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A chaotic chimp sine cosine algorithm for optimizing hydrothermal power scheduling

CHAOS SOLITONS & FRACTALS 2025年 192卷

作者： Iqbal, Shahid A. Raj, Saurav Shiva, Chandan Kumar Inst Chem Technol Mumbai Marathwada Campus Jalna India SVKMs Inst Technol Dept Elect Engn Dhule Maharsahtra India SR Univ Dept Elect & Elect Engn Warangal Telangana India

This study addresses the critical issue of optimizing the short-term hydrothermal scheduling (STHTS) problem, which is a significant concern in the context of rising energy demands. The need to reduce fuel costs while meeting operational constraints makes the STHTS a pressing problem in today's power generation context. This study provides a comprehensive analysis of various soft computing techniques employed to solve the STHTS problem, characterized by its nonlinear nature, encompassing both linear and nonlinear constraints, and a nonlinear objective function. The importance of this study lies in its relevance to the global push towards more efficient and sustainable energy solutions. This study introduces a novel approach using the chaotic-chimp sine cosine (C-CHOA-SC) algorithm, which stands out because of its ability to handle the complexities of the STHTS problem efficiently, including avoiding local optima and managing constraints. This is because of its innovative repair process for candidate solutions, which addresses the limitations of traditional penalty function approaches. The comparative analysis is conducted on multiple hydrothermal scheduling test systems including genetic algorithms, particle swarm optimization, gravitational search algorithm, biogeography-based optimization, krill herd algorithm, bacterial foraging optimization, ant colony optimization, chaotic ant swarm optimization, cuckoo search optimization, co-evolutionary differential evolution, salp swarm algorithm, lightning attachment procedure optimization, social group optimization, multi-objective salp swarm algorithm, grey wolf optimizer, and enhanced harris hawks optimization. The results demonstrated that the C-CHOA-SC algorithm effectively solved the STHTS problem by minimizing fuel costs and emissions. It outperformed 17 other metaheuristic techniques across the three test systems and demonstrated superior performance in terms of cost reduction, constraint satisfaction, and converge

关键词： Short-term hydrothermal scheduling optimization Cost function Linear and nonlinear constraints nonlinear objective function Special repair process

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Multi-variable constrained non-linear optimal planning and operation problem for isolated microgrids with stochasticity in wind, solar, and load demand data

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第11期14卷 2181-2190页

作者： Kumar, Maneesh Tyagi, Barjeev IIT Roorkee Dept Elect Engn Roorkee Uttar Pradesh India

A microgrid (MG) is a cluster of small-scale sources known as micro-sources, the energy storage devices, and the loads. MGs are promising entities that allow a considerable amount of renewable energy penetration into the system. A stochastic optimisation model is presented in this study to find the optimal size of the distributed energy resources (DERs). The uncertainties are considered with the help of multiple scenarios of random variables viz. wind output, solar output, and load demand data. A particular case of Beta distribution is used to create these variations. A cost-based, multi-variable constrained non-linear objective function is formulated. The considered test MG system is more generalized with solar and wind energy penetration. The results show the effect of operational as well as the planning aspects together under various reliability conditions for an isolated MG. The formulated problem is solved to obtain a global optimal solution using a sequential programming approach and a comparative assessment of results with a hybrid particle swarm optimisation (PSO) approach has also been presented. It is found that the results obtained from the sequential programming approach are better compared to the hybrid PSO approach.

