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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…Later, this algorithm was used to solve bi-objective Production Planning (PP) and Scheduling Problem (Sch.P). …”
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    Thesis
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    An efficient method for determining all the extreme points of function with one variable by Pandiya, Ridwan

    Published 2014
    “…The algorithm is directly suitable for a class of problems of commonly used in solving the global optimization problems. …”
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    Thesis
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    Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…One classical engineering problem known as the welded beam structure problem is used to test the proposed LSMA algorithm's efficacy. …”
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    Conference or Workshop Item
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    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
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    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…Mathematical optimization was typical use for such problem, in which it was supposed to maximizing or minimizing a function. …”
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    Undergraduates Project Papers
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    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

    Published 2018
    “…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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    Thesis
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    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…We took advantage of Levy flight, which solved the local optima problem and improved traditional TSA efficiency. The proposed LTSA algorithm performance was evaluated using 23 well-known benchmark test functions, namely unimodal benchmark functions, multimodal benchmark functions, and fixed-dimension multimodal benchmark functions, as well as compared with the traditional TSA. …”
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    Conference or Workshop Item
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    New heuristic function in ant colony system for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak

    Published 2012
    “…Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with dynamic environment features to mimic the grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and make span.…”
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    Conference or Workshop Item
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    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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    Article
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    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
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