文章基本信息

标题：The Similarity Index to Decompose Two-Stage Stochastic Scheduling Problems
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作者：Daniel Montes ; José Luis Pitarch ; Cesar de Prada 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：7
页码：821-826
DOI：10.1016/j.ifacol.2022.07.546
语种：English
出版社：Elsevier
摘要：AbstractTwo-stage stochastic scheduling problems often involve a large number of continuous and discrete variables, so fnding solutions in short time periods is challenging and computationally expensive. However, for online or closed-loop scheduling implementations, optimal or near-optimal solutions are required in real-time. We propose a decomposition method based on the so-called Similarity Index(SI).An iterative procedure is set up so that each sub-problem (corresponding to a scenario) is solved independently, aiming to optimize the original cost function while maximizing the similarity of the frst-stage variables among the scenarios solutions. TheSIis incorporated into each subproblem cost function, multiplied by a penalty parameter that is updated in each iteration until reaching complete similarity in the frst-stage variables among all subproblems. The method is applied to schedule production and maintenance tasks in an evaporation network. The tests show that signifcant benefts are expected in terms of computational demands as the number of scenarios increases.
关键词：KeywordsDecompositionOnline SchedulingUncertaintyMixed-Integer Optimization