Location-Routing for Distribution Centers
Read this article. One objective of this paper is to determine distribution center locations. Compare and contrast the two cases presented.
Conclusions
As a new branch of location problems,
location-routing problem is still under development by various
researchers. Present paper considered a location-routing problem on
multimodal network. This paper aims to model and solve two problems at
the same time. First problem is to select multimodal routes from
supplier to potential DCs along with locating multimodal terminals.
Second problem is DC location with routing tours from located DCs to
retailers. An integer linear programming proposed and a genetic
algorithm developed to capture the problem structure. To validate
mathematical model, analyze sensitivity and demonstrate algorithm
performance, two small and large size numerical instances generated
based on previous papers, and different cost scenarios applied to these
instances. Scenarios were different in vehicle capacity, transportation
modes' costs, and mode changing cost. According to the results, for
different scenarios, different multimodal routes selected. Changing mode
change cost affects on establishing multimodal terminals. High mode
changing cost caused products to be transported on just one
transportation mode; decreasing the cost, however, led to changes in
modes, requiring multimodal terminals to be established. Changing
vehicle capacity cause a change in number of established DCs and
retailers orders on delivery tours. Also, by changing transportation
cost on multimodal network, model makes a trade-off between distance and
transportation cost and selects a multimodal route with lowest cost. In
large numerical instance, due to high complexity of the model, GAMS
software failed to find an optimum solution within a reasonable time. In
this case, genetic algorithm run under different scenarios and ended up
returning solutions equal to or better than GAMS results, revealing
good performance of the algorithm.
For future researches, first
suggestion is to develop other solving algorithms including exact
algorithms and comparing results. Other developments to LRP can be other
suggestion for future research; mathematical model can be further
developed considering uncertainties within data and dynamic programming
issues, for example. Applying model for real cases and reporting real
results can be another validation for model.