Search Results - (( using multi source algorithm ) OR ( simulation optimization based algorithm ))

Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm by Jamal S., Pasupuleti J., Rahmat N.A., Tan N.M.L.

“…This strategy, which is based on the improved pelican optimization algorithm (IPOA), involves the development of a multi-objective optimization (MOA) equation with several constraints, while taking into account the Malaysian grid purchasing and selling prices. …”

Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

“…The ANN acts as a controller for radio frequency (RF)-Iocalization behavior of a Khepera robot simulated in a 3D physics-based environment. A fitness function has been created from the preliminary experiment with optimized two conflicting objectives: (1) maximize the virtual Khepera robot's behavior for homing towards a RF signal source and (2) minimize the number of hidden neurons used in its ANNs controller by the utilization of Pareto-frontier Differential Evolutionary Multi-objective (POE) algorithm. …”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

“…A smart memory-based strategy is incorporated into the algorithm to enhance solution optimality, convergence properties, and exploitation capabilities. …”

Enhancing quality of service in Multi-Radio Multi-Channel Wireless Mesh Networks by Raja Bongsu, Raja Hasyifah

“…This research utilizes the OmNET++ 4.6 simulator, an open-source tool in C++, to evaluate proposed algorithms effectively. …”
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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization by Chin, Kim On, Teo, Jason Tze Wi

“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

“…Comparative studies have been conducted with respect to Multi-Objective Modified Firefly Algorithm (MOMFA), Multi-Objective Artificial Bees Colony (MOABC) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Long-term optimal planning of distributed generations and battery energy storage systems towards high integration of green energy considering uncertainty and demand response progra... by Ba-swaimi S., Verayiah R., Ramachandaramurthy V.K., ALAhmad A.K.

“…To solve the proposed model, a hybrid approach combining Non-Dominated Sorting Genetic Algorithm II (NSGAII) and Multi-Objective Particle Swarm Optimization (MOPSO) is employed. …”

Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Kim On Chin, Jason Teo

“…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Chin Kim On, Jason Teo

“…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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Efficient and stable routing algorithm based on user mobility and node density in urban vehicular network by Al-Mayouf, Y.R.B., Ismail, M., Abdullah, N.F., Wahab, A.W.A., Mahdi, O.A., Khan, S., Choo, R.K.K.

“…This algorithm works by selecting an optimal route on the basis of hop count and link duration for delivering data from source to destination, thereby satisfying various quality of service considerations. …”
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Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

“…To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”

Meta-heuristic matrix moth�flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability by Jafar-Nowdeh A., Babanezhad M., Arabi-Nowdeh S., Naderipour A., Kamyab H., Abdul-Malek Z., Ramachandaramurthy V.K.

“…This paper presents optimal multi-criteria reconfiguration of radial distribution systems with solar and wind renewable energy sources using the weight factor method while considering reliability. …”

INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM by MOHAMED ABDELGADIR, KHALID HAROUN

“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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Optimized one-way electric vehicle carsharing system in campus environment using heterogeneous non-dominated sorting genetic algorithm II by Abdulazeez, Omar Saud

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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives by Al-Sahlawi, Ameer A. Kareim, Md. Ayob, Shahrin, Tan, Chee Wei, Mohammed Ridha, Hussein, Hachim, Dhafer Manea

“…A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid ((Formula presented.)). …”
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Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology by ALAhmad A.K., Verayiah R., Shareef H., Ramasamy A.

“…A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”

4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer by Ahmed, R., Mahadzir, S., Mota-Babiloni, A., Al-Amin, M., Usmani, A.Y., Ashraf Rana, Z., Yassin, H., Shaik, S., Hussain, F.

“…Therefore, this work aims to study a two-stage vapor compression refrigeration system (VCRS) through a novel and robust hybrid multi-objective grey wolf optimizer (HMOGWO) algorithm. …”
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Selective harmonic elimination (SHE) based 3-phase multilevel voltage source inverter (VSI) for standalone applications by Shanono, Ibrahim Haruna, Nor Rul Hasma, Abdullah, Hamdan, Daniyal, Aisha, Muhammad

“…With the fundamental switching SHE-PWM, twelve non-linear, transcendental equations are generated, and they are optimally solved using the Hybrid Coded Genetic Algorithm to eliminate 11 (n − 1) lower-order harmonics. …”
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Determining penetration limit of central distributed generation topology in radial distribution networks by Suliman, Mohamed Saad Abdelgadir

“…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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