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Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization
Published 2019“…In another hand, numerical results of ABCED Conjugate Gradient Methods also achieved up to 80.95% of the selected benchmark global optimization been solved successfully. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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Global optimization method for continuous - Time sensor scheduling
Published 2010“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)
Published 2016“…Several global methods have been proposed for solving discrete optimization problems. …”
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Globalization of Barzilai and Borwein Method for Unconstrained Optimization
Published 2009“…Incorporate with monotone strategies, the resulting algorithms belong to the class of monotone gradient methods with globally convergence. …”
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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications
Published 2023“…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
Published 2018“…The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. …”
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Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization
Published 2016“…Other than that, we also analyse the global convergence properties of the modified methods. …”
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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A modified conjugate gradient coefficient with inexact line search for unconstrained optimization
Published 2016“…Conjugate gradient (CG) method is a line search algorithm mostly known for its wide application in solving unconstrained optimization problems. …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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A Global African Buffalo Optimization
Published 2017“…In this paper, a modified version of the African Buffalo Optimization algorithm with emphasis on global search is proposed. …”
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A Hybrid Method Based on Cuckoo Search Algorithm for Global Optimization Problems
Published 2018“…However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimization algorithm, which is a combination of Cuckoo search algorithm and Hill climbing called CSAHC discovers many local optimum traps by using local and global searches, although the local search method is trapped at the local minimum point. …”
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A variational discrete filled function approach in discrete global optimization
Published 2015“…Many real-life applications governed by discrete variables poss multiple local optimal solutions, which requires the utilization of global optimization tools find the best solution amongst them.The main difficulty in determining the best solution, or also known as the global solution, is to escape from the basins surrounding local minimums.To overcome this issue, an auxiliary function is introduced in discrete filled function method which turns the local minimizer of the original function become a maximizer.Then, an improved local minimum is found by minimizing the filled function, otherwise the edge of the feasible region is attained.Based on a discrete filled function method from the literature, we propose a modification particularly on the neighbourhood search to enhance its computational efficiency.Numerical results suggest that the proposed algorithm is efficient in solving large scale complex discrete optimization problems.…”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…Finally, a modified local search method using Perturb and Observe with adaptive step size method (P&O-ASM) is proposed to refine the near-optimal duty cycle and track GMPP with negligible oscillations. …”
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A Comparison of Particle Swarm optimization and Global African Buffalo Optimization
Published 2020“…However, in this paper, a comparison between Particle Swarm Optimization (PSO) and Global African Buffalo Optimization (GABO) algorithms was performed. …”
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Development of committee machine models for multiple response optimization problems
Published 2014“…There are several methods in two categories to solve MRO problems. The first category includes premier methods such as Response Surface Methodology (RSM) and Taguchi method and the second one includes newer methods like hybrid methods of ANNs and Genetic Algorithm (GA). …”
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A Hybrid of Quasi-Newton Method with CG Method for Unconstrained Optimization
Published 2019“…The resulting hybrid algorithm is globally convergent under exact line search…”
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