Search Results - (( problem representation search algorithm ) OR ( java application optimization algorithm ))

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  1. 1

    A comparative representation approach to modern heuristic search methods in a job shop by Dominic P, Dhanapal Durai, Ahmad, Kamil, Parthiban, P, Lenny Koh, SC

    Published 2008
    “…This research article addresses the problem of static job shop scheduling on the job-based representation and the rule-based representations. …”
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    Citation Index Journal
  2. 2

    A review of crossover methods and problem representation of genetic algorithm in recent engineering applications by Zainuddin, Farah Ayiesya, Abd Samad, Md Fahmi

    Published 2020
    “…This paper reviews crossover methods and problem representation, e.g. in the form of binary coded and real coded representation, used by researchers in order to solve engineering operations. …”
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    Article
  3. 3

    An Ant Colony Search Algorithm (ACSA) approach for unit commitment problem / Mohamad Masri Mohamad Jaib by Mohamad Jaib, Mohamad Masri

    Published 2010
    “…This thesis presents an Ant Colony Search Algorithm (ACSA) to solve unit commitment problem. …”
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    Thesis
  4. 4

    An Ant Colony Search Algorithm (ACSA) approach for unit commitment problem: article / Mohamad Masri Mohamad Jaib by Mohamad Jaibt, Mohamad Masri

    Published 2010
    “…This thesis presents an Ant Colony Search Algorithm (ACSA) to solve unit commitment problem. …”
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    Article
  5. 5

    A Micro-Genetic Algorithm Approach for Soft Constraint Satisfaction Problem in University Course Scheduling by Abd. Halim, Bohadean @ Bohari

    Published 2013
    “…The Micro Genetic Algorithm proposed has been tested in a test comparison with the Standard Genetic algorithm and the Guided Search Genetic algorithm as a benchmark. …”
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    Thesis
  6. 6

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…In order to accomplish better performance by improving the search quality and efficiency of the discrete MOPSO, this research proposes a hybrid with the Diversification Generation Method in Scatter Search, the non-dominated sorting mechanism in non-dominated sorting Genetic Algorithm II (NSGA-II) and the local search mechanism in Tabu Search. …”
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    Thesis
  7. 7

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, Norwati, Sulaiman, Md. Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2002
    “…Structure used in typical algorithms for solving this problem operate in several database scans and a large number of candidate generation. …”
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    Article
  8. 8

    Compact structure representation in discovering frequent patterns for association rules by Mustapha, N., Sulaiman, M.N., Othman, M., Selamat, M.H.

    Published 2002
    “…Structure used in typical algorithms for solving this problem operate in several database scans and a large number of candidate generation. …”
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    Article
  9. 9

    A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem by M. F. F., Ab Rashid

    Published 2017
    “…Design/methodology/approach – The ASP problem is formulated by using task-based representation. …”
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    Article
  10. 10

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
    “…JSSP generates a huge search space. An iterative forward-backward pass which reduces search space has been shown to produce significant improvement in reducing makespan in other field of scheduling problem. …”
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    Thesis
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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
  13. 13

    A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

    Published 2009
    “…In this study, we propose an Optimised Crossover Genetic Algorithm (OCGA) for the problem. The objective is to find a schedule which minimises the maximum lateness of the jobs in the presence of the sequence independent family setup times.In brief, the proposed OCGA uses binary representation to encode the problem. …”
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    Conference or Workshop Item
  14. 14

    Effective query structuring with ranking using named entity categories for XML retrieval by Roko, Abubakar

    Published 2016
    “…The systems focus on user query representation, user search intention identification and ranking algorithms to improve keyword search. …”
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    Thesis
  15. 15

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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    Article
  16. 16

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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    Thesis
  17. 17

    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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    Image matching using relational graph representation by Lai, Chui Yen

    Published 2005
    “…Feature-based matching algorithm cannot tackle the problem of matching ambiguities easily. …”
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    Thesis
  20. 20

    A combinatorial optimization technique using genetic algorithm :a case study in machine layout problem by Lau, Yung Siew.

    Published 2007
    “…Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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    Final Year Project Report / IMRAD