4.6 Article

An optimization approach for the design and planning of the oil palm supply chain in Colombia

Journal

COMPUTERS & CHEMICAL ENGINEERING
Volume 146, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2020.107208

Keywords

Oil palm industry; Mixed integer linear programming; Supply chain management; Biomass; Bio-based electricity

Funding

  1. Government of Magdalena
  2. General System of Regalias (SGR) doctorate Nacional Colombia [672]
  3. Universidad del Norte (Colombia)
  4. YKLOS research group of the National University of Tucuman (Argentina)

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This article presents a mathematical model for optimizing planning decisions in the Colombian oil palm supply chain, with the aim of maximizing the value of the entire supply chain by considering various products, warehouse types, transportation modes, and export options. The model has the advantage of optimizing the distribution of production units and maximizing the utilization of resources, making it an important tool in the field of biomass supply chain planning.
This article presents a mathematical model to optimize the planning decisions in the Colombian oil palm supply chain (SC). The optimization model consists of a mixed integer linear formulation, aiming at maximizing the expected net present value of the entire SC, including electricity supplied to the national grid by this activity. The model considers different products, types of warehouses, transportation modes, and export options, reflecting as far as possible the current situation of the oil palm industry in Colombia. It sets as free variables the location of the storage and production facilities, their expansion possibilities, and the flows of all feedstock and final products involved in the SC. The model constitutes a quantitative decision-making tool in the area of strategic design and optimal planning of biomass-based SCs. The optimal solution obtained by the model presents a more rational distribution of the production units in comparison with the current situation. (C) 2020 Elsevier Ltd. All rights reserved.

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