Transfer line balancing problem: A comprehensive review, classification, and research avenues

The Transfer Line Balancing Problem (TLBP) is characterized as the challenge of optimally distributing tasks across various workstations in an automated machining line to ensure its maximum efficiency. This problem holds pivotal importance for industries reliant on high-volume production, such as the automotive and aerospace sectors, where it directly influences the overall productivity and cost efficiency of the manufacturing process. TLBP has been studied for over two decades, and many problem variants and solution approaches have been devised to address real-world challenges. Despite the long history of the topic, no review study exists to shed light on its past, current, and future developments. This study conducted a systematic literature review on TLBP to identify and address the research gaps, focusing on classifying existing studies. A tuple notation classification framework has been introduced to organize TLBP research based on system configuration, problem characteristics, and optimization objectives. This framework offers a structured overview of the field, clarifying the current state of research and highlighting prospective research pathways. Consequently, this review study establishes itself as a foundational guide for academics and industry professionals interested in TLBP studies. • A systematic literature review on transfer line balancing problem (TLBP) is provided. • A tuple-notation classification is proposed to classify the literature. • Through descriptive analysis, trends in TLBP research are examined. • Research gaps are discerned, accompanied by proposed avenues for future studies.

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Publication Details

Journal
Computers & Industrial Engineering
Published
2025-01-29
DOI
https://doi.org/10.1016/j.cie.2025.110913
Citations
4
Primary Topic
Assembly Line Balancing Optimization
Type
article
Field-Weighted Citation Impact
4.97

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article

Transfer line balancing problem: A comprehensive review, classification, and research avenues

Alexandre B. Dolgui, Xavier Delorme, Pedram Beldar, Masood Fathi et al.
4 citations
Computers & Industrial Engineering
Assembly Line Balancing Optimization
4.97
article

Transfer line balancing problem: A comprehensive review, classification, and research avenues

Alexandre B. Dolgui, Xavier Delorme, Pedram Beldar, Masood Fathi, Amir Nourmohammadi, Olga Battaïa
article en
4 citations

Abstract

The Transfer Line Balancing Problem (TLBP) is characterized as the challenge of optimally distributing tasks across various workstations in an automated machining line to ensure its maximum efficiency. This problem holds pivotal importance for industries reliant on high-volume production, such as the automotive and aerospace sectors, where it directly influences the overall productivity and cost efficiency of the manufacturing process. TLBP has been studied for over two decades, and many problem variants and solution approaches have been devised to address real-world challenges. Despite the long history of the topic, no review study exists to shed light on its past, current, and future developments. This study conducted a systematic literature review on TLBP to identify and address the research gaps, focusing on classifying existing studies. A tuple notation classification framework has been introduced to organize TLBP research based on system configuration, problem characteristics, and optimization objectives. This framework offers a structured overview of the field, clarifying the current state of research and highlighting prospective research pathways. Consequently, this review study establishes itself as a foundational guide for academics and industry professionals interested in TLBP studies. • A systematic literature review on transfer line balancing problem (TLBP) is provided. • A tuple-notation classification is proposed to classify the literature. • Through descriptive analysis, trends in TLBP research are examined. • Research gaps are discerned, accompanied by proposed avenues for future studies.

Computers & Industrial EngineeringVol. 201
Uppsala University (SE), Centre National de la Recherche Scientifique (FR), University of Skövde (SE), Mines Saint-Étienne (FR), Laboratoire des Sciences du Numérique de Nantes (FR), IMT Atlantique (FR), Kedge Business School (FR)
Agence Nationale de la Recherche
Sustainable cities and communities
Openalex Percentile: Top 6%
Assembly Line Balancing Optimization
4.97
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