Distributionally robust optimization under endogenous uncertainty with an application in retrofitting planning

Xuan Vinh Doan

European Journal of Operational Research, 2022, vol. 300, issue 1, 73-84

Abstract: Endogenous uncertainty concerns uncertainty which is dependent of decisions such as link failure in the retrofitting planning application. We propose a marginal-based distributionally robust optimization framework for integer stochastic optimization with decision-dependent discrete distributions that can be applied for the retrofitting planning application. We show that the resulting model can be formulated as a mixed-integer linear optimization problem. In order to solve the problem, we develop a constraint generation algorithm given the exponentially large number of constraints. Numerical results for the retrofitting planning application show that the proposed algorithm once tailored can solve the problem efficiently.

Keywords: Stochastic programming; Distributionally robust optimization; Endogenous uncertainty; Retrofitting planning (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:300:y:2022:i:1:p:73-84

DOI: 10.1016/j.ejor.2021.07.013

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