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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

“…This implementation will be based on parallel distributed model, which will reduce the complexity of each microcontroller to solve large complex problem and increase problem solving speed. � 2008 IEEE.…”

Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

“…While quantitative technique is based on statistical concepts and requires large amount of data in order to formulate the mathematical models.This technique can be classified into projective and causal technique.The projective technique (or univariate modelling) just involve one variable while the causal technique (or econometric modelling) suitable for multi-variables.Since forecasting involves uncertainty, several methods need to be executed on one set of time series data in order to produce accurate forecast.Hence, usually in practice forecaster need to use several softwares to obtain the forecast values.If this practice can be transformed into algorithm (well-defined rules for solving a problem) and then the algorithm can be transformed into a computer program, less time will be needed to compute the forecast values where in business world time is money.In this study, we focused on algorithm development for univariate forecasting techniques only and will expand towards econometric modelling in the future.Two set of simulated data (yearly and non-yearly) and several univariate forecasting techniques (i.e. …”
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Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

“…For solving this problem, the aforesaid algorithms have been applied. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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Genetic algortihm to solve pcb component placement modeled as travelling salesman problem by Mohd Khazzarul Khazreen, Mohd Zaidi

“…This thesis discuss about Genetic Algorithm to solve PCB component placement modeled as Travelling Salesman Problem (TSP). …”
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Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

“…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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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…A hybrid Particle Swarm Optimization-Bacterial Foraging Algorithm is developed for solving the single objective LIRP model. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

“…In this paper, an efficient computational algorithm is proposed to solve the nonlinear optimal control problem. …”
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Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

“…Four methodologies are to make four different CM models to solve MRO problems. The fifth methodology proposes the final algorithm which uses four CM models together to solve MRO problems. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

“…In this paper, an efficient computational algorithm is proposed to solve the nonlinear optimal control problem. …”
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Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

“…These four algorithms can be used to solve discrete combinatorial optimization problems (COPs). …”
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Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem by Nurdiyana, Jamil

“…Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. …”
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An algorithm model for solving the single-period inventory transportation problems in the construction industry by Mohd Kamarul Irwan Abdul Rahim

“…An algorithm model for solving the single-period inventory transportation problems in the construction industry by Mohd Kamarul Irwan Abdul Rahim…”
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Development of Hybrid Algorithm for Integrated Aircraft Routing Problem and Crew Pairing Problem by NurulFarihan Mohamed, ZaitulMarlizawati Zainuddin, Said Salhi, Nurul Huda Mohamed, NurulAkmal Mohamed

Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

“…The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups. …”
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Solving single machine scheduling problem with maximum lateness using a genetic algorithm by Nazif, Habibeh, Lee, Lai Soon

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Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm by Muhamad Rozikin, Kamaluddin, M. F. F., Ab Rashid

“…Specific optimization model and algorithm were developed to solve the problem. …”
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OPTIMISED UNIT COMMITMENT AND DYNAMIC ECONOMIC DISPATCH FOR LARGE SCALE POWER SYSTEMS by Ab Ghani, Mohd Ruddin

“…A second modelling strategy and solution algorithm for solving the same problem is also investigated. …”
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