Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling

Ullah, Wasif and Mohd Fadzil Faisae, Ab Rashid and Muhammad Ammar, Nik Mu’tasim (2025) Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling. Expert Systems with Applications, 273 (126955). pp. 1-15. ISSN 0957-4174. (In Press / Online First) (In Press / Online First)

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Abstract

Production scheduling is a strategic process that organizes the execution of jobs on available resources to optimize specific objectives. One significant scheduling challenge is the Cost-based Hybrid Flow Shop (CHFS) problem, which involves optimizing job scheduling across multiple stages to minimize scheduling-related costs. However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. Unlike previous studies that focus on isolated cost factors, this research formulated an integrated mathematical model for CHF holistically capturing labor, energy consumption, maintenance, and late penalty costs. The GTLBO algorithm incorporates a unique hybrid initialization strategy, generating 10 % of the initial population using a Greedy algorithm to enhance exploration efficiency. The performance of GTLBO was evaluated through computational experiments involving 12 test instances, with comparative algorithms included for analysis. Results from the Wilcoxon rank-sum test indicated a significant difference between the outputs of GTLBO and other algorithms, with GTLBO outperforming the comparative algorithms in 75 % of the test instances. Additionally, the case study validation showed that GTLBO can reduce costs by 0.23 % to 4.31 % compared to other algorithms. This research offers valuable insights for manufacturers seeking to optimize CHFS scheduling to reduce production expenses.

Item Type:	Article
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Cost optimization; Hybrid flow shop scheduling; Teaching learning-based optimization algorithm
Subjects:	T Technology > TJ Mechanical engineering and machinery
Faculty/Division:	Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology Faculty of Mechanical and Automotive Engineering Technology
Depositing User:	Mrs Norsaini Abdul Samat
Date Deposited:	03 Mar 2025 07:37
Last Modified:	03 Mar 2025 07:37
URI:	http://umpir.ump.edu.my/id/eprint/43975
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