A tutorial on multiobjective optimization: fundamentals and evolutionary methods
MTM Emmerich, AH Deutz - Natural computing, 2018 - Springer
In almost no other field of computer science, the idea of using bio-inspired search paradigms
has been so useful as in solving multiobjective optimization problems. The idea of using a …
has been so useful as in solving multiobjective optimization problems. The idea of using a …
Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently
The amino acid sequence of a protein affects both its structure and its function. Thus, the
ability to modify the sequence, and hence the structure and activity, of individual proteins in …
ability to modify the sequence, and hence the structure and activity, of individual proteins in …
Multi-objective optimisation using evolutionary algorithms: an introduction
K Deb - Multi-objective evolutionary optimisation for product …, 2011 - Springer
As the name suggests, multi-objective optimisation involves optimising a number of
objectives simultaneously. The problem becomes challenging when the objectives are of …
objectives simultaneously. The problem becomes challenging when the objectives are of …
Multi-objective optimization
CONTENTS 3.1 Introduction.................................................... 146 3.2 MO
Basics..................................................... 1463.2. 1 Principles of MO............................................ 147 …
Basics..................................................... 1463.2. 1 Principles of MO............................................ 147 …
A multi-facet survey on memetic computation
Memetic computation is a paradigm that uses the notion of meme (s) as units of information
encoded in computational representations for the purpose of problem-solving. It covers a …
encoded in computational representations for the purpose of problem-solving. It covers a …
A unified evolutionary optimization procedure for single, multiple, and many objectives
Traditionally, evolutionary algorithms (EAs) have been systematically developed to solve
mono-, multi-, and many-objective optimization problems, in this order. Despite some efforts …
mono-, multi-, and many-objective optimization problems, in this order. Despite some efforts …
Particle swarm optimization with sequential niche technique for dynamic finite element model updating
F Shabbir, P Omenzetter - Computer‐Aided Civil and …, 2015 - Wiley Online Library
Due to uncertainties associated with material properties, structural geometry, boundary
conditions, and connectivity of structural parts as well as inherent simplifying assumptions in …
conditions, and connectivity of structural parts as well as inherent simplifying assumptions in …
Shear wave travel time estimation from petrophysical logs using ANFIS-PSO algorithm: A case study from Ab-Teymour Oilfield
M Anemangely, A Ramezanzadeh… - Journal of Natural Gas …, 2017 - Elsevier
Among petrophysical logs, shear wave velocity is known to provide more accurate results in
terms of mechanical rock properties. However, due to higher costs associated with acquiring …
terms of mechanical rock properties. However, due to higher costs associated with acquiring …
A method for constrained multiobjective optimization based on SQP techniques
We propose a method for constrained and unconstrained nonlinear multiobjective
optimization problems that is based on an SQP-type approach. The proposed algorithm …
optimization problems that is based on an SQP-type approach. The proposed algorithm …
Lévy flight artificial bee colony algorithm
Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-
based probabilistic approach for global optimisation. The solution search equation of ABC is …
based probabilistic approach for global optimisation. The solution search equation of ABC is …