Extension of the Constrained Gravitational Search Algorithm for Solving Multi-Reservoir Operation Optimization Problem

IF 6 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Journal of Environmental Informatics Pub Date : 2020-06-22 DOI:10.3808/jei.202000434
R. Moeini, M. Soltani-nezhad
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引用次数: 10

Abstract

In this paper the proposed constrained gravitational search algorithm (CGSA) is extended and used to solve multi-reservoir operation optimization problem. Tow constrained versions of GSA named partially constrained GSA (PCGSA) and fully constrained GSA (FCGSA) are outlined to solve this optimization problem. In the PCGSA, the problem constraints are partially satisfied, however, in the FCGSA, all the problem constraints are implicitly satisfied by providing the search space for each agent which contains only feasible solution and hence leading to smaller search space for each agent. These proposed constrained versions of GSA are very useful when they are applied to solve large scale multi-reservoir operation optimization problem. The constrained versions of GSA are formulated here for both possible variables of the problem means considering water release or storage volumes as the decision variables of the problem and therefore first and second formulations of these algorithms are proposed. The proposed algorithms are used to solve the well-known four and ten reservoir operation optimization problems and the results are presented and compared with those of original form of the GSA and any available results in the literature. The results indicate the superiority of the proposed algorithms and especially FCGSA over existing methods to optimally solve large scale multi-reservoir operation optimization problem.
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求解多水库调度优化问题的约束引力搜索算法的推广
本文将提出的约束引力搜索算法(CGSA)进行推广,并应用于求解多水库调度优化问题。为解决这一优化问题,提出了部分约束GSA (PCGSA)和完全约束GSA (FCGSA)两种约束GSA算法。在PCGSA中,问题约束得到部分满足,而在FCGSA中,通过为每个智能体提供只包含可行解的搜索空间,隐式地满足所有问题约束,从而使每个智能体的搜索空间更小。这些约束版本的GSA在求解大规模多水库调度优化问题时是非常有用的。GSA的约束版本在这里为问题的两个可能变量制定,意味着考虑放水量或储水量作为问题的决策变量,因此提出了这些算法的第一和第二种公式。将所提出的算法用于解决著名的水库调度优化问题,并将结果与原始形式的GSA和文献中已有的结果进行了比较。结果表明,本文提出的算法,特别是FCGSA算法,在求解大规模多水库调度优化问题上具有较好的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Environmental Informatics
Journal of Environmental Informatics ENVIRONMENTAL SCIENCES-
CiteScore
12.40
自引率
2.90%
发文量
7
审稿时长
24 months
期刊介绍: Journal of Environmental Informatics (JEI) is an international, peer-reviewed, and interdisciplinary publication designed to foster research innovation and discovery on basic science and information technology for addressing various environmental problems. The journal aims to motivate and enhance the integration of science and technology to help develop sustainable solutions that are consensus-oriented, risk-informed, scientifically-based and cost-effective. JEI serves researchers, educators and practitioners who are interested in theoretical and/or applied aspects of environmental science, regardless of disciplinary boundaries. The topics addressed by the journal include: - Planning of energy, environmental and ecological management systems - Simulation, optimization and Environmental decision support - Environmental geomatics - GIS, RS and other spatial information technologies - Informatics for environmental chemistry and biochemistry - Environmental applications of functional materials - Environmental phenomena at atomic, molecular and macromolecular scales - Modeling of chemical, biological and environmental processes - Modeling of biotechnological systems for enhanced pollution mitigation - Computer graphics and visualization for environmental decision support - Artificial intelligence and expert systems for environmental applications - Environmental statistics and risk analysis - Climate modeling, downscaling, impact assessment, and adaptation planning - Other areas of environmental systems science and information technology.
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