Robust Logistics Network Modeling and Design against Uncertainties

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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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