An effective iterated local search algorithm for the distributed no-wait flowshop scheduling problem. (April 2023)

• Record Type: Journal Article
• Authors: Avci, Mustafa
• Is Part Of: Engineering applications of artificial intelligence. Volume 120(2023)
• Publication Date: 2023-04
• Subjects: Scheduling -- Flowshop scheduling -- Distributed no-wait -- Iterated local search; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2023.105921
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: The no-wait flowshop scheduling problem (NWFSP) is a variant of the classical flowshop scheduling problem in which the jobs must be processed without any interruption between their operations. The distributed no-wait flowshop scheduling problem (DNWFSP) extends the NWFSP by considering multiple identical factories. The DNWFSP combines two types of decisions, allocating the jobs to the factories and scheduling the set of jobs allocating to the same factory. In this study, an iterated local search (ILS) algorithm is proposed to solve the DNWFSP. The proposed ILS implements a specialized local search in which two variable neighborhood descent (VND) based procedures are incorporated. Moreover, the perturbation strength is adjusted adaptively to the structure of the search space. Another important aspect of our ILS is its simple structure which makes it easy to implement. The performance of ILS is evaluated on a set of benchmark problem instances available in the DNWFSP literature. The results indicate that the developed ILS is able to produce high-quality solutions in short computing times for the DNWFSP.