Supplier Selection using NSGA-II Technique
International Journal of Web Portals, 2012 In modern manufacturing industries, supplier selection is increasingly recognized as a critical decision in supply chain management. Supplier selection problem is a typical multiple criteria decision making problem involving a number of different and usually conflicting objectives.
Vladimir Rankovic +5 more
openaire +2 more sources
NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training
Algorithms, 2023 This paper presents NSGA-PINN, a multi-objective optimization framework for the effective training of physics-informed neural networks (PINNs). The proposed framework uses the non-dominated sorting genetic algorithm (NSGA-II) to enable traditional ...
Binghang Lu, Christian Moya, Guang Lin
doaj +1 more source
Modeling and Optimal Design of Machining-Induced Residual Stresses in Aluminium Alloys Using a Fast Hierarchical Multiobjective Optimization Algorithm [PDF]
, 2011 The residual stresses induced during shaping and machining play an important role in determining the integrity and durability of metal components. An important issue of producing safety critical components is to find the machining parameters that create ...
Christophe Pinna +10 more
core +1 more source
Dynamic multi‐objective optimisation of complex networks based on evolutionary computation
IET Networks, EarlyView., 2022 Abstract As the problems concerning the number of information to be optimised is increasing, the optimisation level is getting higher, the target information is more diversified, and the algorithms are becoming more complex; the traditional algorithms such as particle swarm and differential evolution are far from being able to deal with this situation ...
Linfeng Huang
wiley +1 more source
Proposal and Comparative Study of Evolutionary Algorithms for Optimum Design of a Gear System [PDF]
, 2019 This paper proposes a novel metaheuristic framework using a Differential Evolution (DE) algorithm with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II).
Frutos, Mariano +3 more
core +1 more source
Multi-objective discrete particle swarm optimisation algorithm for integrated assembly sequence planning and assembly line balancing [PDF]
, 2016 In assembly optimisation, assembly sequence planning and assembly line balancing have been extensively studied because both activities are directly linked with assembly efficiency that influences the final assembly costs.
Ab Rashid, Mohd Fadzil Faisae +2 more
core +1 more source
An Analysis on Selection for High-Resolution Approximations in Many-Objective Optimization [PDF]
, 2014 This work studies the behavior of three elitist multi- and many-objective evolutionary algorithms generating a high-resolution approximation of the Pareto optimal set.
Aguirre, Hernan +3 more
core +3 more sources
An improved knowledge-informed NSGA-II for multi-objective land allocation (MOLA)
Geo-spatial Information Science, 2018 Multi-objective land allocation (MOLA) can be regarded as a spatial optimization problem that allocates appropriate use to certain land units subjecting to multiple objectives and constraints.
Mingjie Song, Dongmei Chen
doaj +1 more source
A First Runtime Analysis of the NSGA-II on a Multimodal Problem
IEEE Transactions on Evolutionary Computation, 2022 Appeared in the Transactions on Evolutionary Computation.
Benjamin Doerr, Zhongdi Qu
openaire +3 more sources
Multiobjective synchronization of coupled systems [PDF]
, 2011 Copyright @ 2011 American Institute of PhysicsSynchronization of coupled chaotic systems has been a subject of great interest and importance, in theory but also various fields of application, such as secure communication and neuroscience. Recently, based
Blekhman I. I. +7 more
core +1 more source