Search Results - (( problem application optimisation algorithm ) OR ( java application optimization algorithm ))
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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Application of adaptive bats sonar algorithm for solving a single objective of practical business optimisation problem PROBLEM
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Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm
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An Improved VEPSO Algorithm for Multi-objective Optimisation Problems
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Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm
Published 2019“…For optimisation purpose, this research proposed a relatively new algorithm called the Moth-Flame Optimisation (MFO). …”
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Optimization of multi-holes drilling path using particle swarm optimization
Published 2022“…The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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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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Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation
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