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  1. 1

    Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm by Abed, S.A., Rais, H.M.

    Published 2020
    “…This problem belongs to the NP-complete complexity class that cannot be solved exactly in a polynomial time. …”
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    Article
  2. 2

    The graph heuristic with great deluge algorithm to solve the ITC2007 examination timetabling problem by Chuan, Wei Kiat

    Published 2014
    “…This dataset contains of total of twelve dataset which have different features (i.e. number of room, exam and timeslot). The graph heuristic with great deluge algorithm will be used to solve this problem. …”
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    Undergraduates Project Papers
  3. 3

    Optimizing boarding school schedule using graph colouring : case study of Sekolah Menengah Sultan Abdul Halim / Nur Farhana Mohd Asri by Mohd Asri, Nur Farhana

    Published 2021
    “…Greedy Algorithm is used to solve the Vertex Coloring approach meanwhile Graph Coloring Algorithm is used to solve the Edge Coloring approach. …”
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    Student Project
  4. 4

    Optimizing boarding school schedule using graph coloring: case study of Sekolah Menengah Sultan Abdul Halim / Nur Farhana Mohd Asri by Mohd Asri, Nur Farhana

    Published 2022
    “…Greedy Algorithm is used to solve the Vertex Coloring approach meanwhile Graph Coloring Algorithm is used to solve the Edge Coloring approach. …”
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    Research Reports
  5. 5

    Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

    Published 2015
    “…The complexity of combinatorial problems is classified as NP meaning that algorithms are yet to exist to efficiently solve the problem. …”
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    Thesis
  6. 6

    Path Optimization For Cooperative Multi-Head 3d Printing by Cheong, Kah Jun

    Published 2020
    “…Two well-known algorithms for solving a closely related graph theory problem known as the Travelling Salesman Problem (TSP) are the Ant System (AS) and Ant Colony System (ACS) algorithms. …”
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    Final Year Project / Dissertation / Thesis
  7. 7

    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…When compared to the Ant Colony Optimization algorithm, Simulated Annealing and Genetic Algorithm, the results obtained from African Buffalo Optimization show that the algorithm works well and can be extended to solving problems like: path planning, scheduling, vehicle routing in addition to other constraint-driven problems.…”
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    Article
  8. 8

    Graph theory-based radial load flow analysis to solve the dynamic network reconfiguration problem by Aman, M.M., Jasmon, G.B., Bakar, Ab Halim Abu, Mokhlis, Hazlie, Naidu, K.

    Published 2016
    “…This paper has presented an intelligent graph theory-based RLF analysis to solve "dynamic" problems. …”
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    Article
  9. 9

    Partial examination assignment approaches for solving examination timetabling problems by Mandal, Ashis Kumar

    Published 2016
    “…We have implemented partial graph heuristic with hill climbing (PGH-HC) and partial graph heuristic with modified great deluge algorithm (PGH-mGD) into solving the examination timetabling. …”
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    Thesis
  10. 10

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…Although the swmcan algorithm solves the noise problem in multi-view data, its initial and final graphs are independent and cannot learn from each other. …”
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    Thesis
  11. 11

    Solving single machine scheduling problem with maximum lateness using a genetic algorithm by Nazif, Habibeh, Lee, Lai Soon

    Published 2010
    “…We develop an optimised crossover operator designed by an undirected bipartite graph within a genetic algorithm for solving a single machine family scheduling problem, where jobs are partitioned into families and setup time is required between these families. …”
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    Article
  12. 12

    Combination of Graph Heuristic with Hill Climbing Search for Solving Capacitated Examination Timetabling Problem by Ashis Kumar, Mandal, M. N. M., Kahar

    Published 2015
    “…The algorithm starts with ordering all the exams according to graph heuristic approach and then partial exams are considered for construction. …”
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    Conference or Workshop Item
  13. 13

    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

    Published 2018
    “…Background and Objective: The process of solving the Maximum Clique (MC) problem through approximation algorithms is harder, however, the Maximum Vertex Cover (MVC) problem can easily be solved using approximation algorithms. …”
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    Article
  14. 14

    A comparative study of greedy algorithms and dynamic programming in road network / Nuralya Sofea Hairulanuar by Hairulanuar, Nuralya Sofea

    Published 2024
    “…Dijkstra's algorithm and A* algorithm have been shown to be very efficient for solving single-source shortest route problems. …”
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    Thesis
  15. 15

    Heuristic factors in ant system algorithm for course timetabling problem by Djamarus, Djasli, Ku-Mahamud, Ku Ruhana

    Published 2009
    “…This paper presents an algorithm that is based on ant system to solve the course timetabling problem.The problem is modeled using the bipartite graph.Four heuristic factors are derived from the graph characteristic, are used to direct ants as the agent in finding course timetable elements The concept of negative pheromone was also applied to ensure that paths leading to dead ends are not chosen.The performance of this proposed algorithm is promising when comparison of performance was made with the original ant system algorithm. …”
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    Conference or Workshop Item
  16. 16

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

    Published 2009
    “…As a member of the NP Problem, an exact algorithm to solve the course scheduling problem is not available to date. …”
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    Thesis
  17. 17

    Performance analysis of graph heuristics and selected trajectory metaheuristics on examination timetable problem by Mandal, Ashis Kumar, Mohd Nizam Mohmad, Kahar

    Published 2020
    “…Examination timetabling problem is hard to solve due to its NP-hard nature, with a large number of constraints having to be accommodated. …”
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    Article
  18. 18
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    Performance analyses of graph heuristics and selected trajectory metaheuristics on examination timetable problem by Mandal, Ashis Kumar, M. N. M., Kahar

    Published 2020
    “…Examination timetabling problem is hard to solve due to its NP-hard nature, with a large number of constraints having to be accommodated. …”
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    Article
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