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作者机构:Department of Mathematics and Systems Analysis Aalto University Espoo Finland
出 版 物:《arXiv》 (arXiv)
年 卷 期:2023年
核心收录:
主 题:Mixed integer linear programming
摘 要:In this paper, we propose novel mixed-integer linear programming (MIP) formulations to model decision problems posed as influence diagrams. We also present a novel heuristic that can be employed to warm start the MIP solver, as well as provide heuristic solutions to more computationally challenging problems. We provide computational results showcasing the superior performance of these improved formulations as well as the performance of the proposed heuristic. Lastly, we describe a novel case study showcasing decision programming as an alternative framework for modelling multi-stage stochastic dynamic programming problems. Copyright © 2023, The Authors. All rights reserved.