Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing

Oliveira, Hime Aguiar e; Ingber, Lester; Petraglia, Antonio; Petraglia, M.R.; Machado, Maria Augusta Soares

doi:10.1007/978-3-642-27479-4

Cited by 35 publications

(6 citation statements)

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“…Discharge of water reservoirs is prohibited STHS problem solving takes into account hydro plant areas as well as the valve‐point loading effect of the thermal unit. The researchers developed a novel TLBO approach to obtain the best solution for hydrothermal system power generation scheduling in Reference 104. The impact of piston mounting of thermal power generation and PDZs is regarded, and the STHS issue is resolved using three different scenarios with varying constraints (Figure 20).…”

Section: Heuristic Optimization Techniquesmentioning

confidence: 99%

Decarbonizing the grid by optimal scheduling of solarPV‐windturbine‐pumped hydro storage considering application on heuristic algorithms: A comprehensive review

Bhol

Sahu

2021

Int J Energy Res

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Summary The potential for distributed generation (DG) to minimize power loss, increase productivity, lower investment costs, and, most significantly, the ability to leverage renewable energy resources such as wind, photovoltaic (PV), and microturbines, which generate power with low greenhouse‐gas emissions, has piqued interest in the power sector. Deploying DG in an unfavorable location can result in a slew of problems, including increased system failures and costs, voltage spikes and swings, and stability and resilience issues. As a result, an optimization or perceptual technique‐based paradigm is needed to identify the optimal configuration of distributed renewable energy generation for a given system that can provide fiscal, environmental, and technological benefits. Several researchers looked at the best possible location for distributed renewable generation based on their needs and goals. The formal theory for this issue, however, remains unsolved. Individual studies on solar PV systems, types of solar PV systems, wind power generation, and pumped hydro storage systems are all covered in detail in this paper. In addition, the study focuses on a variety of optimization techniques and algorithms for providing a better perspective on resolving issues related to the integration and functionality of many renewable resources in an islanded as well as grid‐connected environment. The heuristic algorithms are explained with respective flow charts individually. Finally, a comparative analysis has been carried out in order to understand and validate the usefulness of individual optimization techniques with itself and others.

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Section: Heuristic Optimization Techniquesmentioning

confidence: 99%

Decarbonizing the grid by optimal scheduling of solarPV‐windturbine‐pumped hydro storage considering application on heuristic algorithms: A comprehensive review

Bhol

Sahu

2021

Int J Energy Res

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“…The "QUENCHing" OPTIONS are among the most important for controlling Adaptive Simulated Annealing. Fuzzy ASA algorithms in particular offer new ways of controlling how these QUENCHing OPTIONS may be applied across many classes of problems (Oliveira et al, 2012).…”

Section: Adaptive Simulated Annealing (Asa)mentioning

confidence: 99%

Forecasting with Importance-Sampling and Path-Integrals: Applications to COVID-19

Ingber¹

2020

SSRN Journal

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Background: Forecasting nonlinear stochastic systems most often is quite difficult, without giving in to temptations to simply simplify models for the sake of permitting simple computations. Objective: Here, two basic algorithms, Adaptive Simulated Annealing (ASA) and path-integral codes PATHINT/PATHTREE (and their quantum generalizations qPATHINT/qPATHTREE) are offered to detail such systems. Method: ASA and PATHINT/PATHTREE have been effective to forecast properties in three disparate disciplines in neuroscience, financial markets, and combat analysis. Applications are described for COVID-19. Results: Results of detailed calculations have led to new results and insights not previously obtained. Conclusion: These 3 applications give strong support to a quite generic application of these tools to stochastic nonlinear systems.

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“…Concerning the positioning of Boltzmann machines within types of artificial neural networks, see [41]. A book by Aguiar e Oliveira et al [42] discussed stochastic global optimization using fuzzy adaptive simulated annealing, "developed to statistically find the best global fit of a nonlinear constrained, non-convex cost function over a multi-dimensional space". Simulated annealing was applied by Jung et al [43] to taxi dispatch with shared rides.…”

Section: Aimsmentioning

confidence: 99%

An Overview of AI Methods for in-Core Fuel Management: Tools for the Automatic Design of Nuclear Reactor Core Configurations for Fuel Reload, (Re)arranging New and Partly Spent Fuel

Nissan

2019

Designs

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An important aspect of managing a nuclear reactor is how to design refuellings, and from the 1980s to the present different artificial intelligence (AI) techniques have been applied to this problem. A section of the reactor core resembles a symmetrical grid; long fuel assemblies are inserted there, some of them new, some of them partly spent. Rods of “burnable poisons” dangle above, ready to be inserted into the core, in order to stop the reactor. Traditionally, manual design was made by shuffling positions in the grid heuristically, but AI enabled to automatically generate families of candidate configurations, under safety constraints, as well as in order to optimize combustion, with longer cycles of operation between shutdown periods, thus delaying the end-of-cycle point (except in France, where shutdown is on an annual basis, and Canada, where individual fuel assemblies are replaced, with no need for shutdown for rearranging the entire batch). Rule-based expert systems, the first being FUELCON,1 were succeeded by projects combining neural and rule-based processing (a symbolic-to-neural compilation of rules we did not implement), and later on, genetic algorithms in FUELGEN.2 In the literature, one also comes across the application of fuzzy techniques, tabu search, cellular automata and simulated annealing, as well as particle swarms. Safety regulations require simulating the results using a parameter prediction tool; this is done using either nodal algorithms, or neural processing.

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Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing

Cited by 35 publications

References 0 publications

Decarbonizing the grid by optimal scheduling of solarPV‐windturbine‐pumped hydro storage considering application on heuristic algorithms: A comprehensive review

Decarbonizing the grid by optimal scheduling of solarPV‐windturbine‐pumped hydro storage considering application on heuristic algorithms: A comprehensive review

Forecasting with Importance-Sampling and Path-Integrals: Applications to COVID-19

An Overview of AI Methods for in-Core Fuel Management: Tools for the Automatic Design of Nuclear Reactor Core Configurations for Fuel Reload, (Re)arranging New and Partly Spent Fuel

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