Search Results for author:
Found 14 papers, 3 papers with code
The importance of being constrained: dealing with infeasible solutions in Differential Evolution and beyond
Here, we demonstrate that, at least in algorithms based on Differential Evolution, this choice induces notably different behaviours - in terms of performance, disruptiveness and population diversity.
Direct deduction of chemical class from NMR spectra
This paper presents a proof-of-concept method for classifying chemical compounds directly from NMR data without doing structure elucidation.
Deep-BIAS: Detecting Structural Bias using Explainable AI
Recently, the BIAS toolbox was introduced as a behaviour benchmark to detect structural bias (SB) in search algorithms.
Structural bias in population-based algorithms
Theory predicts that structural bias is exacerbated with increasing population size and problem difficulty.
Compact Optimization Algorithms with Re-sampled Inheritance
The resulting compact algorithms with RI are tested on the CEC 2014 benchmark functions.
Multi-Strategy Coevolving Aging Particle Optimization
We propose Multi-Strategy Coevolving Aging Particles (MS-CAP), a novel population-based algorithm for black-box optimization.
Infeasibility and structural bias in Differential Evolution
This paper thoroughly investigates a range of popular DE configurations to identify components responsible for the emergence of structural bias - recently identified tendency of the algorithm to prefer some regions of the search space for reasons directly unrelated to the objective function values.
Training Data Set Assessment for Decision-Making in a Multiagent Landmine Detection Platform
Real-world problems such as landmine detection require multiple sources of information to reduce the uncertainty of decision-making.
Differential evolution outside the box
A wide range of popular Differential Evolution configurations is considered in this study.
Is there Anisotropy in Structural Bias?
We find that anisotropy is very rare, and even in cases where it is present, there are clear tests for SB which do not rely on any assumptions of isotropy, so we can safely expand the suite of SB tests to encompass these kinds of deficiencies not found by the original tests.
Emergence of Structural Bias in Differential Evolution
Heuristic optimisation algorithms are in high demand due to the overwhelming amount of complex optimisation problems that need to be solved.
Modular Differential Evolution
Although these contributions are often compared to the base algorithm, it is challenging to make fair comparisons between larger sets of algorithm variants.
Patterns of Convergence and Bound Constraint Violation in Differential Evolution on SBOX-COST Benchmarking Suite
This study investigates the influence of several bound constraint handling methods (BCHMs) on the search process specific to Differential Evolution (DE), with a focus on identifying similarities between BCHMs and grouping patterns with respect to the number of cases when a BCHM is activated.
Context-Aware Quantitative Risk Assessment Machine Learning Model for Drivers Distraction
We also study the correlation between distraction (driver, vehicle, and environment) and the classification severity based on a continuous distraction severity score.
