Search Results - (( java application bees algorithm ) OR ( surface optimization path algorithm ))

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  1. 1

    A novel fly optimization algorithm for swarming application by Zainal Abidin, Zulkifli, Ngah, Umi Kalthum, Arshad, Mohd Rizal, Ong, Boon Ping

    Published 2010
    “…This paper presents an initial development stage of Fly Optimization Algorithm which will be used for the path planning system of a swarm of autonomous surface vehicles. …”
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    Proceeding Paper
  2. 2

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    Published 2011
    “…Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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    Article
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    Development Of Generative Computer-Aided Process Planning System For Lathe Machining by Zubair, Ahmad Faiz

    Published 2019
    “…Furthermore, to minimize unit production cost, machining parameters including cutting speed (CS), feed rate (f) and depth of cut (d) were optimized for regular form surfaces by using firefly algorithm (FA). …”
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    Thesis
  6. 6

    Simulation of spline based NC- manufacturing of plastic optical components by Nik Anwar, Nik Syahrim, Mohd Rusdy , Yaacob, Md Sani, Zamani

    Published 2011
    “…A spline based postprocessor with integrated testing function is created with Matlab. The algorithm, optimization, and the results of the postprocessor will be discussed. …”
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    Conference or Workshop Item
  7. 7

    Performance evaluation of ultrasonic assisted wire electrical discharge turning for TI-6AL-4V material by Mohd Zakaria, Muhammad Akmal

    Published 2023
    “…After performing with multi-objective parameter optimization with the goal of maximising the MRR and minimising the surface roughness using genetic algorithm method, there is a 5.2% improvement for the MRR and 11.6%–27.9% improvement for surface roughness compared to conventional WEDT. …”
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    Thesis