دانلود رایگان مقاله یک مدل موقعیت مکانی گیاه برای فعالیت های لجستیک معکوس

ABSTRACT

Product remanufacturing is one of the most profitable activities in reverse logistics. Running a business plan, in which companies take responsibility for the waste generated at their end-of-life products, involves making important strategic decisions. One of the challenges in planning the reverse flow of products is decide where installing the reprocessing facilities. This decision influences directly the transport variables costs and the facilities installation fixed costs. This paper proposes a model for the Capacitated Plant Location Problem in Reverse Logistics (CPL-RL), in which we assume that offered material in each collection center is aimed at a single facility for reprocessing. This restriction includes specific cases where there is no logistic availability in the network to send the collected material to different locations. The Mixed Integer Problem (MILP) is solved using an algorithm in two steps. In the first step, reduction tests are performed, which ones determine a priori which facilities are opened /closed. If all facilities are fixed opened or closed then the solution is optimal. Although not all facilities can have their status defined that way, the resultant problem has a less number of variables and it is solved using Benders method. The dataset was randomly generated and the results showed that the applied techniques are appropriate, achieving the optimal solution for all test problems.

7. CONCLUSIONS

In the present paper, the capacitated location problem in reverse logistics is analyzed. This problem is a MILP with two levels: supply points ( , reprocessing facilities ( ) and ? ∈ ?) ? ∈ ? demand points ( ). The objective is to identify the optimal sites to install reprocessing ? ∈ ? facilities to minimize the variable costs of transportation and management as well as the fixed costs of installing these facilities. To solve the problem, we propose a Benders’ decomposition algorithm and a combination of Benders’ method and tests for fixing variables in a single two-steps algorithm. A set of 60 instances was randomly generated, and the performance of both algorithms is evaluated using this set of problems. It became clear that the performance of the Tests+Benders algorithm is superior to Benders’ method in terms of computation time and effort. The difficulties imposed by the generated dataset are diversified and the efficiency of the proposed algorithm is demonstrated, considering that this method allows all of the testing problems to be solved, including those that could not be solved directly by the CPLEX solver and Benders’ algorithm without reduction tests. In addition to computational aspects, the present study has social relevance: it provides models and methods to help public, private and mixed organizations plan their reverse logistics networks. Any efforts in these areas, whether in the remanufacturing, recycling or reconditioning of products, prevent the generation of waste. Although some companies try to implement the reverse flow of products with the goal of complying with current legislation (Fleischmann et al., 2000), if the business plan is well executed, this segment can become a very lucrative activity for companies (Blackburn, 2004).