A case study on problem classification
Peter Korošec (Avtor), Tome Eftimov (Avtor)

Povzetek

Characterization of the optimization problem is a crucial task in many recent optimization research topics (e.g., explainable algorithm performance assessment, and automated algorithm selection and configuration). The state-of-the-art approaches use exploratory landscape analysis to represent the optimization problem, where for each one, a set of features is extracted using a set of candidate solutions sampled by a sampling strategy over the whole decision space. This paper proposes a novel representation of continuous optimization problems by encoding the information found in the interaction between an algorithm and an optimization problem. The new problem representation is learned using the information from the states/positions in the optimization run trajectory (i.e., the candidate solutions visited by the algorithm). With the novel representation, the problem can be characterized dynamically during the optimization run, instead of using a set of candidate solutions from the whole decision space that have never been observed by the algorithm. The novel optimization problem representation is called Opt2Vec and uses an autoencoder type of neural network to encode the information found in the interaction between an optimization algorithm and optimization problem into an embedded subspace. The Opt2Vec representation efficiency is shown by enabling different optimization problems to be successfully identified using only the information obtained from the optimization run trajectory.

Ključne besede

računalništvo;algoritmi;optimizacija;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: IJS - Institut Jožef Stefan
Založnik: Elsevier
UDK: 004
COBISS: 207123459 Povezava se bo odprla v novem oknu
ISSN: 0020-0255
Št. ogledov: 28
Št. prenosov: 7
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: računalništvo;algoritmi;optimizacija;
Strani: 20 str.
Letnik: ǂVol. ǂ680
Zvezek: ǂArt. ǂ121134
Čas izdaje: 2024
DOI: 10.1016/j.ins.2024.121134
ID: 25491646