Optimization of natural resource management: Application to French copper cycle

Abstract

An innovative resource flow optimization model is proposed that aims at helping decision makers to choose the best resource management policies at national and international scales. This model has been developed and validated on French copper cycle, but can easily be extended to any country or metal. A mathematical formulation of all the in- and outflows of the resource, as well as stocks in the technosphere and waste management, including recycling, has been developed. The complexity of resource cycle led to the introduction of 47 decision variables and resulted in a Mixed-Integer Non-Linear Programming formulation. The resource cycle efficiency has been assessed through four indicators regarding costs, greenhouse gas emissions, energy consumption and resource losses. The NSGA II genetic algorithm methodology has been selected as an optimization strategy. Monobjective optimizations have firstly been conducted for each of the four criteria: the results showed that very different management strategies are needed depending on the targeted criteria. Multiobjective optimizations have thus been conducted coupled with the decision support tool TOPSIS to find an optimal compromise solution. As expected, the selected solution highlights the importance of developing a recycling channel for Waste from Electrical and Electronic Equipment in France.