A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines

The Assembly Line Part Feeding Problem (ALPFP) is a complex combinatorial optimisation problem concerned with the delivery of the required parts to the assembly workstations in the right quantities at the right time. Solving the ALPFP includes simultaneously solving two sub-problems, namely tour sch...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of production research Jg. 54; H. 3; S. 878 - 893
Hauptverfasser: Fathi, Masood, Rodríguez, Victoria, Fontes, Dalila B.M.M., Alvarez, Maria Jesus
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Taylor & Francis 01.02.2016
Taylor & Francis LLC
Schlagworte:
Algorithms
Assembly
assembly line
Assembly lines
Combinatorial analysis
Feeding
Linear programming
Mutations
Optimization
part feeding problem
particle swarm optimisation
Scheduling
tour scheduling
tow-train loading
ISSN:0020-7543, 1366-588X
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The Assembly Line Part Feeding Problem (ALPFP) is a complex combinatorial optimisation problem concerned with the delivery of the required parts to the assembly workstations in the right quantities at the right time. Solving the ALPFP includes simultaneously solving two sub-problems, namely tour scheduling and tow-train loading. In this article, we first define the problem and formulate it as a multi-objective mixed-integer linear programming model. Then, we carry out a complexity analysis, proving the ALPFP to be NP-complete. A modified particle swarm optimisation (MPSO) algorithm incorporating mutation as part of the position updating scheme is subsequently proposed. The MPSO is capable of finding very good solutions with small time requirements. Computational results are reported, demonstrating the efficiency and effectiveness of the proposed MPSO.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2015.1090032