关键词： distributed power generation particle swarm optimisation power distribution planning power generation planning power distribution reliability power generation reliability stochastic programming operational costs DERs test MG system isolated MG global optimal solution sequential programming approach hybrid particle swarm optimisation approach optimal sizing reliability conditions system constraints operation problem isolated microgrids stochasticity load demand data microgrid small-scale sources microsources energy storage devices renewable energy penetration stochastic optimisation model optimal size distributed energy resources random variables wind output solar output Beta distribution cost-based function nonlinear objective function multivariable constrained nonlinear optimal planning

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A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2018年第4期15卷 582-586页

作者： Mohanty, Ramanarayan Happy, S. L. Routray, Aurobinda IIT Kharagpur Adv Technol Dev Ctr Kharagpur 721302 W Bengal India IIT Kharagpur Dept Elect Engn Kharagpur 721302 W Bengal India

The lack of proper class discrimination among the hyperspectral (HS) data points poses a potential challenge in HS classification. To address this issue, this letter proposes an optimal geometry-aware transformation for enhancing the classification accuracy. The underlying idea of this method is to obtain a linear projection matrix by solving a nonlinear objective function based on the intrinsic geometrical structure of the data. The objective function is constructed to quantify the discrimination between the points from dissimilar classes on the projected data space. Then, the obtained projection matrix is used to linearly map the data to more discriminative space. The effectiveness of the proposed transformation is illustrated with three benchmark real-world HS data sets. The experiments reveal that the classification and dimensionality reduction methods on the projected discriminative space outperform their counterpart in the original space.

关键词： Dimensionality reduction (DR) geometry-aware mapping hyperspectral (HS) classification manifold nonlinear objective function

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Primal dual based algorithm for degree-balanced spanning tree problem

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APPLIED MATHEMATICS AND COMPUTATION 2018年 316卷 167-173页

作者： Ran, Yingli Chen, Zhihao Tang, Shaojie Zhang, Zhao Xinjiang Univ Coll Math & Syst Sci Urumqi 830046 Xinjiang Peoples R China Zhejiang Normal Univ Coll Math Phys & Informat Engn Jinhua 321004 Zhejiang Peoples R China Univ Texas Dallas Naveen Jindal Sch Management Dallas TX 75080 USA

This paper studies approximation algorithm for the degree-balanced spanning tree (DBST) problem. Given a graph G = (V, E), the goal is to find a spanning tree T such that Sigma v is an element of V deg(T)(v)(2) is minimized, where deg T (v) denotes the degree of node v in tree T. The idea of taking squares on node degrees is to manifest the role of nodes with large degree, and thus minimizing the sum will result in a comparatively balanced degree distribution. This is a non-linear objective function. We prove that DBST is NP-hard, and then develop a primal-dual based algorithm with a guaranteed performance ratio. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Degree-balanced spanning tree nonlinear objective function Primal dual algorithm

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A Maximization Problem in Tropical Mathematics: A Complete Solution and Application Examples

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INFORMATICA 2016年第3期27卷 587-606页

作者： Krivulin, Nikolai St Petersburg State Univ Fac Math & Mech 28 Univ Ave St Petersburg 198504 Russia

An optimization problem is formulated in the tropical mathematics setting to maximize a nonlinear objective function defined by conjugate transposition on vectors in a semimodule over a general idempotent semifield. The study is motivated by problems from project scheduling, where the deviation between completion times of activities is to be maximized subject to precedence constraints. To solve the unconstrained problem, we establish an upper bound for the function, and then obtain a complete solution to a system of vector equations to find all vectors that yield the bound. An extension of the solution to handle constrained problems is discussed. The results are applied to give direct solutions to the motivational problems, and illustrated with numerical examples.

关键词： tropical mathematics idempotent semifield optimization problem nonlinear objective function project scheduling

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Algebraic Solutions of Tropical Optimization Problems

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LOBACHEVSKII JOURNAL OF MATHEMATICS 2015年第4期36卷 363-374页

作者： Krivulin, N. St Petersburg State Univ Univ pr 28 St Petersburg 198504 Russia

We consider multidimensional optimization problems, which are formulated and solved in terms of tropical mathematics. The problems are to minimize (maximize) a linear or nonlinear function defined on vectors over an idempotent semifield, and may have constraints in the form of linear equations and inequalities. The aim of the paper is twofold: first to give a broad overview of known tropical optimization problems and solution methods, including recent results;and second, to derive a direct, complete solution to a new constrained optimization problem as an illustration of the algebraic approach recently proposed to solve tropical optimization problems with nonlinear objective functions.

