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algorithm cost » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
algorithm fa » algorithm _ (Expand Search), algorithms a (Expand Search), algorithms _ (Expand Search)
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Evolutionary algorithms for VLSI multi-objective netlist partitioning
Published 2006“…Fuzzy rules are incorporated in order to handle the multi-objective cost function. For SimE, fuzzy goodness functions are designed for delay and power, and proved efficient. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…The search space is too large to be explored by deterministic algorithms. In this paper, a Genetic Algorithm based algorithm for synthesis of MVL functions is proposed. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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Economic load dispatch using memetic sine cosine algorithm
Published 2022“…SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. …”
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Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem
Published 1999“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images
Published 2023“…The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …”
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Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems
Published 2023“…In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. …”
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Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem
Published 2020“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Attacking ElGamal based cryptographic algorithms using Pollard's rho algorithm
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A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation
Published 2021“…The role of the proposed quasi oppositional based SMPID controller is to modify the tracking strategy on AC/HVDC interconnected systems while reducing the related cost function. …”
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Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…SA evolves a solution by minimizing an energy function that is based on testing objectives such as coverage, diversity, and continuity of events. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The overall cost function has been developed using fuzzy logic. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The overall cost function has been developed using fuzzy logic. …”
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Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm
Published 2018“…<p dir="ltr">This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. …”
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Belief selection in point-based planning algorithms for POMDPs
Published 2017“…Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. …”
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A Comparative Study of Elgamal Based Cryptographic Algorithms
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link
Published 2023“…An optimization problem is formulated with data rate and BER in the cost function while maintaining energy and power constraints. …”