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1
Content available remote Concrete Planning in PlanICS Framework by Combining SMT with GEO and Simulated Annealing
Niewiadomski A., Skaruz J., Switalski P., Penczek W.
Fundamenta Informaticae
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2016
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Vol. 147, nr 2/3
289--313
EN
The paper deals with the concrete planning problem – a stage of the web service composition in the PlanICS framework. We present several known and new methods of concrete planning including those based on Satisfiability Modulo Theories (SMT), Genetic Algorithm (GA), as well as methods combining SMT with GA and other nature-inspired algorithms such as Simulated Annealing (SA) and Generalised Extremal Optimization (GEO). The discussion of all the approaches is supported by the complexity analysis, extensive experimental results, and illustrated by a running example.
2
Content available Combining SMT and Simulated Annealing into a Hybrid Planning Method
Skaruz J., Niewiadomski A., Penczek W.
Studia Informatica : systems and information technology
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2015
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Vol. 1-2(19)
43--48
EN
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.
3
Content available remote SMT Versus Genetic and OpenOpt Algorithms : Concrete Planning in the PlanICS Framework
Niewiadomski A., Skaruz J., Penczek W., Szreter M., Jarocki M.
Fundamenta Informaticae
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2014
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Vol. 135, nr 4
451--466
EN
The paper deals with the concrete planning problem (CPP) – a stage of the Web Service Composition (WSC) in the PlanICS framework. The complexity of the problem is discussed. A novel SMT-based approach to CPP is defined and its performance is compared to the standard Genetic Algorithm (GA) and the OpenOpt numerical toolset planner in the framework of the PlanICS system. The discussion of all the approaches is supported by extensive experimental results.
4
Content available Solving the abstract planning problem using genetic algorithms
Skaruz J., Niewiadomski A., Penczek W.
Studia Informatica : systems and information technology
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2013
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Vol. 1-2(17)
29--48
EN
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.
5
Content available remote Towards Automated Abstract Planning Based on a Genetic Algorithm
Skaruz J., Niewiadomski A., Penczek W.
Prace Instytutu Podstaw Informatyki Polskiej Akademii Nauk
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2012
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Nr 1026
1--32
EN
The paper presents a new approach based on nature inspired algorithms to an automated abstract planning problem, which is a part 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, which show that GA finds solutions for very large sets of service types in a reasonable time.
PL
Raport przedstawia nowe podejście do problemu planowania abstrakcyjnego za pomocą algorytmów genetycznych (AG). Problem planowania abstrakcyjnego polega na takiej kompozycji usług sieciowych, która spełnia zapytanie użytkownika. W raporcie pokazano sposób zastosowania AG do rozwiązania problemu planowania abstrakcyjnego oraz zaprezentowano wyniki eksperymentalne.
6
Content available Image reconstruction with the use of evolutionary algorithms and cellular automata
Seredyński F., Skaruz J., Piraszewski A.
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
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2012
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Vol. 12, no. 4
39--49
EN
In the paper we present a new approach to the image reconstruction problem based on evolution algorithms and cellular automata. Two-dimensional, nine state cellular automata with the Moore neighbourhood perform reconstruction of an image presenting a human face. Large space of automata rules is searched through efficiently by the genetic algorithm (GA), which finds a good quality rule. The experimental results show that the obtained rule allows to reconstruct an image with even 70% damaged pixels. Moreover, we show that the rule found in the genetic evolution process can be applied to the reconstruction of images of the same class but not presented during the evolutionary one.
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