New heuristics for the 2-stage assembly scheduling problem with total earliness and tardiness minimisation: A computational evaluation

Traditionally, scheduling literature has focused mainly on solving problems related to processing jobs with non-assembly operations. Despite the growing interest in the assembly literature in recent years, knowledge of the problem is still in its early stages in many aspects. In this regard, we are not aware of any previous contributions that address the assembly scheduling problem with just-in-time objectives. To fill this gap, this paper studies the 2-stage assembly scheduling problem minimising the sum of total earliness and total tardiness. We first analyse the relationship between the decision problem and the generation of the due dates of the jobs, and identify the equivalences with different related decision problems depending on the instances. The properties and conclusions obtained in the analysis are applied to design two constructive heuristics and a composite heuristic. To evaluate our proposals, different heuristics from the state-of-the-art of related scheduling problems are adapted, and a computational evaluation is carried out. The excellent behaviour of the proposed algorithms is demonstrated by an extensive computational evaluation. • Scheduling in a 2-stage assembly layout is addressed. • The total earliness and tardiness minimisation as objective is studied. • The decision problem depending on the generation of the due dates is analysed. • Two constructive heuristics and one composite heuristic are proposed. • The heuristics outperform existing methods for the problem.

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Publication Details

Journal
Computers & Operations Research
Published
2024-08-29
DOI
https://doi.org/10.1016/j.cor.2024.106824
Citations
3
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
1.05

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article

New heuristics for the 2-stage assembly scheduling problem with total earliness and tardiness minimisation: A computational evaluation

Jorge M. S. Valente, Carla Talens, Victor Fernández-Viagas
3 citations
Computers & Operations Research
Scheduling and Optimization Algorithms
1.05
article

New heuristics for the 2-stage assembly scheduling problem with total earliness and tardiness minimisation: A computational evaluation

Jorge M. S. Valente, Carla Talens, Victor Fernández-Viagas
article en
3 citations

Abstract

Traditionally, scheduling literature has focused mainly on solving problems related to processing jobs with non-assembly operations. Despite the growing interest in the assembly literature in recent years, knowledge of the problem is still in its early stages in many aspects. In this regard, we are not aware of any previous contributions that address the assembly scheduling problem with just-in-time objectives. To fill this gap, this paper studies the 2-stage assembly scheduling problem minimising the sum of total earliness and total tardiness. We first analyse the relationship between the decision problem and the generation of the due dates of the jobs, and identify the equivalences with different related decision problems depending on the instances. The properties and conclusions obtained in the analysis are applied to design two constructive heuristics and a composite heuristic. To evaluate our proposals, different heuristics from the state-of-the-art of related scheduling problems are adapted, and a computational evaluation is carried out. The excellent behaviour of the proposed algorithms is demonstrated by an extensive computational evaluation. • Scheduling in a 2-stage assembly layout is addressed. • The total earliness and tardiness minimisation as objective is studied. • The decision problem depending on the generation of the due dates is analysed. • Two constructive heuristics and one composite heuristic are proposed. • The heuristics outperform existing methods for the problem.

Computers & Operations ResearchVol. 172
Universidade do Porto (PT), Hospital Universitario Virgen Macarena (ES), Instituto de Biomedicina de Sevilla (ES), INESC TEC (PT), Universidad de Sevilla (ES)
Ministerio de Ciencia, Innovación y Universidades, European Commission, Ministerio de Ciencia e Innovación, Instituto de Salud Carlos III
Climate action
Openalex Percentile: Top 20%
Scheduling and Optimization Algorithms
1.05
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