An effective hybrid goal programming approach for multi-objective straight assembly line balancing problem with stochastic parameters

A new multi-objective straight assembly line balancing problem is focused in this study. The problem happens in a stochastic environment where the task times and the task performing quality levels are distributed normally. The objectives like equipment purchasing cost, worker time dependent wage, an...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Operational research Jg. 20; H. 4; S. 1939 - 1976
Hauptverfasser: Mardani-Fard, Heydar Ali, Hadi-Vencheh, Abdollah, Mahmoodirad, Ali, Niroomand, Sadegh
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2020
Springer Nature B.V
Schlagworte:
ISSN:1109-2858, 1866-1505
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A new multi-objective straight assembly line balancing problem is focused in this study. The problem happens in a stochastic environment where the task times and the task performing quality levels are distributed normally. The objectives like equipment purchasing cost, worker time dependent wage, and average task performing quality of the assembly line are to be optimized simultaneously. A mixed integer non-linear formulation is proposed for the problem. Applying a chance-constrained modeling approach and some linearization techniques the model is converted to a crisp multi-objective mixed integer linear formulation. To tackle such problem, a hybrid fuzzy programming approach is proposed and combined with a typical goal programming method to construct a new hybrid goal programming approach. The computational experiments of the study results in a superior performance of the proposed approach comparing to the literature.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1109-2858
1866-1505
DOI:10.1007/s12351-018-0428-8