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Minimization of total completion time on a batch processing machine with arbitrary release dates: an effectual teaching–learning based optimization approach
Department of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.ORCID iD: 0000-0003-2300-7929
Industrial Management, School of Engineering, University of Seville, Camino de los Descubrimientos, Seville, Spain.
National Center for Ports and Shipping, Australian Maritime College, University of Tasmania, Australia.
2019 (English)In: Production Engineering, ISSN 0944-6524, E-ISSN 1863-7353, Vol. 13, no 5, p. 557-566Article in journal (Refereed) Published
Abstract [en]

In this research study, a single machine batch-processing problem with release dates to minimize the total completion times of jobs is considered. The machine is able to process at most a certain number of jobs at the same time and the total size of the jobs allocated to a batch cannot exceed the machine capacity. Since the research problem has been shown to be NP-hard, an efective Teaching–Learning Based Optimization (TLBO) is proposed. A constructive heuristic approach is developed to generate initial feasible solutions for the TLBO. In order to enhance the efciency of the proposed TLBO, a Tabu Search (TS) with three diferent neighborhood generation mechanisms is incorporated into the teaching phase and learner phase separately. To validate the outcomes of the proposed TLBO, we carry out an experimental study and compare its outcomes with the best-known results obtained by several meta-heuristic methods on a set of benchmark instances derived from the literature. The computational results show that the proposed TLBO with the incorporation of TS in its learning phase is able to come up with very good quality solutions.

Place, publisher, year, edition, pages
Springer, 2019. Vol. 13, no 5, p. 557-566
Keywords [en]
Total completion times minimization, Batch processing, Single machine scheduling, Teaching–Learning Based Optimization, Heuristic approach
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:his:diva-23592DOI: 10.1007/s11740-019-00906-2ISI: 000484614500005Scopus ID: 2-s2.0-85067043551OAI: oai:DiVA.org:his-23592DiVA, id: diva2:1837913
Available from: 2024-02-15 Created: 2024-02-15 Last updated: 2024-02-15Bibliographically approved

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Beldar, Pedram

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