Advances in Data-Driven Computing and Intelligent Systems
Selected Papers from ADCIS 2023, Volume 4
Page
%P
213 Result(s)
within
Carlos A. Coello Coello
-
Book and Conference Proceedings
-
Book and Conference Proceedings
-
Book and Conference Proceedings
-
Book and Conference Proceedings
-
Article
Open AccessOn the automatic design of multi-objective particle swarm optimizers: experimentation and analysis
Research in multi-objective particle swarm optimizers (MOPSOs) progresses by proposing one new MOPSO at a time. In spite of the commonalities among different MOPSOs, it is often unclear which algorithmic compo...
-
Article
Thematic issue on advances in analysis and application of multi-objective memetic optimization algorithms
-
Chapter and Conference Paper
A Novel Performance Indicator Based on the Linear Assignment Problem
Evaluating the performance of Multi-Objective Evolutionary Algorithms is complex since we have to assess different characteristics of the approximation sets that they generate. Over the years, a variety of per...
-
Chapter and Conference Paper
On the Computational Complexity of Efficient Non-dominated Sort Using Binary Search
Over the years, several approaches have been proposed to solve the problem of non-dominated sorting, which is one of the crucial steps in Pareto dominance-based multi-objective evolutionary algorithms (MOEAs)....
-
Chapter and Conference Paper
Recent Research Topics in Evolutionary Multiobjective Optimization: A Personal Perspective
The field which is now known as evolutionary multi-objective optimization (EMOO) started in the mid-1980s and since then, it has experienced a significant growth. In this chapter, we discuss some of the (sever...
-
Book and Conference Proceedings
-
Book and Conference Proceedings
-
Chapter and Conference Paper
Considerations in the Incremental Hypervolume Algorithm of the WFG
The hypervolume indicator (HV) has been subject of a lot of research in the last few years, mainly because its maximization yields near-optimal approximations of the Pareto optimal front of a multi-objective o...
-
Chapter and Conference Paper
An Extension of the iMOACO \(\mathbb {_R}\) Algorithm Based on Layer-Set Selection
iMOACO \(\mathbb {_R}\) is an ant colony optimization algorithm designed to tackle multi-objective optimization problems in continuous sea...
-
Chapter and Conference Paper
Automatic Design of Multi-objective Particle Swarm Optimizers
Multi-objective particle swarm optimizers (MOPSOs) have been widely used to deal with optimization problems having two or more conflicting objectives. As happens with other metaheuristics, finding the most ade...
-
Book and Conference Proceedings
Innovations in Intelligent Computing and Communication
First International Conference, ICIICC 2022, Bhubaneswar, Odisha, India, December 16-17, 2022, Proceedings
-
Chapter
Multi-objective Ant Colony Optimization: An Updated Review of Approaches and Applications
Ant colony optimization (ACO) is one of the most representative metaheuristics derived from the broad concept known as swarm intelligence (SI) where the behavior of social insects is the main source of inspira...
-
Chapter
An Overall Characterization of the Project Portfolio Optimization Problem and an Approach Based on Evolutionary Algorithms to Address It
This chapter describes the main features of project portfolio selection and formalizes a problem statement that considers these features. We provide a simple but comprehensive illustrative example that shows t...
-
Chapter and Conference Paper
The Influence of Swarm Topologies in Many-Objective Optimization Problems
Particle Swarm Optimization (PSO) is a bio-inspired metaheuristic that has been successfully adopted for single- and multi-objective optimization. Several studies show that the way in which particles are conne...
-
Chapter
The Importance of Diversity in Multi-objective Evolutionary Algorithms
This paper presents a very short overview of diversity in the context of multi-objective evolutionary algorithms. Besides emphasizing the importance of diversity maintenance when dealing with multi-objective o...
-
Chapter and Conference Paper
An Overview of Pair-Potential Functions for Multi-objective Optimization
Recently, an increasing number of state-of-the-art Multi-objective Evolutionary Algorithms (MOEAs) have incorporated the so-called pair-potential functions (commonly used to discretize a manifold) to improve t...
