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A properly designed supply chain system is essential for competitive performance.
A well designed supply chain network provides a proper platform for efficient and effective supply chain management.
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This research focuses on designing supply chain systems where a large number of discrete configurations exist.
We consider a detailed mathematical formulation for the problem of designing supply chain networks comprising multiproduct production facilities with shared production resources, warehouses, distribution centers and customer zones and operating under time varying demand uncertainty.
The aim of this study is to design supply chain network for biomass to energy conversion systems for the regions having high potential of animal wastes and energy crops production and to reveal economical and environmental benefits from these systems.
The results of this theoretical study show that some of the indicators can be effectively used for identifying better configuration variant having feasible influence on organization performance while designing supply chain network.
Experimental results reveal that the proposed algorithm is rather computational effectiveness, and the pooling strategy that considers both vehicles and inventory transfers is a worthy option in designing supply chain operations.
This new concept helps top managers decide well in designing supply chains and establishing plants and warehouses.
This study develops a mixed integer nonlinear programming (MINLP) model to design supply chains.
This paper addresses the problem of designing supply chains that are resilient to natural or human-induced extreme events.
This paper describes a typology for designing supply chains that work in harmony to design, produce, and deliver products with different characteristics and customer expectations.
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