TY - JOUR
T1 - Designing e-commerce supply chains
T2 - a stochastic facility–location approach
AU - Calvet, Laura
AU - Pagès-Bernaus, Adela
AU - Ramalhinho, Helena
AU - Juan, Angel A.
PY - 2019/3
Y1 - 2019/3
N2 - e-Commerce activity has been increasing during recent years, and this trend is expected to continue in the near future. e-Commerce practices are subject to uncertainty conditions and high variability in customers’ demands. Considering these characteristics, we propose two facility–location models that represent alternative distribution policies in e-commerce (one based on outsourcing and another based on in-house distribution). These models take into account stochastic demands as well as more than one regular supplier per customer. Two methodologies are then introduced to solve these stochastic versions of the well-known capacitated facility–location problem. The first is a two-stage stochastic-programming approach that uses an exact solver. However, we show that this approach is not appropriate for tackle large-scale instances due to the computational effort required. Accordingly, we also introduce a “simheuristic” approach that is able to deal with large-scale instances in short computing times. An extensive set of benchmark instances contribute to illustrate the efficiency of our approach, as well as its potential utility in modern e-commerce practices.
AB - e-Commerce activity has been increasing during recent years, and this trend is expected to continue in the near future. e-Commerce practices are subject to uncertainty conditions and high variability in customers’ demands. Considering these characteristics, we propose two facility–location models that represent alternative distribution policies in e-commerce (one based on outsourcing and another based on in-house distribution). These models take into account stochastic demands as well as more than one regular supplier per customer. Two methodologies are then introduced to solve these stochastic versions of the well-known capacitated facility–location problem. The first is a two-stage stochastic-programming approach that uses an exact solver. However, we show that this approach is not appropriate for tackle large-scale instances due to the computational effort required. Accordingly, we also introduce a “simheuristic” approach that is able to deal with large-scale instances in short computing times. An extensive set of benchmark instances contribute to illustrate the efficiency of our approach, as well as its potential utility in modern e-commerce practices.
KW - capacitated facility–location problem
KW - e-commerce
KW - simheuristics
KW - stochastic combinatorial optimization
KW - stochastic programming
KW - supply-chain management
UR - http://www.scopus.com/inward/record.url?scp=85021722356&partnerID=8YFLogxK
UR - http://dialnet.unirioja.es/servlet/articulo?codigo=7373869
U2 - 10.1111/itor.12433
DO - 10.1111/itor.12433
M3 - Article
AN - SCOPUS:85021722356
SN - 0969-6016
VL - 26
SP - 507
EP - 528
JO - International Transactions in Operational Research
JF - International Transactions in Operational Research
IS - 2
ER -