Search Results - (( generating adaptation optimization algorithm ) OR ( java application using algorithm ))
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Optimal operation of hydropower reservoirs under climate change
Published 2024“…The current research aims to optimize the water release to generate optimal hydropower generation for the future up to the year 2039. …”
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Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator
Published 2019“…Being a NP-complete problem, pairwise test suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in the literature. …”
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Optimal operation of hydropower reservoirs under climate change
Published 2023“…The current research aims to optimize the water release to generate optimal hydropower generation for the future up to the year 2039. …”
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Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation
Published 2018“…The VS-MGS’s results ultimately revealed that the adaptation of elitism mechanism with iteration in greedy algorithm resulted in an improved efficiency in the process of generating a near-optimal test case set size.…”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Active power optimization based on non adaptive immune algorithm: article
Published 2010“…This paper presents a study of active power optimization based on non adaptive immune algorithm (NAIA) in power systems. …”
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An adaptive flower pollination algorithm for minimizing software testing redundancy
Published 2017“…In this paper, we present an adaptive flower pollination algorithm for solving an optimization problem, i.e., minimization of software testing redundancy. …”
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A Kidney Algorithm for Pairwise Test Suite Generation
Published 2018“…This study introduces a new pairwise strategy by adapting KA; which is the first time to adapt KA in generating the test suite. …”
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Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites
Published 2017“…The teaching learning-based optimization (TLBO) algorithm has shown competitive performance in solving numerous real-world optimization problems. …”
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Fuzzy adaptive teaching learning-based optimization strategy for the problem of generating mixed strength t-way test suites
Published 2017“…The teaching learning-based optimization (TLBO) algorithm has shown competitive performance in solving numerous real-world optimization problems. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Q-learning whale optimization algorithm for test suite generation with constraints support
Published 2023“…This paper introduces a new variant of a metaheuristic algorithm based on the whale optimization algorithm (WOA), the Q-learning algorithm and the Exponential Monte Carlo Acceptance Probability called (QWOA-EMC). …”
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An improved adaptive shuffled frog leaping algorithm to solve various non smooth economic dispatch problems in power system / Mohamad Helmi Muhamad Izham
Published 2016“…This thesis discusses the solution of Economic Dispatch (ED) problems which is to minimize the total cost of generation in power system operation by using an improved adaptive shuffled frog leaping algorithm (lASFLA). …”
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…A test suite of twelve benchmark test functions and three global optimization problems: Team Formation Optimization (TFO), Low Autocorrelation Binary Sequence (LABS), and Modified Condition/ Decision coverage (MC/DC) test case generation problem were solved using the proposed algorithm. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy
Published 2023“…Air quality; Decision making; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Inference engines; Mapping; Mean square error; Multiobjective optimization; Optimal systems; Particle swarm optimization (PSO); Quality control; Renewable energy resources; Solar radiation; Uncertainty analysis; Adaptive neuro-fuzzy inference system; ANFIS; Multi objective algorithm; Multi objective particle swarm optimization; Multi-objective genetic algorithm; Renewable energies; Renewable energy generation; Solar radiation forecasting; Parameter estimation…”
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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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Book Chapter -
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An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem
Published 2022“…A test suite of twelve optimization benchmark test functions and three global optimization problems (Team Formation Optimization - TFO, Low Autocorrelation Binary Sequence - LABS, and Modified Condition/Decision Coverage - MC/DC test case generation) were solved using the proposed algorithm. …”
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