Optimizing a Biobjective Production-Distribution Planning Problem Using a GRASP

Author:

Casas-Ramírez Martha-Selene1ORCID,Camacho-Vallejo José-Fernando2ORCID,González-Ramírez Rosa G.3,Marmolejo-Saucedo José-Antonio4,Velarde-Cantú José-Manuel5

Affiliation:

1. Departamento de Actuaría, Física y Matemáticas, Universidad de las Américas Puebla, Santa Catarina Mártir s/n, 72810 San Andrés Cholula, PUE, Mexico

2. Facultad de Ciencias Físico-Matemáticas, Universidad Autónoma de Nuevo León, Av. Universidad s/n, 66450 San Nicolás de los Garza, NL, Mexico

3. Faculty of Engineering and Applied Sciences, Universidad de los Andes Chile, Monseñor Álvaro Portillo 12455, Las Condes, Santiago, Chile

4. Facultad de Ingeniería, Universidad Panamericana, Augusto Rodin 498, 03920 Ciudad de México, Mexico

5. Instituto Tecnológico de Sonora Unidad Navojoa, Ramón Corona S/N, Esq. con Aguascalientes, Col. ITSON, Navojoa, SON, Mexico

Abstract

This paper addresses a biobjective production-distribution planning problem. The problem is formulated as a mixed integer programming problem with two objectives. The objectives are to minimize the total costs and to balance the total workload of the supply chain, which consist of plants and depots, considering that it represents a company vertically integrated. In order to solve the model, we propose an adapted biobjective GRASP to obtain an approximation of the Pareto front. To evaluate the performance of the proposed algorithm, numerical experimentations are conducted over a set of instances used for similar problems. Results indicate that the proposed GRASP obtains a relatively small number of nondominated solutions for each tested instance in very short computational time. The approximated Pareto fronts are discontinuous and nonconvex. Moreover, the solutions clearly show the compromise between both objective functions.

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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