ABSTRACT In this paper, a weighted cellular automata (CA) is proposed to solve bi-objective reservoir operation optimisation problem considering two objectives of water supply and hydropower production. A mathematically derived updating rule is used contributing to the efficiency of the proposed CA method. The updating rule of the problem is derived by converting the bi-objective problem to a single-objective problem using the well-known weighting method. The proposed method is used to operate the Dez reservoir in Iran over various operation periods of 60, 120, 240 and 480 months to test the performance of the method for operational problems of different scales. Performance of the method is also compared with that of a non-dominated sorting genetic algorithm (NSGAII) as one of the most popular multi-objective evolutionary algorithms. The results indicate that the proposed method is highly efficient compared to the NSGAII while producing comparable results. This is in line with the early findings of superior efficiency and comparable effectiveness of the CA method with the existing evolutionary algorithms for single objective optimisation problems.

中文翻译：

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使用元胞自动机的多目标优化：在多用途油藏作业中的应用

摘要 在本文中，提出了一种加权元胞自动机（CA）来解决考虑供水和水电生产两个目标的双目标水库运行优化问题。使用数学推导的更新规则有助于提高所提出的 CA 方法的效率。问题的更新规则是通过使用众所周知的加权方法将双目标问题转换为单目标问题来导出的。将所提出的方法用于伊朗 Dez 水库在 60、120、240 和 480 个月的不同运营期，以测试该方法对不同规模运营问题的性能。还将该方法的性能与作为最流行的多目标进化算法之一的非支配排序遗传算法 (NSGAII) 的性能进行了比较。结果表明，与 NSGAII 相比，所提出的方法是高效的，同时产生可比的结果。这与 CA 方法与现有进化算法对单目标优化问题的卓越效率和可比有效性的早期发现一致。