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首页> 外文期刊>International journal of metaheuristics >A multi-objective dynamic programming-based metaheuristic to solve a bi-objective unit commitment problem using a multi-objective decoder
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A multi-objective dynamic programming-based metaheuristic to solve a bi-objective unit commitment problem using a multi-objective decoder

机译：基于多目标动态规划的元启发式算法，使用多目标解码器解决双目标单元承诺问题

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摘要

The unit commitment problem (UCP) is a heavily constrained scheduling problem, where the on/off scheduling and production amounts of heterogeneous power production units have to be determined for a discrete time horizon. Due to environmental concerns, the traditional UCP to solely minimise the production cost is no longer adequate, and a second objective, to minimise the gas emissions has to be added to properly model reality. In this paper, we propose an efficient metaheuristic to solve this multi-objective version of the UCP. The proposed method, MO-DYNAMOP, is a generalisation of DYNAMOP (DYNAmic programming-based Metaheuristic for Optimisation Problems), a state-of-the-art hybrid optimiser which was successfully applied to the single-objective unit commitment problem. The main difficulty in extending DYNAMOP to the multi-objective UCP is that it uses an indirect representation of solution that gives the on/off scheduling of each unit. The real production amounts are computed by an exact sub-optimiser which minimises the production cost assuming that the on/off scheduling is fixed. Since the sub-optimiser now has to solve a multi-objective problem, each on/off scheduling induces an entire Pareto optimal set of solutions. We handle this complication by assigning an approximation of the corresponding set to each on/off scheduling solution. A comparison study with methods previously proposed in the literature indicates that MO-DYNAMOP performs considerably better on many benchmark instances.
机译：单元承诺问题（UCP）是一个严重受限的调度问题，其中必须为离散时间范围确定异构发电单元的开/关调度和生产量。由于环境方面的考虑，仅将生产成本最小化的传统UCP不再足够，而必须添加第二个目标以最小化气体排放以正确地模拟现实。在本文中，我们提出了一种有效的元启发式方法来解决UCP的这一多目标版本。提出的方法MO-DYNAMOP是DYNAMOP（基于DYNAmic编程的优化问题元启发式算法）的推广，该模型是一种最新的混合优化器，已成功应用于单目标单元承诺问题。将DYNAMOP扩展到多目标UCP的主要困难在于，它使用解决方案的间接表示形式来给出每个单元的开/关调度。实际生产量由精确的次优化器计算，假设开/关计划是固定的，该子优化器可最大程度地降低生产成本。由于次优化器现在必须解决多目标问题，因此每个开/关调度都可以得出整个帕累托最优解集。我们通过为每个开/关调度解决方案分配对应集合的近似值来处理这种复杂情况。与先前文献中提出的方法进行的比较研究表明，MO-DYNAMOP在许多基准实例上的性能要好得多。

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