Results 21 to 30 of about 28,586 (232)
Multi-objective routing optimization using evolutionary algorithms [PDF]
, 2012 Wireless ad hoc networks suffer from several limitations, such as routing failures, potentially excessive bandwidth requirements, computational constraints and limited storage capability. Their routing strategy plays a significant role in determining the
Cheung, Kent Tsz Kan +2 more
core +1 more source
Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Preserving population diversity and providing knowledge, which are two core tasks in the dynamic multi‐objective optimisation (DMO), are challenging since the sampling space is time‐ and space‐varying. Therefore, the spatiotemporal property of evolutionary information needs to be considered in the DMO.
Qinqin Fan +3 more
wiley +1 more source
Optimal Parameter Design by NSGA-II and Taguchi Method for RCD Snubber Circuit
IEEE Access, 2020 A genetic algorithm and Taguchi method were used to optimize parameters for the residual-current device (RCD) snubber circuit of a DC-DC flyback converter. The most suitable algorithm was determined by using test functions to compare performance in three
Ying Ma +5 more
doaj +1 more source
An optimization method for nacelle design [PDF]
, 2017 A multi-objective optimiZation method is demonstrated using an evolutionary genetic algorithm. The applicability of this method to preliminary nacelle design is demonstrated by coupling it with a response surface model of a wide range of nacelle designs.
Heidebrecht, A. +2 more
core +1 more source
Case Studies in Thermal Engineering, 2023 A performance prediction model is built utilizing Slipcevie method and the experimental verification results show that the average errors of Q, ΔPt, ΔPs are 4.4%, 5.3%, 6.0%, respectively. Through parametric study of Ddo_i, Ddb, Nb by Sobol’ method based
Zhe Xu +5 more
doaj +1 more source
A Study of the Combination of Variation Operators in the NSGA-II Algorithm [PDF]
, 2013 Multi-objective evolutionary algorithms rely on the use of variation operators as their basic mechanism to carry out the evolutionary process. These operators are usually fixed and applied in the same way during algorithm execution, e.g., the mutation ...
Coello Coello, Carlos A. +4 more
core +2 more sources
Improved Crowding Distance for NSGA-II
CoRR, 2018 EC course ...
Xiangxiang Chu, Xinjie Yu
openaire +2 more sources
A Computational Comparison of Evolutionary Algorithms for Water Resource Planning for Agricultural and Environmental Purposes [PDF]
, 2018 The use of water resources for agricultural purposes, particularly in arid and semi-arid regions, is a matter of increasing concern across the world.
Fitzgerald, Andrew +3 more
core +2 more sources
Ingeniería e Investigación, 2020 Multi-Objective and Many-objective Optimization problems have been extensively solved through evolutionary algorithms over a few decades. Despite the fact that NSGA-II and NSGA-III are frequently employed as a reference for a comparative evaluation of ...
Luis Felipe Ariza Vesga +2 more
doaj +1 more source
Multiobjective genetic algorithm strategies for electricity production from generation IV nuclear technology [PDF]
, 2010 Development of a technico-economic optimization strategy of cogeneration systems of electricity/hydrogen, consists in finding an optimal efficiency of the generating cycle and heat delivery system, maximizing the energy production and minimizing the ...
Azzaro-Pantel, Catherine +5 more
core +2 more sources