Search Results - (( evolution optimization strategy algorithm ) OR ( using optimization approach algorithm ))

Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

“…ORA is formulated based on Lagrangian method and optimized using Particle Swarm Optimization (PSO). …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Teo, Jason Tze Wi, Rayner Alfred, Kim, On Chin

“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…Experimental results of the proposed strategy are compared with other advanced meta-heuristic algorithms using the Otsu and Kapur fitness functions. …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Jason, Teo, Kim, On Chin, Alfred, Rayner

“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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Heat exchanger network optimization using differential evolution with stream splitting by Thuy, N.T.P., Pendyala, R., Marneni, N.

“…This article introduces a new strategy for HEN optimization using differential evolution algorithm. …”
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Harmonic Elimination Pulse Width Modulation Using Differential Evolution Technique For Three Phase Voltage Source Inverter by Kamisman, Norazelina

“…Explanation of DE algorithm execution is given, and the best approach of mutation strategy selection used in DE has been investigated. …”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir

“…In this paper, a new variant of Manta Ray Foraging Optimization (MRFO) algorithm is introduced to deal with real parameter constrained optimization problem. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…Experimental results of the proposed strategy are compared with other advanced meta-heuristic algorithms using the Otsu and Kapur fitness functions. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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Evolving controllers for simulated car racing using differential evolution by Shi, Jun Long, Chin, Kim On, Teo, Jason Tze Wi, Tan, Tse Guan, Rayner Alfred, Patricia Anthony

“…This research result shows that DE performed well in TORCS even though a very simple fitness function was used. This indicates that DE has well-tuned the neural network weights to generate optimal and sub-optimal controllers in TORCS.…”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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Base pressure control through micro jets at supersonic Mach numbers using experimental and machine learning approach by Aabid, Abdul, Khan, Sher Afghan, Yasir, Javed

“…Furthermore, machine learning (ML) algorithms were utilized to predict base pressure outcomes and optimize control strategies. …”
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Evaluation and prediction of time overruns in Jordanian construction projects using coral reefs optimization and deep learning methods by Shihadeh, Jumana, Al-Shaibie, Ghyda, Bisharah, Majdi, Alshami, Dania, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…The Multilayer Perceptron (MLP) was utilized as the underlying framework, and the model's parameters were refined utilizing the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) with Rank-One Adaptation (CROA) to enhance the predictive capabilities. …”
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Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

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A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

“…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
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An improved hybrid method combined with a cloud-based supervisory control to facilitate smooth coordination under low-inertia grids by Yiizzan, Suffian, Ahmed Mohamed, Ahmed Haidar, Wan Azlan, Wan Zainal Abidin, Hazrul, Mohamed Basri

“…The presented approach synthesizes the traditional droop control and the generalized cloud-based algorithm to address challenges related to dynamic load variations and intermittent renewable energy sources. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…Hence, a new co-evolution binary particle swarm optimization with a multiple inertia weight strategy (CBPSO-MIWS) is proposed in this work. …”
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