TY - JOUR
T1 - A closed-loop supply chain management problem
T2 - Reformulation and piecewise linearization
AU - Al-Salem, Mohammed
AU - Diabat, Ali
AU - Dalalah, Doraid
AU - Alrefaei, Mahmoud
N1 - Publisher Copyright:
© 2016 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
PY - 2016/7/1
Y1 - 2016/7/1
N2 - Recent environmental considerations as well as advancements in the field of logistics have promoted the integration of the forward and reverse supply chains, in order to increase operational efficiency and support sustainable operations. In light of this, we formulate a mixed integer non-linear program (MINLP) that describes both the forward and reverse flow of a single type of product, through a set of warehouses whose location is determined based on whether they serve as forward, reverse or joint warehouses dealing with products from both directions. The objective of the model is to minimize the total costs, which include fixed location, fixed ordering, inventory holding, transportation as well as re-processing costs, the latter referring to returned products. In order to overcome the non-linearity of the formulation, the respective constraints are linearized, while for the non-linear terms of the objective function a piecewise linearization is proposed. The computational analysis focuses on comparing the results obtained by solving the MINLP in commercial software with the results obtained from implementing the linearization for a different number of adopted segments for the piecewise linearization. In addition, both integrated approaches are compared to the sequential approach, according to which the location, ordering and transportation problems are initially solved, producing an output that is subsequently used as an input to solve the inventory problem. Results demonstrate the benefits of integration as well as the cost savings that can be achieved due to the closed loop consideration of the supply chain. A discussion of these results produces useful insights for supply chain operators.
AB - Recent environmental considerations as well as advancements in the field of logistics have promoted the integration of the forward and reverse supply chains, in order to increase operational efficiency and support sustainable operations. In light of this, we formulate a mixed integer non-linear program (MINLP) that describes both the forward and reverse flow of a single type of product, through a set of warehouses whose location is determined based on whether they serve as forward, reverse or joint warehouses dealing with products from both directions. The objective of the model is to minimize the total costs, which include fixed location, fixed ordering, inventory holding, transportation as well as re-processing costs, the latter referring to returned products. In order to overcome the non-linearity of the formulation, the respective constraints are linearized, while for the non-linear terms of the objective function a piecewise linearization is proposed. The computational analysis focuses on comparing the results obtained by solving the MINLP in commercial software with the results obtained from implementing the linearization for a different number of adopted segments for the piecewise linearization. In addition, both integrated approaches are compared to the sequential approach, according to which the location, ordering and transportation problems are initially solved, producing an output that is subsequently used as an input to solve the inventory problem. Results demonstrate the benefits of integration as well as the cost savings that can be achieved due to the closed loop consideration of the supply chain. A discussion of these results produces useful insights for supply chain operators.
KW - Closed-loop supply chains
KW - Inventory management
KW - Reverse logistics
KW - Warehouse location
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U2 - 10.1016/j.jmsy.2016.04.001
DO - 10.1016/j.jmsy.2016.04.001
M3 - Article
AN - SCOPUS:84966267395
SN - 0278-6125
VL - 40
SP - 1
EP - 8
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
ER -