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Maddalena Nonato, Davide Bertozzi, Marco Gavanelli, Andrea Peano.

A network model for routing-fault-free wavelength selection in WRONoCs design

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Abstract: Emerging technologies in on-chip communication domain bring about new combinatorial optimization problems at design automation. We address the Wavelength Selection Problem in Wavelength-Routed Optical Networks-on-Chip (WRONoCs), where wavelengths act as signal carriers for initiator-to-target communication, so that signals are the least interfering and routing faults are prevented. We present this novel engineering problem and model it as a constrained shortest path on acyclic networks, propose a graph-based mathematical formulation and an iterative procedure on incremental graphs to solve the model on realistic data.

Marco Gavanelli, Maddalena Nonato, Andrea Peano. An ASP approach for the valves positioning optimization in a water distribution system. Journal of Logic and Computation 2013; doi: 10.1093/logcom/ext065

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Positioning of valves is a real-life issue in Water Distribution System (WDS) design and, currently, it is usually addressed by hydraulic engineers either by hand or by means of genetic algorithms, that give no assurance of optimality. Since a given valves placement identifies a sectorization of the WDS in several isolable portions, the valves positioning problem can be seen as a variant of the well known graph partitioning problem, which is a hard combinatorial problem. Cattafi et al. (2011, TPLP, 11, 731–747) showed recently that Computational Logic can provide technologies and techniques that can be exploited to model and achieve the optimal partition of the water network (i.e. the optimal positioning of valves). In particular, the authors tackled the optimization of the valves positioning through a two player game model, giving a Constraint Logic Programming formalization to solve it effectively. The aim of this article, instead, is to investigate the potential of Answer Set Programming in this practical application; evaluation is in terms both of language expressivity and solving efficiency. Results are discussed for different ASP models and a comparison with the CLP(FD) technique shown by Cattafi et al. (2011, TPLP, 11, 731–747) will be given.

Keywords: Answer set programming, isolation system design, valves positioning, hydroinformatics.

Marco Gavanelli, Maddalena Nonato, Andrea Peano, Stefano Alvisi, and Marco Franchini. Genetic algorithms for scheduling devices operation in a water distribution system in response to contamination events. In J.-K. Hao and M. Middendorf, editors, EvoCop 2012, volume 7245 of Lecture Notes in Computer Science, pages 124-135, Berlin Heidelberg, 2012. Springer-Verlag.

PDF ©Springer-Verlag, Berlin Heidelberg, 2012. This is the author's version of the work. It is posted here by permission of Springer-Verlag for your personal use. Not for redistribution. The definitive version was published in J.-K. Hao and M. Middendorf (Eds.): EvoCOP 2012, LNCS 7245, pp. 124-135, 2012 and is available at http://www.springerlink.com/content/q072186n51501m44/

This paper heuristically tackles a challenging scheduling problem arising in the field of hydraulic distribution systems in case of a contamination event, that is, optimizing the scheduling of a set of tasks so that the consumed volume of contaminated water is minimized. Each task consists of manually activating a given device, located on the hydraulic network of the water distribution system. In practice, once contamination has been detected, a given number of response teams move along the network to operate each device on site. The consumed volume of contaminated water depends on the time at which each device is operated, according to complex hydraulic laws, so that the value associated to each schedule must be evaluated by a hydraulic simulation.

We explore the potentials of Genetic Algorithms as a viable tool for tackling this optimization-simulation problem. In particular, we compare different encodings and propose ad hoc cross over operators that exploit the combinatorial structure of the feasible region, featuring hybridization with Mixed Integer Linear Programming.

Computational results are provided for a real life hydraulic network of average size, showing the effectiveness of the approach. Indeed, we greatly improve upon common sense inspired solutions which are adopted in practice.

Keywords: Hybrid Genetic Algorithms, Simulation-Optimization, Scheduling

Marco Alberti, Massimiliano Cattafi, Federico Chesani, Marco Gavanelli, Evelina Lamma, Paola Mello, Marco Montali, and Paolo Torroni. A computational logic application framework for service discovery and contracting. International Journal of Web Services Research, 8(3):1-25, July-September 2011.

PDF This paper appears in International Journal of Web Services Research July-September 2011, Vol. 8, No. 3 edited by Liang-Jie Zhang © 2011, IGI Global, www.igi-global.com. Posted by permission of the publisher.

In Semantic Web technologies, searching for a service means to identify components that can potentially satisfy the user needs in terms of inputs and outputs (discovery), and devise a fruitful interaction with the customer (contracting). In this paper, we present an application framework that encompasses both the discovery and the contracting steps, in a unified search process. In particular, we accommodate service discovery by ontology-based reasoning, and contracting by reasoning about behavioural interfaces, published in a formal language. To this purpose, we consider a formal approach grounded on Computational Logic. We define, illustrate and evaluate a framework, called SCIFF Reasoning Engine (SRE), which can establish if a Semantic Web Service and a requester can fruitfully inter-operate, by computing a possible interaction plan based on the behavioural interfaces of both. The same operational machinery used for contracting can be used for runtime verification.

Keywords: Web services, semantic discovery, contracting, rules, analysis, abductive logic programming, proof procedure, interoperability

Marco Gavanelli, Fabrizio Riguzzi, Michela Milano, Davide Sottara, Alessandro Cangini, and Paolo Cagnoli. An application of fuzzy logic to strategic environmental assessment. In Roberto Pirrone and Filippo Sorbello, editors, AI*IA 2011: Artificial Intelligence Around Man and Beyond - XIIth International Conference of the Italian Association for Artificial Intelligence, Palermo, Italy, September 15-17, 2011. Proceedings, volume 6934 of Lecture Notes in Artificial Intelligence, pages 324-335. Springer Verlag, 2011.

PDF ©Springer-Verlag, Berlin Heidelberg, 2011. This is the author's version of the work. It is posted here by permission of Springer-Verlag for your personal use. Not for redistribution. The definitive version was published in AI*IA 2011: Artificial Intelligence Around Man and Beyond, Lecture Notes in Computer Science Volume 6934, 2011, pp 324-335 and is available at http://link.springer.com/chapter/10.1007%2F978-3-642-23954-0_30

Strategic Environmental Assessment (SEA) is used to evaluate the environmental effects of regional plans and programs. SEA expresses dependencies between plan activities (infrastructures, plants, resource extractions, buildings, etc.) and environmental pressures, and between these and environmental receptors. In this paper we employ fuzzy logic and many-valued logics together with numeric transformations for performing SEA. In particular, we discuss four models that capture alternative interpretations of the dependencies, combining quantitative and qualitative information. We have tested the four models and presented the results to the expert for validation. The interpretability of the results of the models was appreciated by the expert that liked in particular those models returning a possibility distribution in place of a crisp result.

PDF ©Springer-Verlag, Berlin Heidelberg, 2008. This is the author's version of the work. It is posted here by permission of Springer-Verlag for your personal use. Not for redistribution. The definitive version was published in N.T. Nguyen and R. Katarzyniak, editors, "New Challenges in Applied Intelligence Technologies", number 134 in Studies in Computational Intelligence. Springer-Verlag, Heidelberg, Germany, 2008 and is available at www.springerlink.com

Cancer screening is a method of preventing cancer by early detecting and treating abnormalities. One of the most critical screening phase is invitation planning since screening resources are limited and there are many people to invite. For this reason, smart resource allocation approaches are needed.

In the paper, we propose and compare two solutions for smart invitation plan definition, one based on greedy approaches and one based on Constraint Programming techniques that enable the definition of the optimal invitation plan.

Keywords: Constraint Programming, Scheduling, Greedy Algorithm