Search Results - (( logistics implementation a algorithm ) OR ( java application optimized algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Article -
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Reverse logistics network optimizing by genetic algorithm: a case study of automotive wiring harnesses
Published 2014“…Thus, an evolutionary algorithm based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model and find the optimum solution. …”
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Article -
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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CHAOS AND PUBLIC KEY INFRASTRUCTURE (PKI)
Published 2004“…A major problem faced in this implementation has been solved while implementing the new logistic map scheme. …”
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Final Year Project -
9
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…In this work, two AP selection algorithms are proposed which are Max Kernel and Kernel Logistic Discriminant that implement the knowledge of kernel density estimate and logistic regression machine learning classification. …”
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Thesis -
10
Using genetic algorithm in implementing capacitated vehicle routing problem
Published 2023Conference paper -
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Chaotic-based encryption algorithm using henon and logistic maps for fingerprint template protection
Published 2020“…The performance proposed encryption algorithm was promising which could be a starting point for detailed analysis and implementation in real application domains.…”
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Article -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
16
Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…Therefore, various meta-heuristic algorithms have been tried by researchers. In this research, a new Multi-Objective Logistics Network Model for Automotive Closed-Loop Supply Chain (MOACLSC) for recovering ELVs was developed. …”
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Thesis -
17
Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
18
Real time traceability module for halal logistic transportation using GPS and geofence technique
Published 2016“…A user acceptance test has been implemented and most of the respondents agreed that this module will benefit the Halal logistic provider in providing data on real time traceability. …”
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Thesis -
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Thesis -
20
Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…Information gain was used in the feature selection and four classification algorithms namely, Logistic Regression, Random Forest, Decision Tree, and Gradient Boosted, were implemented and tested with the incorporation of 10-fold cross-validation and splitting 70:30 in WEKA. …”
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