A fuzzy multi-objective programming approach for determination of resilient supply portfolio under supply failure risks

The main contribution of this paper is to develop a new decision tool that interprets strategies for determination of resilient supply portfolio under supply failure risks. The strategic decisions include the allocation of emergency capacities to be pre-positioned at backup suppliers, the output of...

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Vydáno v:Journal of purchasing and supply management Ročník 23; číslo 3; s. 211 - 220
Hlavní autor: Lee, Shyh-hwang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.06.2017
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ISSN:1478-4092, 1873-6505
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Shrnutí:The main contribution of this paper is to develop a new decision tool that interprets strategies for determination of resilient supply portfolio under supply failure risks. The strategic decisions include the allocation of emergency capacities to be pre-positioned at backup suppliers, the output of which can be increased in the event of mitigating a shortage caused by another supplier's failure. The model contains three objective functions – minimising the total cost, minimising the net rejected items and minimising the net late deliveries – while satisfying capacity and minimum order quantity requirement constraints. A weighted additive fuzzy multi-objective model is proposed to simultaneously consider the imprecision of information and the relative importance of objectives for determining the allocation of order quantity and emergency capacity to each supplier. The application of the proposed model is illustrated using an example case of global supply chains with different supplier characteristics. •A new model of resilient supply portfolio is presented for decreasing supply risks.•A weighted additive fuzzy multi-objective programming is used to model the problem.•An optimal allocation of pre-positioned emergency capacities can be obtained.•The model is coded in MATLAB language to facilitate the search for the best solution.•The fortification model is illustrated using an example case of global supply chain.
ISSN:1478-4092
1873-6505
DOI:10.1016/j.pursup.2017.01.003