[2] According to the introduced model the main differences between forward and reverse logistics can be identified: In case of a reverse logistics network the nodes represent the different kind of facilities such as the manufacturers, distribution centers, recovery centers, ware houses.
The two common way of designing reverse logistics network are the Mixed Integer Linear Programing (MILP) and Mixed Integer Non-Linear Programing (MINLP) methods, where the objective function, decision variables and constraint have to be defined This model is a two-level location problem with three type of facilities, integrated forward and reverse flow of goods.
It means that the used items are gathered from consumers, transported back to plants and after remanufacturing get into the logistics network of new products.
Moreover, the static approach can be partly eliminated by multi-period programming, as a result trade-off between investment and operational cost and long run effect can be analyzed.
The main objective is to maximize profit by determining the optimal number of facilities in order to: It is applicable for large size complex problems Main steps of the algorithm: The algorithm pursues local search and if it finds a local optimum it is prevented to get back formerly visited solution, which were recorded in the so-called tabu list[4]