A5052002490- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Advanced Multi-Objective Optimization Algorithms
- Topology Optimization in Engineering
- Artificial Immune Systems Applications
- Protein Structure and Dynamics
- Computational Drug Discovery Methods
- Reinforcement Learning in Robotics
- T-cell and B-cell Immunology
- Optimization and Mathematical Programming
- Probabilistic and Robust Engineering Design
- Optimization and Variational Analysis
- Immune Cell Function and Interaction
- Advanced Numerical Methods in Computational Mathematics
- RNA and protein synthesis mechanisms
- Gene Regulatory Network Analysis
- Advanced Optimization Algorithms Research
- Numerical methods in engineering
- Machine Learning and Data Classification
- Process Optimization and Integration
- Electromagnetic Simulation and Numerical Methods
- Advanced Manufacturing and Logistics Optimization
- CRISPR and Genetic Engineering
- Neural Networks and Applications
- Data Stream Mining Techniques
Laboratório Nacional de Computação Científica
2016-2025
Universidade Federal de Juiz de Fora
2014-2024
Hospital Universitário - Universidade Federal de Juiz de Fora
2018
National Council for Scientific and Technological Development
1992-2003
Abstract The COVID-19 caused by the SARS-CoV-2 virus was declared a pandemic disease in March 2020 World Health Organization (WHO). Structure-Based Drug Design strategies based on docking methodologies have been widely used for both new drug development and repurposing to find effective treatments against this disease. In work, we present developments implemented DockThor-VS web server provide virtual screening (VS) platform with curated structures of potential therapeutic targets from...
Abstract A parameter‐less adaptive penalty scheme for genetic algorithms applied to constrained optimization problems is proposed. Using feedback from the evolutionary process procedure automatically defines a parameter each constraint. The user thus relieved burden of having determine sensitive parameter(s) when dealing with every new problem. shown be effective and robust test computation literature as well several structural engineering literature. Copyright © 2003 John Wiley & Sons, Ltd.
Bilevel programming problems are characterized by two optimization which hierarchically related, where to each feasible upper level solution an optimal in the lower problem must be associated. These appear many practical applications, and a variety of techniques can found literature. In this paper, algorithm is proposed uses differential evolution solve both problems. Several test from literature solved order assess performance method.
A genetic algorithm (GA) is hybridized with an artificial immune system (AIS) as alternative to tackle constrained optimization problems in engineering. The AIS inspired the clonal selection principle and embedded into a standard GA search engine order help move population feasible region. procedure applied mechanical engineering available literature compared other techniques.
Abstract The bilevel programming problem is characterized as an optimization that has another in its constraints. leader the upper level and follower lower are hierarchically related where leader's decisions affect both follower's payoff function allowable actions, vice versa. One difficulty arises solving problems unless a solution optimal for problem, it cannot be feasible overall problem. This suggests approximate methods could not used they do guarantee actually found. However, from...
Presents an implementation of symbolic regression which is based on genetic programming (GP). Unfortunately, standard implementations GP in compiled languages are not usually the most efficient ones. The present approach employs a simple representation for tree-like structures by making use Read's linear code, leading to more simplicity and better performance when compared with traditional implementations. Creation, crossover mutation individuals formalized. An extension allowing creation...
A genetic algorithm (GA) is hybridized with an artificial immune system (AIS) as alternative to tackle constrained optimization problems in engineering. The AIS inspired the clonal selection principle and embedded into a standard GA search engine order help move population feasible region. procedure applied mechanical engineering available literature compared other techniques.
Performance profiles are an analytical tool for the visualization and interpretation of results benchmark experiments. In this paper we discuss their explanatory power, argue that they should be more widely used by evolutionary computation community. We also introduce some novel performance measures which can extracted from profiles. order to illustrate potential, apply referred analysis CEC 2006 constrained optimization competition. While corroborated, new facts pointed out additional...
Abstract One variant of the ant colony optimization (ACO) metaheuristic, known as rank‐based system (RBAS), is proposed for weight minimization structures involving discrete design variables. Stress and displacements constraints are handled using a penalty technique, structural analysis performed by finite element method. Results obtained several problems show that RBAS algorithm implemented effective competitive when compared with results found genetic algorithms another variant. Copyright...
Bilevel programming is used to model decentralized problems involving two levels of decision makers that are hierarchically related. Those problems, which arise in many practical applications, recognized be challenging. This paper reports a Differential Evolution (DE) method assisted by surrogate solve bilevel (BLPs). The proposed an extension previous one, BlDE, developed the authors, where DE methods generate and evolve upper lower level variables. Here, use similarity-based model,...
de novo Drug Design (dnDD) aims to create new molecules that satisfy multiple conflicting objectives. Since several desired properties can be considered in the optimization process, dnDD is naturally categorized as a many-objective problem (ManyOOP), where more than three objectives must simultaneously optimized. However, large number of typically pose challenges affect choice and design methodologies. Herein, we cover application multi- methods, particularly those based on Evolutionary...