Harmony search optimization applied to reservoir engineering assisted history matching

Shams, Mohamed Bin; El-Banbi, Ahmed; Sayyouh, Helmy

doi:10.1016/s1876-3804(20)60014-3

Cited by 11 publications

(7 citation statements)

References 31 publications

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“…The study conducted a comparative analysis, pitting the results obtained throuIHSA against those derived from genetic and particle swarm optimization algorithms. The findings provided compelling evidence supporting the superiority and effectiveneIof HSA [85]. The authors attributed the enhanced perforIce of HSA in addressing reservoir engineering-assisted history-matching queries over other algorithms to the following factors:…”

Section: Harmony Search Algorithm On Damsmentioning

confidence: 86%

Optimization of Dam Operation and Interaction with Groundwater: An Overview Focusing on Greece

Karakatsanis,

Patsialis,

Kalaitzidou

et al. 2023

Water

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The optimization of dam operations to transform them into multi-objective facilities constitutes a challenge for both hydrology, hydrogeology, and hydropower generation. However, the use of the optimal algorithm for such transformation is critically important. Additionally, the literature has highlighted that dams might negatively influence the recharge of groundwater. Within this study, we provide an overview of the available algorithms for the optimization of dam operations. Additionally, an overview focusing on hydropower generation in Greece illustrates the high potential of the Mediterranean region for hydropower generation and the application of MAR. The water quality of the reservoirs is also highlighted as a critical parameter. Within this study, we present indices for water quality monitoring in dam reservoirs, while the most prevailing index is the SRDD. This study constitutes a guide for researchers in choosing the optimal tools for the optimization of dam operations and the water quality monitoring of reservoirs. The present study suggests a meta-heuristic optimization methodology using the harmony search algorithm. The model uses a geometric model of the reservoir and calculates the level–supply curve. Furthermore, a multi-criteria optimization model was developed with two objective functions: the maximum power output from the hydroelectric power plant turbines and the optimal groundwater recharge. The model with appropriate parameter modifications can be applied to any small dam as it is a decision- and policy-making methodology, independent of local conditions. A further step is the application of these approaches dealing with field data and the numerical modeling of case studies. The interdisciplinary approach of this study links deferent aspect and scientific perceptions, providing a comprehensive guide to optimal water resource management and environmental sustainability.

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Section: Harmony Search Algorithm On Damsmentioning

confidence: 86%

Optimization of Dam Operation and Interaction with Groundwater: An Overview Focusing on Greece

Karakatsanis,

Patsialis,

Kalaitzidou

et al. 2023

Water

View full text Add to dashboard Cite

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“…It searches for the optimal example in the solution space by the particles in the swarm [16]. Research and practice have shown that PSO has the advantages of fast convergence speed, high quality of noninferior solutions, and good robustness in multidimensional spatial function optimization and dynamic objective optimization.…”

Section: Adaptive Mutation Particle Swarm Algorithm Partmentioning

confidence: 99%

[Retracted] An Improved Particle Swarm Optimization‐Powered Adaptive Classification and Migration Visualization for Music Style

Liu

2021

Complexity

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Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper proposes methods for different styles of music classification and migration visualization. This method has the advantages of simple structure, mature algorithm, and accurate optimization. It can find better network weights and thresholds so that particles can jump out of the local optimal solutions previously searched and search in a larger space. The global search uses the gradient method to accelerate the optimization and control the real-time generation effect of the music style transfer, thereby improving the learning performance and convergence performance of the entire network, ultimately improving the recognition rate of the entire system, and visualizing the musical perception. This kind of real-time information visualization is an artistic expression form, in which artificial intelligence imitates human synesthesia, and it is also a kind of performance art. Combining traditional music visualization and image style transfer adds specific content expression to music visualization and time sequence expression to image style transfer. This visual effect can help users generate unique and personalized portraits with music; it can also be widely used by artists to express the relationship between music and vision. The simulation results show that the method has better classification performance and has certain practical significance and reference value.

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“…The HS algorithm mechanism can be demonstrated by the following steps: initialization of harmony memory, formulating new vectors for the new solution (applying a two-stage probability-based harmony memory). The HS algorithm's core tweakable factors are pitch adjustment probability (PAR) along with the retention probability of harmony memory [38]. Here, the PAR ensures the local search capabilities of the vectors around sub problem space.…”

Section: Harmony Search Algorithm (Hs)mentioning

confidence: 99%

Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances

et al. 2021

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Combinatorial optimization problems are often considered NP-hard problems in the field of decision science and the industrial revolution. As a successful transformation to tackle complex dimensional problems, metaheuristic algorithms have been implemented in a wide area of combinatorial optimization problems. Metaheuristic algorithms have been evolved and modified with respect to the problem nature since it was recommended for the first time. As there is a growing interest in incorporating necessary methods to develop metaheuristics, there is a need to rediscover the recent advancement of metaheuristics in combinatorial optimization. From the authors’ point of view, there is still a lack of comprehensive surveys on current research directions. Therefore, a substantial part of this paper is devoted to analyzing and discussing the modern age metaheuristic algorithms that gained popular use in mostly cited combinatorial optimization problems such as vehicle routing problems, traveling salesman problems, and supply chain network design problems. A survey of seven different metaheuristic algorithms (which are proposed after 2000) for combinatorial optimization problems is carried out in this study, apart from conventional metaheuristics like simulated annealing, particle swarm optimization, and tabu search. These metaheuristics have been filtered through some key factors like easy parameter handling, the scope of hybridization as well as performance efficiency. In this study, a concise description of the framework of the selected algorithm is included. Finally, a technical analysis of the recent trends of implementation is discussed, along with the impacts of algorithm modification on performance, constraint handling strategy, the handling of multi-objective situations using hybridization, and future research opportunities.

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Harmony search optimization applied to reservoir engineering assisted history matching

Cited by 11 publications

References 31 publications

Optimization of Dam Operation and Interaction with Groundwater: An Overview Focusing on Greece

Optimization of Dam Operation and Interaction with Groundwater: An Overview Focusing on Greece

[Retracted] An Improved Particle Swarm Optimization‐Powered Adaptive Classification and Migration Visualization for Music Style

Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems: Overview and Recent Advances

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