Investigating the multi-objective optimisation problem of supplier selection using the new COTOP hybrid method
Elham Shadkam
International Journal of Business Performance and Supply Chain Modelling, 2023, vol. 14, issue 1, 79-105
Abstract:
In recent years, selecting the best supplier in the supply chain problem has become a strategically important issue. The nature of this problem is usually complex and there are conflicting objectives. Selecting the best supplier will significantly reduce the cost of purchasing materials and the delivery time. It also increases the level of competitiveness of organisations. The purpose of this paper is to present a new approach to solve multi-objective optimisation problems. The proposed method in this paper has been used to solve the evaluation and selection of the appropriate supplier. The proposed hybrid method is a combination of the cuckoo optimisation algorithm (COA) and the TOPSIS method and is therefore called COTOP. The speed and accuracy of the results from the implementation of the proposed COTOP method on the supplier selection problem show the efficiency of the algorithm in solving multi-objective problems, and this method can well identify the Pareto frontier of the problem. Due to the use of the cuckoo optimisation algorithm, the proposed COTOP method can be used in large-scale problems, and due to the use of the TOPSIS method, there is no concern in terms of the number of objective functions.
Keywords: supplier selection; supply chain; TOPSIS; cuckoo optimisation algorithm; hybrid method. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=130468 (text/html)
Access to full text is restricted to subscribers.
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:ids:ijbpsc:v:14:y:2023:i:1:p:79-105
Access Statistics for this article
More articles in International Journal of Business Performance and Supply Chain Modelling from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().