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Restriction techniques for the unit-commitment problem with total procurement costs

机译：具有总采购成本的单位承诺问题的限制技术

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Many discrete optimization problems may be solved much easier, if the solution space can be restricted in a convenient way. For a given specific problem, the restriction techniques can be helpful if an available optimization solver, perceived as a black box, is capable of solving quickly only reduced subproblems of a limited size. For the family of hard unit-commitment problems we investigate a hierarchical search algorithm, which is based on decomposition of the problem into two subproblems. The upper-level subproblem is a relatively small decision "kernel" of the problem that can be solved approximately by a search algorithm. We define an appropriate restricted decision space for this subproblem. The lower-level subproblem is an appropriate restriction of the original problem that can be solved efficiently by a dedicated solver. Our approach was analyzed on a set of historical data from the Polish electrical balancing market and the best known solutions were improved by the average of about 2-5%.
机译：如果可以方便地限制解决方案空间，则可以轻松解决许多离散的优化问题。对于给定的特定问题，如果可用的最佳化求解器（被视为黑匣子）仅能够快速解决有限大小的简化子问题，那么限制技术可能会有所帮助。对于硬单位承诺问题，我们研究了一种分层搜索算法，该算法基于将问题分解为两个子问题的能力。上层子问题是问题的相对较小的决策“内核”，可以通过搜索算法大致解决。我们为此子问题定义了一个适当的受限决策空间。较低级别的子问题是对原始问题的适当限制，可以通过专用求解器有效地解决该问题。我们根据波兰电气平衡市场的一组历史数据对我们的方法进行了分析，最著名的解决方案平均提高了约2％至5％。

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