TY - JOUR
T1 - Combining production and distribution in supply chains
T2 - The hybrid flow-shop vehicle routing problem
AU - Martins, Leandro do C.
AU - Gonzalez-Neira, Eliana M.
AU - Hatami, Sara
AU - Juan, Angel A.
AU - Montoya-Torres, Jairo R.
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/9
Y1 - 2021/9
N2 - Many supply chains are composed of producers, suppliers, carriers, and customers. These agents must be coordinated to reduce waste and lead times. Production and distribution are two essential phases in most supply chains. Hence, improving the coordination of these phases is critical. This paper studies a combined hybrid flow-shop and vehicle routing problem. The production phase is modeled as a hybrid flow-shop configuration. In the second phase, the produced jobs have to be delivered to a set of customers. The delivery is carried out in batches of products, using vehicles with a limited capacity. With the objective of minimizing the service time of the last customer, we propose a biased-randomized variable neighborhood descent algorithm. Different test factors, such as the use of alternative initial solutions, solution representations, and loading strategies, are considered and analyzed.
AB - Many supply chains are composed of producers, suppliers, carriers, and customers. These agents must be coordinated to reduce waste and lead times. Production and distribution are two essential phases in most supply chains. Hence, improving the coordination of these phases is critical. This paper studies a combined hybrid flow-shop and vehicle routing problem. The production phase is modeled as a hybrid flow-shop configuration. In the second phase, the produced jobs have to be delivered to a set of customers. The delivery is carried out in batches of products, using vehicles with a limited capacity. With the objective of minimizing the service time of the last customer, we propose a biased-randomized variable neighborhood descent algorithm. Different test factors, such as the use of alternative initial solutions, solution representations, and loading strategies, are considered and analyzed.
KW - Biased randomization
KW - Hybrid flow-shop problem
KW - Metaheuristics
KW - Vehicle routing problem
UR - http://www.scopus.com/inward/record.url?scp=85108893953&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2021.107486
DO - 10.1016/j.cie.2021.107486
M3 - Article
AN - SCOPUS:85108893953
SN - 0360-8352
VL - 159
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
M1 - 107486
ER -