TY - JOUR
T1 - Optimizing a Biobjective Production-Distribution Planning Problem Using a GRASP
AU - Casas-Ramírez, Martha Selene
AU - Camacho-Vallejo, José Fernando
AU - González-Ramírez, Rosa G.
AU - Marmolejo-Saucedo, José Antonio
AU - Velarde-Cantú, José Manuel
N1 - Funding Information:
The research of the first two authors has been partially supported by the Mexican National Council for Science and Technology (CONACYT) through Grant SEPCONACYTCB-2014-01-240814. Also, the second author acknowledges the program of Professional Development of Professors with Grant PRODEP/511-6/17/7425 for research stays during his sabbatical year.
Publisher Copyright:
© 2018 Martha-Selene Casas-Ramírez et al.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Pareto principle
KW - Supply chains
UR - http://www.scopus.com/inward/record.url?scp=85113186438&partnerID=8YFLogxK
U2 - 10.1155/2018/3418580
DO - 10.1155/2018/3418580
M3 - Article
AN - SCOPUS:85113186438
SN - 1076-2787
VL - 2018
JO - Complexity
JF - Complexity
M1 - 3418580
ER -