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  1. 1

    Analytical Approach for Linear Programming Using Barrier and Penalty Function Methods by Moengin, Parwadi

    Published 2003
    “…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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    Thesis
  2. 2

    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.

    Published 2022
    “…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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    Article
  3. 3

    On network flow problems with convex cost by Nguyen, V.A., Tan, Y. P.

    Published 2004
    “…To address this problem, we derive the optimality conditions for minimising convex and differentiable cost functions, and devise an algorithm based on the primal-dual algorithm commonly used in linear programming. …”
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    Article
  4. 4

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…The minimization of system execution and transfer time in the proposed algorithm are considered as objective functions. The experimental testing of the proposed algorithm are considered as objective functions. …”
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    Academic Exercise
  5. 5

    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.

    Published 2006
    “…A framework for solving a class of nonlinear programming problems via the filter method is presented. …”
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    Article
  6. 6

    The application of genetic algorithm to solve unit commitment problem/ Zuhairi Baharudin by Baharudin, Zuhairi

    Published 1998
    “…Due to large variety of constraints to be satisfied a proper fitness function of the GA is built. MATLAB program is used to solve the unit commitment problems and to represent the fitness function of die GA.…”
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    Thesis
  7. 7

    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

    Published 2015
    “…This study presents the programming results of the nine essential single-objective and multi-objective functions of OPF problem. …”
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    Article
  8. 8

    An improved grey wolf with whale algorithm for optimization functions by Asgher, Hafiz Maaz

    Published 2022
    “…The performance of the proposed algorithm is tested and evaluated on five benchmarked unimodal and five multimodal functions. …”
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    Thesis
  9. 9

    Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim by Md Daim, Mohd Khairil Izwan

    Published 2006
    “…Optimal power flow (OPF) is one of the main functions of power system operation and control. This project presents a new technique for solving the optimal power flow problem, in a power system using an Evolutionary Programming and Immune Evolution Programming optimization technique. …”
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    Thesis
  10. 10

    CSC099: Foundation Computing II / Centre of Foundation Studies by UiTM, Centre of Foundation Studies

    Published 2022
    “…This course introduces basic computer programming algorithm, problem solving, structured programming language, selection structure, repetition structure, function and array. …”
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    Teaching Resource
  11. 11

    Congestion management based optimization technique using bee colony by Rahim M.A., Musirin I., Abidin I.Z., Othman M.M., Joshi D.

    Published 2023
    “…Tests conducted on the IEEE 30-Bus Reliability Test System for performance assessment revealed that the proposed bee algorithm technique is better than evolutionary programming technique in addressing this problem. �2010 IEEE.…”
    Conference Paper
  12. 12

    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

    Published 2016
    “…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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    Article
  13. 13

    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.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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    Article
  14. 14

    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.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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    Article
  15. 15

    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…Linear programming (LP) is a mathematical modelling that formulate a problem into three components which are decision variables, objective function and constraints. …”
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    Thesis
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    Online Programming Judge System (UOJ) by Tran , Quang Trung

    Published 2013
    “…The system has the function to judge programming code by evaluating the output that the program produced. …”
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    Final Year Project
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    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…As for WXES3l82, the thesis cover the development of programming code, the code implementation and testing and the evaluation including discussion about the problem/constraints meed in the coding program development. …”
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    Thesis
  20. 20

    Integrated Optimization Algorithm in Solving Economic Dispatch Problems by Ismail N.L., Musirin I., Dahlan N.Y., Mansor M.H., Sentilkumar A.V.

    Published 2024
    “…The proposed algorithm has been compared with the existing techniques, Multi-objective Barnacles Mating Optimizer and Multi-objective Evolutionary Programming. …”
    Conference Paper