Multi-period, multi-echelon and spatially explicit features are embodied within the formulation to steer decisions and investments through a global approach.
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.
The work addresses a multi-product, multi-echelon and multi-period Mixed-Integer Linear Programming (MILP) problem in a closed-loop supply chain network design solved to global optimality using standard branch-and-bound techniques.
Concentrating on the problems of the product and network design for a multi-product, multi-echelon and multi-period CLSC, in this work a two-stage stochastic mixed integer linear model incorporating uncertainty on the quality and quantity of the return flows is proposed.
A fuzzy multi-objective, multi-echelon and multi-product mixed integer linear programming model with different importance and priorities are developed in this paper.
This study addresses a new multi-period multi-echelon and multi-transportation integrated petroleum supply chain model to obtain a global optimal solution.
The concerned agile supply chain network in this paper is a multi-echelon and direct acyclic network, which integrates the production, outsourcing, flexibility, discount, safety stock, shortage, and distribution activities.
In this paper, the location-routing problem with time window (LRPTW) and homogeneous fleet type and designing a multi-echelon, and capacitated reverse logistics network, are considered which may arise in many real-life situations in logistics management.
This paper addresses a new problem in designing and planning a multi-echelon and multi-product supply chain network over a multi-period horizon in which customer zones have price-sensitive demands.
