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Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz by Abdul Aziz, Nurizzati

“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz by Abdul Aziz, Nur Izzati

“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

“…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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Multi-objective service restoration in distribution networks using genetic algorithm by Moazami, Ehsan

“…Another proposed technique is implemented to improve the penalty strategy to enhance the performance of algorithm and reduce the convergence iteration. The effectiveness of the proposed method is demonstrated by testing on two case studies, a 33-bus test system and a 16 bus test system. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”

Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems by Al-Nemrat, Asem Mustafa Moh’ad

“…In this algorithm, the convolution theorem has been used to find an optimal Lagrange multiplier.…”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems by Al-Nemrat, Asem Mustafa Moh’ad

“…In this algorithm, the convolution theorem has been used to find an optimal Lagrange multiplier.…”
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SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique by Doroody C., Tiong S.K., Darzi S.

Identification of manipulator kinematics parameters through iterative method by Baharin, Iskandar, Hasan, Md. Mahmud

“…A gradient projection algorithm was used to obtain the optimal parameters that had satisfied the world coordinates from the joint angles reading. …”
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A Comparison of Particle Swarm optimization and Global African Buffalo Optimization by Adam Kunna Azrag, Mohammed, Tuty Asmawaty, Abdul Kadir, Noorlin, Mohd Ali

“…However, the experimental result showed that PSO achieved good results in all the test cases within a short time. In many cases, PSO and GABO are promising optimization methods.…”
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Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

“…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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Towards large scale unconstrained optimization by Abu Hassan, Malik

“…Therefore in dealing with large scale unconstrained problems with a large number of variables, modifications must be made to the standard implementation of the many existing algorithms for the small scale case. One of the most effective Newton-type methods for solving large-scale problems is the truncated Newton method. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

“…However, in some cases, as the iteration number increases the result of PSO–KS method is comparable with ABC–KS method.…”
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Power line faults classification by neural network train by Ant Colony Optimization by Nasirudin, Mohd Syafiq

“…In this paper, the selected method is to train the neural network with the Ant Colony Optimization. …”
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Vehicle pick-up and drop-off schedule optimization in a university setting by Teo, Chun Kit

“…A simulated annealing-based multi-directional iterative local search algorithm is employed for solution optimization. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir by Sambo, C.H., Hematpour, H., Danaei, S., Herman, M., Ghosh, D.P., Abass, A., Elraies, K.A.

“…The second method is automatic optimization using Genetic Algorithm. …”
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm by Priyadi, Irnanda, Daratha, Novalio, Gunawan, Teddy Surya, Ramli, Kalamullah, Jalistio, Febrian, Mokhlis, Hazlie

“…The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. …”
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