Dynamic Multi-objective Optimization and Decision-Making Using Modified NSGA-II: A Case Study on Hydro-thermal Power Scheduling
Dynamic Multi-objective Optimization and Decision-Making Using Modified NSGA-II: A Case Study on Hydro-thermal Power Scheduling
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DOI：
10.1007/978-3-540-70928-2_60
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发表时间：
2007-03
期刊：
影响因子：
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通讯作者：
K. Deb;Udaya Bhaskara;Rao N;S. Karthik
中科院分区：
文献类型：
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作者：
K. Deb;Udaya Bhaskara;Rao N;S. Karthik
大多数现实世界的优化问题都涉及目标、约束和参数，这些都是随时间不断变化的。将此类问题视为平稳优化问题需要先验地了解变化模式，即使如此，该过程的计算成本也很高。尽管使用进化算法的动态考虑已经用于单目标优化问题，但对制定和解决动态多目标优化问题的兴趣不温不热。在本文中，我们修改了常用的NSGA-II过程来跟踪新的帕累托最优前沿，一旦问题发生变化。详细介绍了几种随机解和几种突变解的引入。在一个测试问题和一个实际的水火发电调度优化问题上对这些方法进行了测试和比较。该系统的研究能够找到两个动态EMO程序的问题允许的最小变化频率，以在线充分跟踪帕累托最优边界。基于这些结果，本文还提出了一种自动决策程序，用于在线求解动态单一最优解。
Most real-world optimization problems involve objectives, constraints, and parameters which constantly change with time. Treating such problems as a stationary optimization problem demand the knowledge of the pattern of change a priori and even then the procedure can be computationally expensive. Although dynamic consideration using evolutionary algorithms has been made for single-objective optimization problems, there has been a lukewarm interest in formulating and solving dynamic multi-objective optimization problems. In this paper, we modify the commonly-used NSGA-II procedure in tracking a new Pareto-optimal front, as soon as there is a change in the problem. Introduction of a few random solutions or a few mutated solutions are investigated in detail. The approaches are tested and compared on a test problem and a real-world optimization of a hydro-thermal power scheduling problem. This systematic study is able to find a minimum frequency of change allowed in a problem for two dynamic EMO procedures to adequately track Pareto-optimal frontiers on-line. Based on these results, this paper also suggests an automatic decision-making procedure for arriving at a dynamic single optimal solution on-line.