Multi-objective optimisation of risk and business strategy in real-world supply networks in the presence of uncertainty

Dobrila Petrovic, Magdalena Kalata

Research output: Contribution to journalArticle

Abstract

Selection of suppliers is very important for a strategic supply network (SN) design. This paper presents a novel multi-objective optimisation model for supplier selection and order allocation. In addition to a standard objective of total SN cost minimisation, two new objectives are considered: minimisation of suppliers’ risk and maximisation of achievement of a manufacturer business strategy. Uncertainty in supply lead times and non-conformance rates of delivered components causes uncertainty in the SN cost objective. These parameters are described using imprecise linguistic terms and modelled using fuzzy numbers. Risk classification of suppliers is carried out using imprecise knowledge which is modelled using fuzzy If-Then rules and embedded in the risk objective. Various experiments are carried out to analyse the trade-off between the considered objectives and the impact of SN network parameters on the suppliers’ selection and order allocation. The size of the problem that the model can handle is analysed also.
Original languageEnglish
Pages (from-to)(In-Press)
Number of pages16
JournalJournal of the Operational Research Society
Volume(In-Press)
Early online date24 Jan 2019
DOIs
Publication statusE-pub ahead of print - 24 Jan 2019

Fingerprint

Multiobjective optimization
Industry
Linguistics
Costs
Uncertainty
Supply network
Business strategy
Multi-objective optimization
Experiments
Suppliers
Supplier selection

Keywords

  • fuzzy sets
  • optimisation
  • risk
  • Supply network

ASJC Scopus subject areas

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

Cite this

Multi-objective optimisation of risk and business strategy in real-world supply networks in the presence of uncertainty. / Petrovic, Dobrila; Kalata, Magdalena.

In: Journal of the Operational Research Society, Vol. (In-Press), 24.01.2019, p. (In-Press).

Research output: Contribution to journalArticle

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