(166e) Study and Optimization of the Supply Chain of the Recollection and Harnessing of Used Cooking Oil in the City of Bogotá

Currently, waste disposal is a major challenge for most mega-populated cities worldwide. Particularly in underdeveloped and developing countries, the lack of regulations and law enforcement, together with a generalized unconscious behavior regarding waste management had generated a large variety of impacts. Among the different urban residues, used cooking oil (UCO) is a highly problematic waste that is generally disposed through the sewage system. As a consequence of this improper disposal, there is blockage of sewage pipes, which in turn generates flooding during rainy seasons, proliferation of vectors (rats, cockroaches, bacteria, etc.), and bad odors while decomposing. In some cases, the waste oil reaches surface or underground waters generating a major ecological impact.

All these problems have been increasingly experienced in the capital city of Colombia, Bogota. The city and its surrounding metropolitan area concentrate nearly 20% of the country’s population (~ 10 million), and it is expected to grow at 2.8% annually in the coming years. Then, the increasing population will boost impacts associated to UCOs mishandling. Nowadays the city expends nearly 6 to 8 million dollar per year on corrective sewage maintenance related to UCOs mismanagement.

In order to reduce UCO disposal problem, major cooking oil companies in Colombia have started responsible consumption programs to promote UCOs recollection and valorization. Currently, UCOs are collected to be used as feedstock for soaps and biodiesel production. However, as these are low-added value commodities, sustainability of the recollections and exploitation chain is challenging. Thus, all the constituent steps of the collection, treatment and transformation processes must be optimized to ensure sustainability. Particularly, supply chain optimization is a necessary task to accomplish during the sustainability assessment.

In this work, the analysis and optimization of a UCO recollection program, implemented in the city of Bogota by a major fat and oils, was accomplished. An analysis of available UCOs volumes, source locations, recollections frequencies and routes, and the corresponding impacts (e.g. fuel consumption) was carried out. Subsequently, the optimization of the supply chain was focused on maximizing recollection volumes while minimizing time, costs and the associated impacts (i.e. environmental). Thus, the supply chain was modelled using a Travelling Salesman Problem like formulation with combinatorial Genetic Algorithm as solution algorithm for the route optimization. The formulation is based on a graph where each collection location was represented by a node and the route is formed by changing the paths between them. Restrictions were incorporated to take into account shift times, truck capacities, and recollections times. The optimization problem was formulated and solved in Python.