Search Results - (( java implementation path algorithm ) OR ( program quality selection algorithm ))

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  1. 1

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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    Thesis
  2. 2

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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    Thesis
  3. 3

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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    Thesis
  4. 4

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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    Article
  5. 5

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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    Thesis
  6. 6

    Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

    Published 2022
    “…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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    Article
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    CSC099: Foundation Computing II / Centre of Foundation Studies by UiTM, Centre of Foundation Studies

    Published 2022
    “…This course introduces basic computer programming algorithm, problem solving, structured programming language, selection structure, repetition structure, function and array. …”
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    Teaching Resource
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    A Systematic Exploration of Mutation Space in a Hybridized Interactive Evolutionary Programming for Mobile Game Programming by Jia Hui Ong, Jason Teo

    Published 2014
    “…From the optimization results obtained, the single best individual was selected from each mutation rate to further analyze its quality. …”
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    Article
  10. 10

    Selecting quality initial random seed for metaheuristic pproaches: a case of timetabling problem by Md Sultan, Abu Bakar, Mahmod, Ramlan, Sulaiman, Md. Nasir, Abu Bakar, Mohd Rizam

    Published 2008
    “…This paper analyzes the effect of different random seed over metaheuristic performance. Techniques for selecting quality random seeding as an input for metaheuristic algorithm to solve university course timetabling are presented. …”
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    Article
  11. 11

    A Simulated Annealing Approach to Solve Fuzzy Multi-Objective Linear Model for Supplier Selection in a Supply Chain by Parthiban, P, Dominic P, Dhanapal Durai, dhanalakshmi, p

    Published 2010
    “…Finally the problem is solved by using simulated annealing algorithm to enable the decision-maker to select the right suppliers and allocate their quota in order to minimize the cost, maximize the quality level and again maximize the service level.…”
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    Conference or Workshop Item
  12. 12

    Differentiating Agarwood Oil Quality Using Artificial Neural Network by Saiful Nizam, Tajuddin, Nurlaila, Ismail, Nor Azah, Mohd Ali, Mailina, Jamil, Mohd Hezri, Fazalul Rahiman, Mohd Nasir, Taib

    Published 2013
    “…The ANN programming algorithm was developed and computed automatically via Matlab software version R2010a. …”
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    Article
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    Selection of prospective workers using profile matching algorithm on crowdsourcing platform by Cucus, Ahmad, Aji, Luhur Bayu, Al Fahim, Mubarak Ali, Aminuddin, Afrig, Farida, Lilis Dwi

    Published 2022
    “…This algorithm is able to select worker profiles from 10,000 datasets, up to 1148 people who are most suitable for the tasks offered. …”
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    Conference or Workshop Item
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    Computational Thinking Through Unplugged Programming Activities : Exploring Students’ Learning Experiences by Lim, Bih Loong

    Published 2019
    “…Based on their pre-test and post-test results, nine of them were selected for individual interview. The result shows that there is no significant effect of the learning material in increasing the participants’ algorithm skill. …”
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    Thesis
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    Cognitive selection mechanism performance in IEEE 802.11 WLAN by Hashim, Wahidah, Ismail, Ahmad Fadzil, Ghafar, Nadratul, Dzulkifly, Sumayyah

    Published 2013
    “…The results for the selection were evaluated respectively to see the variation in selection pattern when compared to the default selection algorithm. …”
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    Article
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    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…In process planning of conventional milling, selecting reasonable milling parameters is necessary to satisfy requirements involving machining economics, quality and safety. …”
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    Undergraduates Project Papers
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    An artificial bee colony-based double layered neural network approach for solving quadratic Bi-level programming problems by Watada, J., Roy, A., Wang, B., Tan, S.C., Xu, B.

    Published 2020
    “…The improved ABC algorithm accommodates upper-level decision problems by selecting a set of potential solutions from all combinations of solutions. …”
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    Article
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