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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

“…In this thesis also, I developed a new technique to extract the logic programming from radial basis function neural networks. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

“…This project present a system program algorithm based on Moth Flame Optimization (MFO) algorithm to assign an optimal set of system program to meet the satisfaction of quality of service requirements of cloud computing in such a way that the total execution time of tasks is minimized. …”
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A combined filter line search and trust region method for nonlinear programming by Chin, Choong Ming, Halim, Abdul, Rashid, A. H. A., Nor, K. M.

“…A framework for solving a class of nonlinear programming problems via the filter method is presented. …”
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A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization by Ean, Kate Nee Goh, Jeng, Feng Chin, Wei, Ping Loh, Chea, Ling Tan

“…Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company. …”
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A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

“…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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Analytical Approach for Linear Programming Using Barrier and Penalty Function Methods by Moengin, Parwadi

“…None of these methods used Lagrangian function as a tool to solve the problem. This raises a question why are we not using this to solve the linear programming problems. …”
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Euclidean space data projection classifier with cartesian genetic programming (CGP) by WK Wong, Gopal Lenin, Tan, Terence, Ali Chekima

“…The evolutionary algorithm is based on a simplified CGP Algorithm using a 1+4 evolutionary strategy. …”
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Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

“…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm by Kahourzade, S., Mahmoudi, A., Mokhlis, Hazlie

“…This study presents the programming results of the nine essential single-objective and multi-objective functions of OPF problem. …”
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Movie recommendation system / Najwa Syamimie Hasnu by Hasnu, Najwa Syamimie

“…As a result, the objectives for this project are to study the most suitable algorithms used for a movie recommender system, to implement Collaborative Filtering algorithm on a movie recommender system prototype and to test the functionality of the movie recommender system, hi this project, a movie recommendation system with the use of Collaborative Filtering is proposed to produce a set list of movies for the users. …”
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Online Programming Judge System (UOJ) by Tran , Quang Trung

“…This research conducts a study to build an Online Programming Judge system with a mechanism to generate test cases automatically using Particle Swarm Optimization (PSO) algorithm. …”
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Projecting image on non-planar surface with zero-th order geometric continuity using simple dual-linear function and manipulation of strict integer implementation in programming la... by Yusoff, Fakhrul Hazman, Azhar, Muhammad Amirul

“…Usage of a projection system to display large screen images is still relevant in the midst of LED-based display increasing popularity.This is due to that the system itself is a mature technology, reliable and cheaper than the LED counterpart.While various methods had addressed the projection problems on curve surface, projecting image on jagged like surface (zero order geometric continuity) has yet to be studied in depth.This paper proposes a method for projecting image on non-planar surface with zero-order geometric continuity property using parametric modeling.The method manipulate linear function by combining two functions into one by taking advantage of computer programs strict implementation of integer variables.The method was applied to grid-based texturing algorithm in order to create the desired zero-continuity effect on the surface.The method was compared with texturing that implement existing curve algorithm to project image on the screen.Visual evaluation results showed that the proposed method fared better compared to existing curve-based projection algorithm.…”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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