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    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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    Article
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    Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows by Sankor, Salah Mortada Shahen

    Published 2022
    “…The Artificial Bee Colony (ABC) is a popular swarm intelligence algorithm for COP. In this study, existing Modified ABC (MABC) algorithm is revised to solve the VRPTW. …”
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    Thesis
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    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
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    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
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    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
    “…Similarly, the algorithm proposed in MALESAbrain can, be used to deal, the problem of conducting a meeting among learners to solve problems. …”
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    Article
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    Optimizing schedule of boarding school using vertex and edge coloring approach / Nurhuda Ismail, Siti Sarah Raseli and Nur Farhana Mohd Asri by Ismail, Nurhuda, Raseli, Siti Sarah, Mohd Asri, Nur Farhana

    Published 2021
    “…Greedy Algorithm has been used to solve the Vertex Coloring approach while Graph Coloring Algorithm has been used to solve the Edge Coloring approach. …”
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    Article
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    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

    Published 2024
    “…Thus, this research aims to extend the application of ANN to solve FFDE with power law kernel in Caputo sense (FFDEPC) by develop a vectorized algorithm based on deep feedforward neural network that consists of multiple hidden layer (DFNN-2H) with Adam optimization. …”
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    Article
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    DEVELOPMENT OF A MULTI-OBJECTIVE OPTIMZATION FRAMEWORK FOR INDUSTRIAL PROCESSES by GANESAN, TIMOTHY

    Published 2014
    “…The knowledge obtained from the above explorations was then used to construct a novel framework for solving these problems efficiently. …”
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    Thesis
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    Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

    Published 2015
    “…The results show that the extraction algorithm has been able to extract 100 % of the information correctly. …”
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    Thesis
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    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

    Published 2009
    “…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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    Book Chapter
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    Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

    Published 2015
    “…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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    Conference or Workshop Item
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    Web intelligence: A fuzzy knowledge-based framework for the enhancement of querying and accessing web data by Jaafar, J., Danyaro, K.U., Liew, M.S.

    Published 2015
    “…The chapter also provides the completeness fuzzy knowledge-based algorithm, which was used to determine the robustness and adaptability of the knowledge base. …”
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    Book
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    Modified Nsga-Iii As A Many-Objective Optimization Technique For Ab Initio Protein Structure Prediction by Smadi, Motasem Mohammad Yaqoob Al

    Published 2024
    “…Furthermore, this study proposes four novel objectives from three distinct energy function types with the goal of solving as a MOOP. In this regard, the first two objectives are derived from the physics-based energy function (PEF) which decomposes into bond and nonbond terms. …”
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    Thesis