TY - GEN
T1 - A framework for locating logistic facilities with multi-criteria decision analysis
AU - Montibeller, Gilberto
AU - Yoshizaki, Hugo
PY - 2011
Y1 - 2011
N2 - Locating logistic facilities, such as plants and distribution centres, in an optimal way, is a crucial decision for manufacturers, particularly those that are operating in large developing countries which are experiencing a process of fast economic change. Traditionally, such decisions have been supported by optimising network models, which search for the configuration with the minimum total cost. In practice, other intangible factors, which add or reduce value to a potential configuration, are also important in the location choice. We suggest in this paper an alternative way to analyse such problems, which combines the value from the topology of a network (such as total cost or resilience) with the value of its discrete nodes (such as specific benefits of a particular location). In this framework, the focus is on optimising the overall logistic value of the network. We conclude the paper by discussing how evolutionary multi-objective methods could be used for such analyses.
AB - Locating logistic facilities, such as plants and distribution centres, in an optimal way, is a crucial decision for manufacturers, particularly those that are operating in large developing countries which are experiencing a process of fast economic change. Traditionally, such decisions have been supported by optimising network models, which search for the configuration with the minimum total cost. In practice, other intangible factors, which add or reduce value to a potential configuration, are also important in the location choice. We suggest in this paper an alternative way to analyse such problems, which combines the value from the topology of a network (such as total cost or resilience) with the value of its discrete nodes (such as specific benefits of a particular location). In this framework, the focus is on optimising the overall logistic value of the network. We conclude the paper by discussing how evolutionary multi-objective methods could be used for such analyses.
U2 - 10.1007/978-3-642-19893-9_35
DO - 10.1007/978-3-642-19893-9_35
M3 - Conference Contribution (Conference Proceeding)
SN - 978-3-642-19892-2
T3 - Lecture Notes in Computer Science
SP - 505
EP - 519
BT - Proceedings of the 6th International Conference in Evolutionary Multi-Criterion Optimization
PB - Springer Berlin Heidelberg
ER -