Autor: Niewiadomski, J. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Combining SMT and Simulated Annealing into a Hybrid Planning Method
Autorzy:: Skaruz, J.
Niewiadomski, A.
Penczek, W.
Powiązania:: https://bibliotekanauki.pl/articles/92934.pdf
Data publikacji:: 2015
Wydawca:: Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:: concrete planning
genetic algorithm
satisfiability modulo theories
simulated annealing
web service composition
planics
Opis:: We present a new approach to the concrete planning (CP) - a stage of theWeb service composition in the PlanICS framework. A new hybrid algorithm (HSA) based on a combination of Simulated Annealing (SA) with Satisfiability Modulo Theories (SMT) has been designed and implemented. The main idea of our hybrid solution is to use an SMT-based procedure in order to generate an initial individual and then improve it during subsequent iterations of SA. The experimental results show that HSA is superior to the other methods we have applied to the CP problem, including Genetic Algorithm, an SMT-based approach, and our previously developed hybrids.
Źródło:: Studia Informatica : systems and information technology; 2015, 1-2(19); 43-48
1731-2264
Pojawia się w:: Studia Informatica : systems and information technology
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Solving the abstract planning problem using genetic algorithms
Autorzy:: Skaruz, J.
Niewiadomski, A.
Penczek, W.
Powiązania:: https://bibliotekanauki.pl/articles/93024.pdf
Data publikacji:: 2013
Wydawca:: Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:: abstract planning
genetic algorithms
web service composition
Opis:: The paper presents a new approach based on genetic algorithms to the abstract planning problem, which is the first stage of the web service composition problem. An abstract plan is defined as an equivalence class of sequences of service types that satisfy a user query. Intuitively, two sequences are equivalent if they are composed of the same service types, but not necessarily occurring in the same order. The objective of our genetic algorithm (GA) is to return representatives of abstract plans without generating all the equivalent sequences. The paper presents experimental results compared with the results obtained from SMT-solver, which show that GA finds solutions for very large sets of service types in a reasonable time.
Źródło:: Studia Informatica : systems and information technology; 2013, 1-2(17); 29-48
1731-2264
Pojawia się w:: Studia Informatica : systems and information technology
Dostawca treści:: Biblioteka Nauki

Artykuł

Informacja