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  1. 1
    Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application

    Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application by Hardhienata, Medria Kusuma Dewi, Priandana, Karlisa, Putra, Daffa Rangga, Sriatun, Mamiek, Wulandari, Buono, Agus, Mohamed, Raihani

    Published 2024
    “…Simulation results showed that the proposed ACO algorithm with the modified efficiency factor improved the performance of basic ACO algorithm for solving task allocation problem in terms of the average total travel cost for each agent. …”
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  2. 2
    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation

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

    Published 2022
    “…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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  3. 3
    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…The four prime aspects of this work are: firstly, a model of the grid scheduling problem for dynamic grid computing environment; secondly, development of a new web based simulator (SyedWSim), enabling the grid users to conduct a statistical analysis of grid workload traces and provides a realistic basis for experimentation in resource allocation and job scheduling algorithms on a grid; thirdly, proposal of a new grid resource allocation method of optimal computational cost using synthetic and real workload traces with respect to other allocation methods; and finally, proposal of some new job scheduling algorithms of optimal performance considering parameters like waiting time, turnaround time, response time, bounded slowdown, completion time and stretch time. …”
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  4. 4
    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm

    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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    Academic Exercise
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  5. 5
    Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm

    Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm by Lorpunmanee, Siriluck, Sap, M.N.M, Abdullah, Abdul Hanan, Srinoy, Surat

    Published 2006
    “…The minimization is proposed by using a multiple objective genetic algorithm (GA), because the job scheduling problem is NP-hard problem. …”
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  6. 6
    Solving Airport Gate Allocation Problem Using Angle Modulated Simulated Kalman Filter

    Solving Airport Gate Allocation Problem Using Angle Modulated Simulated Kalman Filter by Kamil Zakwan, Mohd Azmi, Zulkifli, Md. Yusof, Siti Nurzulaikha, Satiman, Badaruddin, Muhammad, Saifudin, Razali, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd Aziz

    Published 2016
    “…In this study, the airport gate allocation problem is solved using a recently introduced angle modulated simulated Kalman filter (AMSKF). …”
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  7. 7
    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean

    Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

    Published 2007
    “…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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  8. 8
    Evalution of binary simulated Kalman filter and its application on airport gate scheduling

    Evalution of binary simulated Kalman filter and its application on airport gate scheduling by Zarifah, Mohamad Nor

    Published 2016
    “…In this study, the airport gate allocation problem is solved using extended version of Simulated Kalman Filter algorithm called Binary Simulated Kalman Filter (BSKF).The main objective of this study is to minimize the total walking distance of passengers either from a gate to entrance/exit or gate to a gate. …”
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    Undergraduates Project Papers
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  9. 9
    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers

    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2022
    “…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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  10. 10
    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network

    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

    Published 2022
    “…The first proposed algorithm aims to optimize the EE by controlling the on/off status of RRH via a deep Q network (DQN) and subsequently solving a power optimization problem. …”
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    Final Year Project / Dissertation / Thesis
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  11. 11
    Optimal power flow using the Jaya algorithm

    Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2016
    “…This paper presents application of a new effective metaheuristic optimization method namely, the Jaya algorithm to deal with different optimum power flow (OPF) problems. …”
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  12. 12
    Incorporating genetic algorithm into simulated annealing based redistricting

    Incorporating genetic algorithm into simulated annealing based redistricting by Sim, Kwan Hua.

    Published 2002
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  13. 13
    Solving Airport Gate Allocation Problem using Simulated Kalman Filter

    Solving Airport Gate Allocation Problem using Simulated Kalman Filter by Zulkifli, Md. Yusof, Siti Nurzulaikha, Satiman, Kamil Zakwan, Mohd Azmi, Badaruddin, Muhammad, Saifudin, Razali, Zuwairie, Ibrahim, Zulfakar, Aspar, Suraya, Ismail

    Published 2016
    “…Since the airport gate allocation problem is a combinatorial optimization problem, the original SKF is extended such that it can be used to solve combinatorial optimization problems. …”
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  14. 14
    Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm

    Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm by Altrad, Abdallah Mahmoud Mousa

    Published 2018
    “…The main goal of this work is to develop a conceptual framework and mathematical model for resource allocation using Shuffled Frog-Leap Algorithm (SFLA). …”
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  15. 15
    Dijkstra’s Algorithm for optimal recyclable waste collection system in Port Dickson / Nur Jazlina Mohd Iszairi, Aina Zulaika Md Ramli and Nursabrina Saifulbahri

    Dijkstra’s Algorithm for optimal recyclable waste collection system in Port Dickson / Nur Jazlina Mohd Iszairi, Aina Zulaika Md Ramli and Nursabrina Saifulbahri by Mohd Iszairi, Nur Jazlina, Md Ramli, Aina Zulaika, Saifulbahri, Nursabrina

    Published 2023
    “…The data are collected from Google Map and are applied in Excel Solver using the Dijkstra’s Algorithm. Based on the simulation conducted, the results show the optimal route for the recyclable waste collection with minimum travel distance where the travel distance from Depot to C13 is 2386 meters, from C13 to D42 is 2555 meters and from D42 back to the Depot is 2407 meters. …”
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    Student Project
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  16. 16
    Solving university examination timetabling problem using intelligent water drops algorithm

    Solving university examination timetabling problem using intelligent water drops algorithm by Aldeeb B.A., Norwawi N.M., Al-Betar M.A., Jali M.Z.B.

    Published 2024
    Conference Paper
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  17. 17
    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…Simulated Kalman Filter (SKF) solves optimization problems by finding the estimate of the optimum solution. …”
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  18. 18
    Adaptive and optimized radio resource allocation algorithms for OFDMA based networks

    Adaptive and optimized radio resource allocation algorithms for OFDMA based networks by Saadat, Md. Nazmus

    Published 2015
    “…AORAA contains an adaptive and optimized subcarrier allocation algorithm which uses graph theoretic techniques to do the best probable matching of subcarrier and users’ channel information. …”
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  19. 19
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone. …”
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  20. 20
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
    “…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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