optimally via lingo in small-sized cases. An intelligent water drop (IWD) algorithm, as a new swarm-based nature-inspired optimisation one, is also adopted to solve this multi-criteria problem. The IDW algorithm is inspired from natural rivers. A set of good paths among plenty of possible paths could be found via a natural river in its ways from the starting place (source) to the destination which results in eventually finding a very good path to their destination. A comprehensive computational and statistical analysis is conducted to analyse the algorithms' performances. Experimental results reveal that the proposed hybrid IWD algorithm is a trustable and proficient one in finding very good solutions, since it is already proved that the IWD algorithm has the property of the convergence in value.