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Optimal integration of the facility location problem into the multi-project multi-supplier multi-resource Construction Supply Chain network design under the vendor managed inventory strategy

H. Golpîra

Published 2020 in Expert systems with applications

ABSTRACT

Abstract Using an expert system, this study is a pioneer in the formulation of an original Mixed Integer Linear Programming to integrate Vendor Managed Inventory strategy into the general multi-project multi-resource multi-supplier Construction Supply Chain (CSC) network design and facility location problems in a minimum cost. The framework is capable of dynamically scheduling resources in terms of timing and delivery as well as selecting appropriate suppliers and suitable candidate locations restricted to only authorized facilities in a capacitated network. Results show that there are different distributions for the different cost components in response to the different network sizes. Since changes in ratios of transportation cost and inventory holding cost to the total cost are mirroring each other, the total transportation and inventory costs in proportion to the total network's cost does not depend on the problem's size. In other point of view, when the network is large enough, changing its size results in a very little change in the cost components, hence better controlling the cost variability is achieved. Besides, increasing the number of projects may increase the total cost of the CSC with increasing rates, and the disparity between the number of projects and the number of suppliers increases the cost of the network, nonlinearly. Further, if the duration of the projects is given fixed, the greater the number of time periods for providing resources, the lower the transportation costs. Finally, the higher replenishment frequency results in the lower inventory cost and brings benefits for both sides of the CSC.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Expert systems with applications

  • Publication date

    Unknown publication date

  • Fields of study

    Business, Engineering, Computer Science

  • Identifiers
    DOI 10.1016/J.ESWA.2019.112841
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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