Minimization of the total weighted tardiness on a single machine scheduling problem with a position based learning effect and unequal release dates. Issue 2 (3rd May 2021)

• Record Type: Journal Article
• Authors: Muştu, Settar; Eren, Tamer
• Is Part Of: Infor. Volume 59:Issue 2(2021)
• Page Start: 353
• Page End: 376
• Publication Date: 2021-05-03
• Subjects: Scheduling -- learning effect -- unequal release dates -- total weighted tardiness -- genetic algorithm -- kangaroo algorithm; Operations research -- Periodicals; Electronic data processing -- Periodicals; Systems engineering -- Periodicals; Systems engineering; Electronic data processing; Periodicals; 003.05
• DOI: 10.1080/03155986.2021.1904538
• Languages: English
• ISSNs: 0315-5986

Abstract

Abstract: This paper concerns with the total weighted tardiness on a single machine scheduling problem with the concept of learning effect and unequal release dates. A mathematical model is proposed with binary variables and only small size problems can be solved efficiently due to its NP-hardness. Therefore, four heuristic methods are developed to solve real size applications including the size of 1000 jobs. Proposed heuristics are: genetic, genetic with solution combination, kangaroo and genetic-kangaroo hybrid algorithms. Results denote that developed heuristics are efficient for the considered problem. Research on this topic shows that no study exists on the total weighted tardiness problem with learning effect and unequal release dates simultaneously tackled in this paper.