A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines
Simge Yelkenci Kose () and
Ozcan Kilincci
Additional contact information
Simge Yelkenci Kose: Turkish Aerospace Industries
Ozcan Kilincci: Dokuz Eylul University
Journal of Intelligent Manufacturing, 2020, vol. 31, issue 1, No 4, 33-51
Abstract:
Abstract The buffer allocation problem is of particular interest for operations management since buffers have a considerable impact on capacity improvement in production systems. In this study, the buffer allocation is solved to optimize two conflicting objectives of maximizing the average system production rate and minimizing total buffer size. A hybrid evolutionary algorithm-based simulation optimization approach is proposed for the multi-objective buffer allocation problem (MOBAP) in open serial production lines. As a search methodology, the Pareto optimal set is derived by hybrid approach using elitist non-dominated sorting genetic algorithm (NSGA-II) and a special version of a multi-objective simulated annealing. As an evaluative tool, discrete event simulation modeling is used to estimate the performance measures for the production systems. To demonstrate the efficacy of the proposed hybrid approach, a comparative study is provided for the MOBAP in various serial line configurations. The comparative results show that the hybrid method has a considerable potential to minimize the total buffer space by appropriately allocating space to each buffer while maximizing average production rate.
Keywords: Buffer allocation problem; Multi-objective optimization; Hybrid meta-heuristics; Production lines (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1007/s10845-018-1435-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:31:y:2020:i:1:d:10.1007_s10845-018-1435-6
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845
DOI: 10.1007/s10845-018-1435-6
Access Statistics for this article
Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak
More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().