Search Results - (( parameter optimization strategy algorithm ) OR ( process optimization problem algorithm ))
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1
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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2
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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3
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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4
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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5
An improved sine cosine algorithm for solving optimization problems
Published 2018“…Due to its simplicity and less tedious parameter tuning over other multi-agent-based optimization algorithms, Sine Cosine Algorithm (SCA) has gained lots of attention from numerous researchers for solving optimization problem. …”
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6
A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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7
Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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8
Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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9
Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
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The effect of job satisfaction on the relationship between organizational culture and organizational performance
Published 2023“…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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11
Application of manta ray foraging optimization with gradient-based mutation (cMRFO) for solving power system problems
Published 2023“…In this paper, the Manta Ray Foraging Optimization (MRFO) algorithm is applied to solve real parameter constrained optimization problems, using the Gradient-based Mutation MRFO (cMRFO) variant. …”
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Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms
Published 2016“…The results indicate the acceptable potential of the evolutionary strategies for the controlling and optimization of the 3DP process as a complicated engineering problem.…”
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Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller
Published 2010“…GA have been successfully applied to solve many optimization problems. This research proposes a method that may help users to determine the membership function of FLC using the technique of GA optimization for the fastest processing in solving the problems. …”
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14
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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17
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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18
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Hence, a memory-based optimization tool has good potential to retain the optimal design parameter during the PID tuning process. …”
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19
Hybrid evolutionary optimization algorithms: A case study in manufacturing industry
Published 2014“…This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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