Search Results - (( model validation a algorithm ) OR ( based optimization strategical algorithm ))*

Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes by Reem Mustafa , Mah’d Al Debes

“…Complementing this, game theory offers a robust framework to model strategic interactions among users, ensuring fair and effective resource distribution. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…This research undertakes a comprehensive exploration aimed at optimizing cancer therapy by integrating mathematical modelling and advanced optimization methodologies. …”
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Agreement options for negotiation on material location decision of housing development by Utomo, C., Rahmawati, Y.

“…Housing development requires infrastructure development, which includes preparation of sand material embankment as much as ± 200,000 m3. The objectives are to find a model for agreement options and coalition, to validate the algorithms of the best fit for material locations and to determine how much the proposed agreement option was achieved. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Ba-swaimi S., Verayiah R., Ramachandaramurthy V.K., ALAhmad A.K., Padmanaban S.

“…The suggested model is validated utilizing the IEEE 33-bus DS developed in MATLAB R2023b. …”

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. …”

An effective strategy for unit commitment of microgrid power systems integrated with renewable energy sources including effects of battery degradation and uncertainties by Manoharan P., Chandrasekaran K., Chandran R., Ravichandran S., Mohammad S., Jangir P.

“…Out of which, two case studies defined as a multiobjective problem, and it has been transformed into a single-objective model using different weight factors. …”

Effectiveness of farmers’ professional cooperatives in helping rural revitalization using big data analysis by Ruiqi Zhang, Wong Sing Yun, Siti Hajar Samsu

“…A combined approach of the Back Propagation Neural Network and the Mayfly Optimization Algorithm was put forward in an attempt to promote feature selection and accuracy of prediction for the intricate and multi-layered socioeconomic case. …”
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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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Harris Hawk Optimization-Based Deep Neural Networks Architecture for Optimal Bidding in the Electricity Market by Kavita Jain, Muhammed Basheer Jasser, Muzaffar Hamzah, Akash Saxena, Ali Wagdy Mohamed

“…In this research, we provide HHO-NN (Harris Hawk Optimization-Neural network), a novel algorithm based on Harris Hawk Optimization (HHO) that is capable of fast convergence when compared to previous evolutionary algorithms for automatically searching for meaningful multilayered perceptron neural networks (MPNNs) topologies for optimal bidding. …”
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Shared mental model as an enabler of Malaysia waqf land development by Ismail, Nur Azlin, Omar, Ismail, Abu Bakar, Mohamad Noor Ropiah, Suhaili, Nur Aqidah, Hussin, Rohayati

“…Besides, several documents such as fatwas and enactment were used to triangulate those findings.Findings - It was found that, WSA development is engaging SMM Team Model.as its design up to tailoring other members expected behaviour.The findings of understanding on SMM setup in WSA are presented in three different layers: Input : 1. the team members had set a stepping stone based on their background and resources before entering the strategic intersection in developing waqf lands; but both main actors shared the same the same vision Process :1. …”
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Towards Wind Energy-based Charging Stations: A Review of Optimization Methods by Alhasan A.M.W., Umar D.A., Alkawsi G., Alkahtani A.A., Alomari M.A., Aris H.

“…Singular reliance on a solitary algorithm or software for charging utility optimization is discerned to be potentially limiting. …”

Maximizing DRL-based energy efficiency in IRS-NOMA using a DDPG algorithm for the next generation of wireless communications by Audah, Kamil, Noordin, Nor K., Hussein, Wala'a, Rasid, Mod Fadlee B. A., Sali, Aduwati, Flah, Aymen

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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

“…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”

Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism by Alomari M.F., Mahmoud M.A., Gharaei N., Rasool S.M., Hasan R.A.

“…The core of the algorithm utilizes a Genetic Algorithm (GA) to find the optimal position for the first evaluator by minimizing the total distance between this evaluator and all CCTV nodes, aiming for surveillance efficiency. …”

Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…In addition, the solutions have been evaluated based on pre-defined performance metrics and the outcomes of the optimization framework were compared with the other existing optimization techniques to evaluate the potency and the productivity of the developed MLPSO algorithm. …”

Dam haji game using A* search algorithm / Siti Farah Najwa Mukhlis by Mukhlis, Siti Farah Najwa

“…In Dam Haji game, the goal is to find the optimal movement to make, so A* algorithm, which is a pathfinding algorithm is used. …”
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Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm by Ariff Nijay, Ramli

“…Lastly, a study of the industrial case was performed as a validation of the developed model and algorithm. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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