Results 41 to 50 of about 5,089,183 (236)
Optimal Bespoke CDO Design via NSGA-II [PDF]
Journal of Applied Mathematics and Decision Sciences, 2009 This research work investigates the theoretical foundations and computational aspects of constructing optimal bespoke CDO structures. Due to the evolutionary nature of the CDO design process, stochastic search methods that mimic the metaphor of natural biological evolution are applied.
Diresh Jewan +2 more
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A Non-dominated Sorting Ant Colony Optimization Algorithm Approach to the Bi-objective Multi-vehicle Allocation of Customers to Distribution Centers [PDF]
Journal of Optimization in Industrial Engineering, 2016 Distribution centers (DCs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of
Jafar Bagherinejad, Mina Dehghani
doaj +1 more source
Mathematics, 2023 In this study, a bi-objective optimization model was established to solve the cooperative distribution problem of a multi-center hybrid fleet by integrating reverse logistics under real-time road conditions.
Mengke Li, Yongkui Shi, Meiyan Li
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Integrated LI-NSGA-II Approach for Solving the Non-linear Multi-objective Optimization Problem
Austrian Journal of StatisticsReal-world engineering projects frequently involve complex, non-linear multi-objective optimization challenges. Traditional methods like PERT/CPM and basic heuristics often fail to provide optimal solutions in such scenarios.
Muskan Kapoor +2 more
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Compact NSGA-II for Multi-objective Feature Selection
2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2023 Feature selection is an expensive challenging task in machine learning and data mining aimed at removing irrelevant and redundant features. This contributes to an improvement in classification accuracy, as well as the budget and memory requirements for classification, or any other post-processing task conducted after feature selection.
Sevil Zanjani Miyandoab +2 more
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Advanced Robotics Research, EarlyView.A codesign multiobjective optimization framework was developed to enhance the morphology and controller of a snake‐like robot driven by artificial muscles. It improved planar locomotion, agility, and power efficiency. The approach optimized link geometry and controller gains, revealing that shorter muscles near joints and longer linkages maximize ...
Ayla Valles, Mahdi Haghshenas‐Jaryani
wiley +1 more source
2-Phase NSGA II: An Optimized Reward and Risk Measurements Algorithm in Portfolio Optimization
Algorithms, 2017 Portfolio optimization is a serious challenge for financial engineering and has pulled down special attention among investors. It has two objectives: to maximize the reward that is calculated by expected return and to minimize the risk. Variance has been
Seyedeh Elham Eftekharian +2 more
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Multi-objective Optimization of Volute Springs using an Improved NSGA II [PDF]
International Journal of Advanced Design and Manufacturing Technology, 2020 Due to the variable stiffness through their length, their resistance against buckling, damping characteristics due to the friction between their chains, and their small solid length, volute springs are widely used in applications where other mechanisms ...
navid moshtaghi yazdani
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Collision‐Resilient Winged Drones Enabled by Tensegrity Structures
Advanced Robotics Research, EarlyView.Based on structures of birds such as the woodpeck, this article presents the collision‐resilient aerial robot, SWIFT. SWIFT leverages tensegrity structures in the fuselage and wings which allow it to undergo large deformations in a crash, without sustaining damage. Experiments show that SWIFT can reduce impact forces by 70% over conventional structures.
Omar Aloui +5 more
wiley +1 more source
Evaluation of Landslide Susceptibility Based on Multi-objective Optimization Method
Shuitu Baochi Xuebao[Objective] In the landslide susceptibility assessment, the selection and optimization of the landslide prediction model are very important to the efficiency of the calculation process and the accuracy of the prediction results.
ZHANG Xingcun +4 more
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