@article{García-Cáceres_2017, title={Strategic planning of biodiesel supply chain}, volume={22}, url={https://revistas.javeriana.edu.co/index.php/iyu/article/view/19030}, DOI={10.11144/Javeriana.iyu22-1.spbs}, abstractNote={<p><em><strong>Objective:</strong></em> A stochastic bi-objective Mixed Integer Problem (MIP) model of biodiesel supply chain networks is presented, ultimately intended to support strategic decisions of stakeholders. <em><strong>Materials and Methods:</strong></em> The bi-objective MIP model aims to minimize the total cost and environmental impact of five chain echelons, taking into consideration the following constraints: economies of scale, location of facilities, production capacity, raw material supply, product demand, bill of materials and mass balance. The solution procedure resorts to chance constraints, valid constraints and the ε-constraint method. <strong><em>Results and Discussion:</em></strong> The CPU times for the optimal solution of the problem instances show very good values. Computational experiments allowed assessing the performance of the solution procedure. <strong><em>Conclusion:</em> </strong>The current approach to the modeling of the biodiesel supply chain may serve as the basis of future similar works and associated solution procedures, thus facilitating decision-making at different supply chain stages. The approach fosters the development of new solution approaches such as adequate acceleration; heuristics and meta-heuristics; branch and cut methods;and Lagrangian, Benders and Danzing-Wolfe decompositions. These new approaches are intended to allow comparisons in terms of computational performance level, optimality gap, CPU time and memory usage.</p>}, number={1}, journal={Ingenieria y Universidad}, author={García-Cáceres, Rafael Guillermo}, year={2017}, month={Dec.}, pages={77–95} }