Iskanje po katalogu digitalne knjižnice

Opis: Fair comparison with state-of-the-art evolutionary algorithms is crucial, but is obstructed by differences in problems, parameters, and stopping criteria across studies. Metaheuristic frameworks can help, but often lack clarity on algorithm versions, improvements, or deviations. Some also restrict parameter configuration. We analysed source codes and identified inconsistencies between implementations. Performance comparisons across frameworks, even with identical settings, revealed significant differences, sometimes even with the authors’ own code. This questions the validity of comparisons using such frameworks. We provide guidelines to improve open-source metaheuristics, aiming to support more credible and reliable comparative studies.
Ključne besede: metaheuristics, evolutionary algorithm, metaheuristic optimization framework, algorithm comparison, benchmarking
Objavljeno v DKUM: 02.10.2025; Ogledov: 0; Prenosov: 4
Celotno besedilo (3,89 MB)

Opis: In this thesis we were discussing an analysis of numerical optimization algorithms from the most important aspect, that is exploration and exploitation. We focused on 2-dimensional and 3-dimensional unconstrained continuous functions, which were used to test the recently proposed metric based on attraction basins. The metric does not need any user-defined parameters. Attraction basins were expounded more profoundly and extensively. Our algorithm to calculate them consists of three steps such as making potential boundaries, filling, and then removing false boundaries from attraction basins. Results show that our algorithm is barely satisfying, depends on a particular problem function used. For example, attraction basins from Rastrigin, Schwefel, Ackley and similar functions (including all unimodal ones) were calculated accurately, while more special functions like Michalewicz, Shubert and Branin were proved to be not so easy. Further, we arbitrarly selected two algorithms, Particle Swarm Optimization and Self-adapting Differential Evolution, not for comparative study, rather to test the metric based on attraction basins. Results implied the relevance of recently proposed metric, and opened us a fruitful field for further investigation.
Ključne besede: exploration, exploitation, attraction basins, optimization, metaheuristic
Objavljeno v DKUM: 04.11.2020; Ogledov: 889; Prenosov: 95
Celotno besedilo (1,76 MB)