关键词： Idempotent semifield tropical optimization problem nonlinear objective function linear inequality constraint direct solution

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Searching Method of Optimization of Bending Reinforced Concrete Slabs with Simultaneous Assessment of Criterion function and the Boundary Conditions

Searching Method of Optimization of Bending Reinforced Concr...

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International Conference on Materials Science and Mechanical Engineering (ICMSME 2013)

作者： Ashot, Tamrazyan Ekaterina, Filimonova Moscow State Univ Civil Engn Dept Reinforced Concrete & Masonry Struct Moscow 129337 Russia

ISBN: (纸本)9783037859490

Problems of optimal design of reinforced concrete structures are characterized by existence of nonlinear objective function and a set of local extrema. For the solution of similar tasks for their optimization it's offered to use an algorithm based on the method of casual search. A prerequisite for this is the requirement for simultaneous consideration of changes in the objective function and the boundary conditions in the motion search for the optimum. This procedure provides a guaranteed search of optimal parameters plate.

关键词： Reinforced concrete structure Optimal design Searching method nonlinear objective function

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OPTIMIZING FUZZY CLUSTER ENSEMBLE IN STRING REPRESENTATION

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2013年第2期27卷 1350005-1350005页

作者： Alizadeh, Hosein Minaei-Bidgoli, Behrouz Parvin, Hamid Iran Univ Sci & Technol Dept Comp Engn Tehran Iran

In this paper, we present a novel optimization-based method for the combination of cluster ensembles. The information among the ensemble is formulated in 0-1 bit strings. The suggested model defines a constrained nonlinear objective function, called fuzzy string objective function (FSOF), which maximizes the agreement between the ensemble members and minimizes the disagreement simultaneously. Despite the crisp primary partitions, the suggested model employs fuzzy logic in the mentioned objective function. Each row in a candidate solution of the model includes membership degrees indicating how much data point belongs to each cluster. The defined nonlinear model can be solved by every nonlinear optimizer;however;we used genetic algorithm to solve it. Accordingly, three suitable crossover and mutation operators satisfying the constraints of the problem are devised. The proposed crossover operators exchange information between two clusters. They use a novel relabeling method to find corresponding clusters between two partitions. The algorithm is applied on multiple standard datasets. The obtained results show that the modified genetic algorithm operators are desirable in exploration and exploitation of the big search space.

关键词： Fuzzy cluster ensemble nonlinear objective function genetic algorithm optimization

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Searching Method of Optimization of Bending Reinforced Concrete Slabs with Simultaneous Assessment of Criterion function and the Boundary Conditions

Searching Method of Optimization of Bending Reinforced Concr...

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2013 International Conference on Materials Science and Mechanical Engineering(ICMSME 2013)

作者： Tamrazyan Ashot Filimonova Ekaterina Moscow State University of Civil Engineering Department of Reinforced Concrete and Masonry Structures

关键词： Reinforced concrete structure Optimal design Searching method nonlinear objective function

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Combinatorial Cutting while Solving Optimization nonlinear Conditional Problems of the Vertex Located Sets

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JOURNAL OF AUTOMATION AND INFORMATION SCIENCES 2010年第5期42卷 21-29页

作者： Yemets, O. A. Yemets, Ye. M. Chilikina, T. V. Poltava Univ Consumer Cooperat Ukraine Poltava Ukraine

The method of cutting for problems on combinatorial vertex located sets with nonlinear objective functions with arbitrary additional conditions is considered. The initial problem is reduced to a problem with a linear ... 详细信息

关键词： combinatorial Euclidean optimization combinatorial vertex located sets nonlinear objective function combinatorial cutting method computation algorithm

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