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  1. 1
    Overview of metaheuristic: classification of population and trajectory

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…Algorithms are used to find the solutions through the computer program. …”
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  2. 2
    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem

    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

    Published 2008
    “…Genetic Algorithm gives a pool of solutions rather than just one. …”
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  3. 3
    Solving transcendental equation using genetic algorithm / Masitah Hambari

    Solving transcendental equation using genetic algorithm / Masitah Hambari by Masitah , Hambari

    Published 2004
    “…Genetic Algorithm is used to find the roots or set of optimal solution that satisfy the equation. …”
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  4. 4
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…For each considered case, results demonstrate that Jaya algorithm can produce a global optimum solution with rapid convergence. …”
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  5. 5
    Comparison Between Linear Programming And Integer Linear Programming: A Review

    Comparison Between Linear Programming And Integer Linear Programming: A Review by Sam, Mei Lee, Saptari, Adi, Salleh, Mohd Rizal, Mohamad, Effendi

    Published 2018
    “…Heuristics are not guaranteed to obtain optimal solutions, compared to exact algorithms.…”
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  6. 6
    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali

    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

    Published 2015
    “…It has been found that by implementing the ACP algorithm, the solution predicted is approximately close or similar to the exact solution. …”
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  7. 7
    Explicit solution of parameter estimate using multiparametric programming for boost converter

    Explicit solution of parameter estimate using multiparametric programming for boost converter by Mid, E.C., Mukhtar, N.M., Syed Yunus, S.H., Abdul Hadi, Dayanasari, Ruslan, Eliyana

    Published 2023
    “…This work proposes an approach to estimate the parameters of capacitance and inductance in a boost converter using an explicit solution. A multiparametric programming (MPP) algorithm is fundamental to the suggested methodology, which aims to develop parameters as explicit functions of measurements. …”
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  8. 8
    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language

    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language by Jano, Zanariah, Omar, Norliza, Nazir, Faridah

    Published 2019
    “…The students were to arrange the basic words into grammatical sentences based on the scratch program and write a cake recipe using an algorithmic technique, a series of instructions contained in the scratch program. …”
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  9. 9
    Solving Sudoku puzzles in Binary Integer Linear Programming using Branch and Bound algorithm / Ahida Waliyyah Ahmad Fuad

    Solving Sudoku puzzles in Binary Integer Linear Programming using Branch and Bound algorithm / Ahida Waliyyah Ahmad Fuad by Ahmad Fuad, Ahida Waliyyah

    Published 2024
    “…The puzzle starts with a partially filled grid provided by the setter, and it usually has a unique solution. This study explores the application of a Binary Integer Linear Programming (BILP) model combined with the Branch and Bound (B&B) algorithm to solve Sudoku puzzles. …”
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  10. 10
    Parallel Homologous Search With Hirschberg Algorithm: A Hybrid MPI-Pthreads Solution.

    Parallel Homologous Search With Hirschberg Algorithm: A Hybrid MPI-Pthreads Solution. by Abdul Rashid, Nur'Aini, Abdullah, Rosni, Hj. Talib, Abdullah Zawawi

    Published 2007
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  11. 11
    Algorithm as a problem solving technique for teaching and learning of the Malay language

    Algorithm as a problem solving technique for teaching and learning of the Malay language by Faridah Nazir, Zanariah Jano, Norliza Omar

    Published 2019
    “…The students were to arrange the basic words into grammatical sentences based on the scratch program and write a cake recipe using an algorithmic technique, a series of instructions contained in the scratch program. …”
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  12. 12
    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly

    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

    Published 2023
    “…Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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  13. 13
    Solving load flow solution using evolutionary programming method / Nurul-Huda Ismail

    Solving load flow solution using evolutionary programming method / Nurul-Huda Ismail by Ismail, Nurul-Huda

    Published 2003
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  14. 14
    The solution of 2048 puzzle game using A* algorithm / Zafhira Ismail

    The solution of 2048 puzzle game using A* algorithm / Zafhira Ismail by Ismail, Zafhira

    Published 2017
    “…The input data of this project is retrieved from the game’s rule itself and implemented with the proposed algorithm which is A* algorithm. The output of this project is the best solution to achieve the goal using A* algorithm. …”
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  15. 15
    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi

    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

    Published 2015
    “…The initial feasible solutions have been generated for this purpose. The solutions have been significantly improved by the algorithms. …”
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  16. 16
    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul

    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul by Siaw Ying Doreen, Sek

    Published 2023
    “…The VNS algorithm is used to improve the obtained solutions in the improvement phase. …”
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  17. 17
    Vehicle Routing Problem with Simultaneous Pickup and Delivery

    Vehicle Routing Problem with Simultaneous Pickup and Delivery by Sze, San Nah, Sek, Siaw Ying Doreen, Sze, Jeeu Fong, Cheah, Wai Shiang, Chiew, Kang Leng

    Published 2020
    “…A simple heuristic is used to generate the initial solution in the first phase. …”
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  18. 18
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…Results of the experiments that were conducted using various data sets showed that the proposed algorithm produced better course schedule solution than the Greedy Algorithm, Genetic Algorithm, and other variants of Ant System Algorithm.…”
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  19. 19
    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming

    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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  20. 20
    Recent research in cooperative path planning algorithms for multi-agent using mixed- integer linear programming

    Recent research in cooperative path planning algorithms for multi-agent using mixed- integer linear programming by Che Ku, Nor Azie Hailma, Omar, Rosli, Sabudin Elia Nadira, Sabudin Elia Nadira

    Published 2016
    “…This paper will review and compare the performances of those existing methods that can find solution without graph search algorithm such as Mixed-Integer Linear Programming (MILP) techniques which exactly solves the problem and then propose four alternative MILP formulations which are computationally less intensive and suited for real-time purposes, but yield a theoretically guaranteed suboptimal solution.…”
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