Results 221 to 230 of about 172,422 (234)

A novel particle swarm optimizer for many-objective optimization

2019 IEEE Congress on Evolutionary Computation (CEC), 2019
A novel many-objective particle swarm optimization (PSO) algorithm called IDMOPSO is presented in this study to robustly and effectively address many-objective optimization problems (MaOPs). IDMOPSO is based on a performance indicator and direction vectors.
Jianping Luo, Xiongwen Huang, Xia Li, Kaizhou Gao   +3 more
openaire   +1 more source

Clustering-Based Selection for Evolutionary Many-Objective Optimization

2014
This paper discusses a selection scheme allowing to employ a clustering technique to guide the search in evolutionary many-objective optimization. The underlying idea to avoid the curse of dimensionality is based on transforming the objective vectors before applying a clustering and the selection of cluster representatives according to the distance to ...
Denysiuk, Roman, Costa, Lino, Espírito Santo, I. A. C. P.   +2 more
openaire   +2 more sources

Constrained many-objective optimization: A way forward

2009 IEEE Congress on Evolutionary Computation, 2009
Many objective optimization is a natural extension to multi-objective optimization where the number of objectives are significantly more than five. The performance of current state of the art algorithms (e.g. NSGA-II, SPEA2) is known to deteriorate significantly with increasing number of objectives due to the lack of adequate convergence pressure.
Dhish Kumar Saxena, Tapabrata Ray, Kalyanmoy Deb, Ashutosh Tiwari   +3 more
openaire   +1 more source

Two novel approaches for many-objective optimization

IEEE Congress on Evolutionary Computation, 2010
In this paper, two novel evolutionary approaches for many-objective optimization are proposed. These algorithms integrate a fine-grained ranking of solutions to favor convergence, with explicit methodologies for diversity promotion in order to guide the search towards a representative approximation of the Pareto-optimal surface.
Mario Garza-Fabre, Gregorio Toscano-Pulido, Carlos A. Coello Coello   +2 more
openaire   +1 more source

Evolutionary multi- and many-objective optimization

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021
Kalyanmoy Deb, Julian Blank
openaire   +1 more source

An Introduction to Many-Objective Evolutionary Optimization

2020
This chapter describes the differences between single-objective, multi-objective, and many-objective optimization problems. In multi- and many-objective optimization, often the objectives are conflicting; hence there is no single best point, and a trade-off between the objectives must be considered.
Dani Irawan, Boris Naujoks
openaire   +1 more source

Many-Objective Optimization with Limited Computing Budget

2019
Designers are increasingly being confronted with practical applications that require solution of optimization problems with more than three conflicting objectives. In recent years, a number of efficient algorithms have been proposed to deal with such problems, commonly referred to as many-objective optimization problems (MaOP).
Kalyan Shankar Bhattacharjee, Hemant Kumar Singh, Tapabrata Ray   +2 more
openaire   +1 more source

Many-Objective Optimal Control for Quadcopters

2023 American Control Conference (ACC), 2023
Xinhuang Wu, Yousef Sardahi
openaire   +1 more source

Surrogate-Assisted Many-Objective Evolutionary Optimization

2021
Yaochu Jin, Handing Wang, Chaoli Sun
openaire   +1 more source

Decomposition and Coordination for Many-Objective Optimization

2022
Margaret M. Wiecek, Philip J. de Castro
openaire   +1 more source