Results show that, ceteris paribus, CLSC outperforms a forward supply chain, both in mono-echelon and multi-echelon structures and under both stationary and turbulent market demands.
Major technologies used for this study are; analytic hierarchy process (AHP), multi-attribute utility with multi-echelon structure and integrating the prioritized set of evaluated results.
In this paper, a multi period, multi product, multi echelon and capacitated supply chain problem for short lifetime products was solved using both exact method and metaheuristic algorithms.
The problem involves a multi-period, multi-product, multi-echelon supply chain.
Features, such as multi-echelon, multi-commodity, products structure, and manufacturing process, are taken into consideration as characteristics of the studied environment.
This research proposes a multi-period, multi-product, multi-echelon closed-loop supply chain network design model under uncertainty.
The model minimizes multi-echelon multi-product cost along the refineries, distribution centers, transportation modes and demand nodes.
This work addresses the design of chemical supply chains (SCs) with multi-product, multi-echelon distribution networks under demand uncertainty.
Multi-period, multi-echelon and spatially explicit features are embodied within the formulation to steer decisions and investments through a global approach.
The main objective of this study was to develop a multi-objective, multi-echelon, multi-product, and multi-period logistics network design model in a more holistic manner while also considering environmental issues.
This paper studies the network design for a multi-product, multi-echelon and multi-period closed-loop supply chain (CLSC) accounting for decisions on the manufacture of new products and remanufactured versions of the new products.
