Search Results - (( problem solving machine algorithm ) OR ( java application optimisation algorithm ))

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

“…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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Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources by Abed, Munther Hameed, Mohd Nizam Mohmad, Kahar

“…Here, we proposed genetic algorithm (GA) to solve the UPMR problem because of the robustness and the success of GA in solving many optimization problems. …”
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Genetic-local hybrid optimizer for solving advance layout problem by Taha, Imad, Ibrahim Habra, Hind Saleem

“…Results show the potentiality of the proposed algorithm in solving the problem and outperforming previous algorithms.…”
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

“…In the past few decades, there have been multiple algorithms proposed for the purpose of solving optimization problems including Machine Learning (ML) applications. …”

A combinatorial optimization technique using genetic algorithm :a case study in machine layout problem by Lau, Yung Siew.

“…Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

“…Genetic algorithm shows promising results in solving UPMR. …”
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Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

“…The results show proposed algorithm approximately solved problems averagely 22% better in terms of find feasible optimal solutions depends of various performance measures in 72.2% of computational time than other previous considered key algorithms.…”
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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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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective by Mousavi, Seyed Mohsen, Sadeghi R., Kiarash, Lee, Lai Soon

“…To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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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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Higher desirability in solving multiple response optimization problems with committee machine by Golestaneh, Seyed Jafar, Ismail, Napsiah, Mohd Ariffin, Mohd Khairol Anuar, Tang, Sai Hong, Naeini, Hassan Moslemi, Maghsoudi, Ali Asghar, Firoozi, Zahra

“…Committee machine (CM) as a set of some experts such as some artificial neural networks (ANNs) in combination with genetic algorithm (GA) is applied for modeling and optimization of MRO problems. …”
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Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

“…The purpose of this study is to develop the application of Particle Swarm Optimization (PSO) which applicable to CNC machine route problem. In this project, the problem of CNC machine can be identifying by routing problem which it become more complicated to solve without use of any optimization method. …”
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

“…Besides, concept drift problem in on-line learning model is solved by Drift Detection Machine (DDM). …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Review on bio-inspired algorithms approach to solve assembly line balancing problem by Noorazliza, Sulaiman, Junita, Mohamad Saleh, Nor Rokiah Hanum, Md. Haron, Z. A., Kamaruzzaman

“…Bio-inspired algorithms that have been developed by mimicking the biological phenomenon of nature have been widely applied to solve many real-world problems. …”
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Performance optimization of simultaneous machine and automated guided vehicle scheduling using fuzzy logic controller based genetic algorithm. by Sulaiman, Shamsuddin, Mohd Ariffin, Mohd Khairol Anuar, Badakshian, Mostafa

“…Previously, genetic algorithm (GA) is considered as a heuristic method to solve AGVscheduling problem. …”
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Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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Optimization of Electrical Discharge Machining Process by Metaheuristic Algorithms by Zainal, Nurezayana, Sithambranathan, Mohanavali, Khattak, Umar Farooq, Mohd Zain, Azlan, A. Mostafa, Salama, Mat Deris, Ashanira

“…The study's outcome showed that the GWO algorithm outperformed the GSO and WOA algorithms in solving the EDM optimization problem and achieved the minimum surface roughness value of 1.7593µm.…”
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Applications of Machine Learning in Networking: A Survey of Current Issues and Future Challenges by Ridwan M.A., Radzi N.A.M., Abdullah F., Jalil Y.E.