Results 41 to 50 of about 299,863 (342)
Multiplicative Approximations, Optimal Hypervolume Distributions, and the Choice of the Reference Point [PDF]
, 2013 Many optimization problems arising in applications have to consider several objective functions at the same time. Evolutionary algorithms seem to be a very natural choice for dealing with multi-objective problems as the population of such an algorithm ...
Friedrich, Tobias +2 more
core +2 more sources
Hybridization of multi-objective deterministic particle swarm with derivative-free local searches [PDF]
, 2020 The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems.
Diez, M. +5 more
core +2 more sources
Complex & Intelligent Systems, 2021 Surrogate-assisted optimization has attracted much attention due to its superiority in solving expensive optimization problems. However, relatively little work has been dedicated to addressing expensive constrained multi-objective discrete optimization ...
Qinghua Gu +4 more
semanticscholar +1 more source
A similarity-based cooperative co-evolutionary algorithm for dynamic interval multi-objective optimization problems [PDF]
, 2019 The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Dynamic interval multi-objective optimization problems (DI-MOPs) are very common in real-world applications.
Gong, Dunwei +4 more
core +1 more source
Journal of Applied Research on Industrial Engineering, 2018 The design of Renewable Energy Power Plants (REPPs) is crucial not only for the investments' performance and attractiveness measures, but also for the maximization of resource (source) usage (e.g.
Burak Omer Saracoglu +1 more
doaj +1 more source
, 2017 Multi-Objective Optimization Problems (MOPs) have attracted growing attention during the last decades. Multi-Objective Evolutionary Algorithms (MOEAs) have been extensively used to address MOPs because are able to approximate a set of non-dominated high ...
Berretta, Regina +3 more
core +1 more source
Development of a Multi-Objective Evolutionary Algorithm for Strain-Enhanced Quantum Cascade Lasers [PDF]
, 2016 An automated design approach using an evolutionary algorithm for the development of quantum cascade lasers (QCLs) is presented. Our algorithmic approach merges computational intelligence techniques with the physics of device structures, representing a ...
Mueller, David, Triplett, Gregory Edward
core +4 more sources
Evolutionary Multi-Objective Algorithms
, 2012 The versatility that genetic algorithm (GA) has proved to have for solving different problems, has make it the first choice of researchers to deal with new challenges. Currently, GAs are the most well known evolutionary algorithms, because their intuitive principle of operation and their relatively simple implementation; besides they have the ability ...
Torres, Aurora +4 more
openaire +3 more sources
Case-base maintenance with multi-objective evolutionary algorithms [PDF]
Journal of Intelligent Information Systems, 2015 Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solving ability of the Case-Base Reasoning system.
Lupiani, Eduardo +4 more
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu +14 more
wiley +1 more source