Robust Logistics Network Modeling and Design against Uncertainties

Abstract

In design of logistics networks, it is inevitable to consider various forward factors that will often change from their reference values. With this point of view, this study formulates a global logistics network design problem under uncertainties and present a solution method in terms of the stochastic programming known as recourse model. To reduce the effort to solve the resulting problem, a scenario-base approach is adopted instead of considering infinite realizations of uncertain parameters and sample average approximation. Furthermore, we present a method to support decision-making on robust design under noisy environment in terms of the knowledge from multi-objective optimization. Numerical experiments revealed validity of the proposed method through comparison with the reference results.

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