Supply–demand hub in industrial clusters: a stochastic approach. Issue 9 (2nd September 2018)

• Record Type: Journal Article
• Authors: Kayvanfar, Vahid; Moattar Husseini, S. M.; Karimi, B.; Sajadieh, Mohsen S.
• Is Part Of: Engineering optimization. Volume 50:Issue 9(2018)
• Page Start: 1561
• Page End: 1577
• Publication Date: 2018-09-02
• Subjects: Supply–demand hub -- accelerated Benders decomposition method -- industrial cluster (IC) -- small and medium-sized enterprises (SMEs) -- third party logistics (3PL) provider; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2017.1406930
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: The relationships between supply chain management and industrial clusters (groups of similar and interconnected companies in a particular field located in the same geographical area) have been imperfectly mathematically investigated so far, despite their intrinsic correlation. A supply–demand hub in industrial clusters (SDHIC) as a public provider of logistics services, managed by a third party logistics provider, is proposed to minimize total costs. The activities of companies within an industrial cluster are first modelled in terms of a two-stage stochastic programming model and then an acceleration technique for the Benders decomposition (BD) algorithm is proposed. To evaluate the effects of the accelerating method, four versions of BD are developed. To show the applicability of the proposed model, a case study including a sensitivity analysis of its main parameters is presented. Lastly, several managerial insights are offered.