Affiliations: Leiden Institute of Advanced Computer Science, Leiden University, 2333 CA Leiden, the Netherlands
Correspondence:
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Corresponding author: Joost Kok, Leiden University, Niels Bohrweg 1, 2333 CA Leiden, the Netherlands. E-mail:[email protected]
Abstract: This article studies a tri-objective formulation of the
inventory routing problem, extending the recently studied bi-objective
formulation. As compared to distance cost and inventory cost, which were
discussed in previous work, it also considers stockout cost as a third
objective. Demand is modeled as a Poisson random variable. State-of-the-art
evolutionary multi-objective optimization algorithms and a new method based
on swarm intelligence are used to compute approximation of the 3-D Pareto
front. A benchmark previously used in bi-objective inventory routing is
extended by incorporating a stochastic demand model with an expected value
that equals the average demand of the original benchmark. The results
provide insights into the shape of the optimal trade-off surface. Based on
this the dependences between different objectives are clarified and
discussed. Moreover, the performances of the four different algorithmic
methods are compared and due to the consistency in the results, it can be
concluded that a near optimal approximation to the Pareto front can be found
for problems of practically relevant size.
