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  1. 1
    Self-similar network traffic using Random Midpoint Displacement (RMD) algorithm / Jumaliah Saarini

    Self-similar network traffic using Random Midpoint Displacement (RMD) algorithm / Jumaliah Saarini by Saarini, Jumaliah

    Published 2006
    “…The way to solve this problem, we applied the existed method in visual C++ programming with used the Random midpoint Displacement (RMD) algorithm. …”
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  2. 2
    Garbage truck staff duty roster using genetic algorithm / Nadea Suneeza Zulkifli

    Garbage truck staff duty roster using genetic algorithm / Nadea Suneeza Zulkifli by Zulkifli, Nadea Suneeza

    Published 2017
    “…This technique is used because studies have shown reasonably good results when genetic algorithms are applied to the staff-scheduling problem. …”
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  3. 3
    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance

    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…The LP’s application is need to be further computed with a technique and Simplex algorithm is the one that commonly used. The Simplex algorithm has three stages of computation namely initialization, iterative calculation and termination. …”
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  4. 4
    Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim

    Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim by Huda Zuhrah , Ab Halim

    Published 2019
    “…A new MILP for DSIRPB is formulated and used within the algorithm. The DSIRPB is modeled as stochastic dynamic programming and solved using hybrid rollout algorithm. …”
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  5. 5
    African Buffalo Optimization and the Randomized Insertion Algorithm for the Asymmetric Travelling Salesman’s Problems

    African Buffalo Optimization and the Randomized Insertion Algorithm for the Asymmetric Travelling Salesman’s Problems by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad, Odili, Esther Abiodun

    Published 2016
    “…This paper presents a comparative study of the African Buffalo Optimization algorithm and the Randomized Insertion Algorithm to solving the asymmetric Travelling Salesman’s Problem with the overall objective of determining a better method to solving the asymmetric Travelling Salesman’s Problem instances. …”
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  6. 6
    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes

    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes by Nor Atiqah, Zolpakar, Lodhi, Swati Singh, Pathak, Sunil, Sharma, Mohita Anand

    Published 2020
    “…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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  7. 7
    A Comparative Study of African Buffalo Optimization and Randomized Insertion Algorithm for Asymmetric Travelling Salesman's Problem

    A Comparative Study of African Buffalo Optimization and Randomized Insertion Algorithm for Asymmetric Travelling Salesman's Problem by Odili, Julius Beneoluchi, M. N. M., Kahar, Shahid, Anwar, Azrag, M. A. K.

    Published 2015
    “…In this study, a comparative study of the African Buffalo Optimization algorithm and the Randomized Insertion Algorithm to solving the asymmetric Travelling Salesman's Problem is made with the aim of ascertaining a better method to solving the asymmetric Travelling Salesman's Problem instances. …”
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  8. 8
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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  9. 9
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…This PhD thesis introduces an extended version of MABSA aimed at addressing constrained multi objective optimization problems by incorporating innovative random approaches, focusing to solves reservoir optimization problems. …”
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  10. 10
    E-Raser: file shredder application with content replacement by using random words function

    E-Raser: file shredder application with content replacement by using random words function by Mohd Nahar, Nur Farah Aqilah, Ab Rahman, Nurul Hidayah, Mohammad, Kamarudin Malik

    Published 2018
    “…Thus, this study proposed a file shredding application named E-Raser which replacing the content of the file using random words function algorithm. A file shredder application named E-Raser was developed to shred Microsoft Word documents with (.doc) or (.docx) format. …”
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  11. 11
    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul

    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul by Siaw Ying Doreen, Sek

    Published 2023
    “…VRPB is a Non-deterministic Polynomial-time hard (NP-hard) problem. The huge data size has increased the difficulty of solving it using mathematical programming or combinatorial optimisation. …”
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  12. 12
    The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem

    The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem by Pook, Mei Foong, Ramlan, Effirul Ikhwan

    Published 2019
    “…Benchmarking is conducted using the traveling salesman problem. The results are comparable with the results of advanced metaheuristic algorithms. …”
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  13. 13
    Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem

    Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem by Razip, H., Zakaria, M.N.

    Published 2018
    “…We tested this approach by sampling the populations for some Set Covering Problems from OR Library using the randomized rounding method (AAR) and compared them with that sampled using a randomized heuristics (R) in terms of redundancy rate, diversity and closeness to the optimal solution (OPT). …”
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  14. 14
    Backward reduction application for minimizing wind power scenarios in stochastic programming

    Backward reduction application for minimizing wind power scenarios in stochastic programming by Muhamad Razali N.M., Hashim A.H.

    Published 2023
    “…These programs use a set of scenarios (or plausible realizations) and corresponding probabilities to model the multivariate random data process, e.g. electrical load, stream flows to hydro units, generation output of intermittent renewable sources as well as fuel and electricity prices. …”
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  15. 15
    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems

    Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. …”
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  16. 16
    Sentiment Analysis of Airline Reviews Using Naive Bayes Algorithm / Ahmad Firdaus Maliki

    Sentiment Analysis of Airline Reviews Using Naive Bayes Algorithm / Ahmad Firdaus Maliki by Maliki, Ahmad Firdaus

    Published 2021
    “…Several classifier models have been built by using Naive Bayes algorithm during the design and implementation phase where the model that has the highest accuracy has been chosen for this project. …”
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  17. 17
    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network

    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network by Puteri Azwa, Ahmad

    Published 2014
    “…The implementation of the EVFCS improved the problems of initial random deployment.…”
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  18. 18
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    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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  19. 19
    Genetic Mutation of Cowpea as a Constrained Stochastic Optimization Problem in Sustainability

    Genetic Mutation of Cowpea as a Constrained Stochastic Optimization Problem in Sustainability by Emmanuel, Okewu, Kehinde, Okewu, Siti Sarah, Maidin, Wong, Ling Shing

    Published 2023
    “…However, uncertainties surround the genetic engineering process, potentially making genetic mutation for sustainability a constrained stochastic optimization (CSO) problem. Using series of experiments in Python programming, we applied genetic algorithm to the genetic mutation of cowpea, a tropical leguminous plant and protein-rich crop. …”
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  20. 20
    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management

    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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