Title: A mathematical model for collecting and distributing perishable products by considering costs minimisation and CO2 emissions

Authors: Rafael Tordecilla-Madera; Andrés Polo Roa; John Willmer Escobar; Nicolas Clavijo Buriticá

Addresses: Department of Industrial Engineering, Fundación Universitaria Agraria de Colombia (Uniagraria), Bogota 11001000, Bogotá, Distrito Capital, Colombia ' Department of Industrial Engineering, Fundación Universitaria Agraria de Colombia (Uniagraria), Bogota 11001000, Bogotá, Distrito Capital, Colombia ' Department of Accounting and Finance, Faculty of Business Management, Universidad del Valle, Cali 76001000, Valle del Cauca, Colombia ' Department of Civil and Industrial Engineering, Pontificia Universidad Javeriana Cali, Cali 76001000, Valle del Cauca, Colombia

Abstract: This paper considers the problem of allocating vehicles to collect and distribute fruit to producer associations in Colombia. In particular, the problem seeks to determine the optimal allocation of vehicles for fruit collection minimising both total transportation costs and CO2 emissions. This problem has multiple objectives, and the well-known ε-constraint method has been used as solution technique for the proposed mathematical models. The efficiency of the former methodology has been tested by using a case study involving the distribution of blackberry (Rubus glaucus) by an association of producers in Cundinamarca Department, Colombia. In particular, we considered 12 different scenarios related to supply levels, route outsourcing, and collection frequency. The results show the efficiency of the proposed methodology in solving vehicle allocation problems related to collection and distribution. The case study reveals that, in general, collecting fruit three days/week yields lower costs and fewer emissions than performing collections four days/week. Furthermore, increased supply leads to greater differences between costs and emissions.

Keywords: Andean blackberry; low-carbon emissions; mixed-integer programming; ε-constraint method; supply chain optimisation.

DOI: 10.1504/IJSOM.2018.094752

International Journal of Services and Operations Management, 2018 Vol.31 No.2, pp.207 - 234

Received: 01 Jul 2016
Accepted: 25 Nov 2016

Published online: 15 Sep 2018 *

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