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TripICS-a Web Service Composition System for Planning Trips and Travels

Niewiadomski A., Switalski P., Kowalczyk M., Penczek W.

Fundamenta Informaticae

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2018

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Vol. 157, nr 4

403--425

EN

We present the web service composition system TripICS, which allows for an easy and user-friendly planning of visits to interesting cities and places around the world in combination with travels, arranged in the way satisfying the user’s requirements. TripICS is a specialization of the concrete planning of PlanICS viewed as a constrained optimization problem to the ontology containing services provided by hotels, airlines, railways, museums etc. The system finds an optimal plan by applying a modification of the most efficient concrete planner of PlanICS based on a combination of an SMT-solver with the algorithm GEO. The modification has been designed in order to solve quickly multiple equality constraints. The efficiency of the new planning algorithm is proved by experimental results.

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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.

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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.

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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.

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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.