Dealing with Fixable and Non-fixable Properties in Service Matchmaking

In the context of service discovery, matchmakers check the compliance of service-level objectives from providers and consumers. The problem of bounded uncertainty arises if some property is non-fixable. In this case, the provider is not able to control the value it takes at runtime, so the eventual consumer must not have the choice to select a value and fix it, but only knowing the guaranteed range of values it may take. To the best of our knowledge, there does not exist any approach which deals with this scenario. Most matchmakers work as if all properties were fixable, and a few have assumed the contrary. In either case, the accuracy of their results is likely to be in question since there may be involved both fixable and non-fixable properties at the same time, and there may also exist dependencies between them. In order to improve the accuracy, we present a holistic approach to matchmaking under bounded uncertainty and propose constraint programming as our choice to deal with it, so that matchmaking is transformed into a quantified constraint satisfaction problem.Comisión Interministerial de Ciencia y Tecnología TIN2006-00472Comisión Interministerial de Ciencia y Tecnología TIN2009- 07366Junta de Andalucía TIC-253

An Hybrid, Qos-Aware Discovery of Semantic Web Services Using Constraint Programming

Most Semantic Web Services discovery approaches are not well suited when using complex relational, arithmetic and logical expressions, because they are usually based on Description Logics. Moreover, these kind of expressions usually appear when discovery is performed including Quality-of-Service conditions. In this work, we present an hybrid discovery process for Semantic Web Services that takes care of QoS conditions. Our approach splits discovery into stages, using different engines in each one, depending on its search nature. This architecture is extensible and loosely coupled, allowing the addition of discovery engines at will. In order to perform QoS-aware discovery, we propose a stage that uses Constraint Programming, that allows to use complex QoS conditions within discovery queries. Furthermore, it is possible to obtain the optimal offer that fulfills a given demand using this approach.Comisión Interministerial de Ciencia y Tecnología TIN2006-0047

An Approach to Temporal-Aware Procurement of Web Services

Es también una ponencia de: International Conference on Service-Oriented Computing: ICSOC 2005: Service-Oriented Computing - ICSOC 2005 pp 170-184. book ISBN: 978-3-540-30817-1 e-ISBN: 978-3-540-32294-8In the context of web service procurement (WSP), temporal–awareness refers to managing service demands and offers which are subject to validity periods, i.e. their evaluation depends not only on quality of service (QoS) values but also on time. For example, the QoS of some web services can be considered critical in working hours (9:00 to 17:00 from Monday to Friday) and irrelevant at any other moment. Until now, the expressiveness of such temporal–aware specifications has been quite limited. As far as we know, most proposals have considered validity periods to be composed of a single temporal interval. Other proposals, which could allow more expressive time–dependent specifications, have not performed a detailed study about all the underlying complexities of such approach, in spite of the fact that dealing with complex expressions on temporality is not a trivial task at all. As a matter of fact, it requires a special design of the so–called procurement tasks (consistency and conformance checking, and optimal selection). In this paper, we present a constraint–based approach to temporal–aware WSP. Using constraints allows a great deal of expressiveness, so that not only demands and offers can be assigned validity periods but also their conditions can be assigned (possibly multiple) validity temporal subintervals. Apart from revising the semantics of procurement tasks, which we previously presented in the first edition of the ICSOC conferences, we also introduce the notion of the covering set of a demand, a topic which is closely related to temporality.Ministerio de Ciencia y Tecnología TIC2003-02737-C02-0

Two-agent scheduling in open shops subject to machine availability and eligibility constraints

Purpose: The aims of this article are to develop a new mathematical formulation and a new heuristic for the problem of preemptive two-agent scheduling in open shops subject to machine maintenance and eligibility constraints. Design/methodology: Using the ideas of minimum cost flow network and constraint programming, a heuristic and a network based linear programming are proposed to solve the problem. Findings: Computational experiments show that the heuristic generates a good quality schedule with a deviation of 0.25% on average from the optimum and the network based linear programming model can solve problems up to 110 jobs combined with 10 machines without considering the constraint that each operation can be processed on at most one machine at a time. In order to satisfy this constraint, a time consuming Constraint Programming is proposed. For n = 80 and m = 10, the average execution time for the combined models (linear programming model combined with Constraint programming) exceeds two hours. Therefore, the heuristic algorithm we developed is very efficient and is in need. Practical implications: Its practical implication occurs in TFT-LCD and E-paper manufacturing wherein units go through a series of diagnostic tests that do not have to be performed in any specified order. Originality/value: The main contribution of the article is to split the time horizon into many time intervals and use the dispatching rule for each time interval in the heuristic algorithm, and also to combine the minimum cost flow network with the Constraint Programming to solve the problem optimally.Peer Reviewe

Examination timetabling at the University of Cape Town: a tabu search approach to automation

With the rise of schedules and scheduling problems, solutions proposed in literature have expanded yet the disconnect between research and reality remains. The University of Cape Town's (UCT) Examinations Office currently produces their schedules manually with software relegated to error-checking status. While they have requested automation, this study is the first attempt to integrate optimisation techniques into the examination timetabling process. Tabu search and Nelder-Mead methodologies were tested on the UCT November 2014 examination timetabling data with tabu search proving to be more effective, capable of producing feasible solutions from randomised initial solutions. To make this research more accessible, a user-friendly app was developed which showcased the optimisation techniques in a more digestible format. The app includes data cleaning specific to UCT's data management system and was presented to the UCT Examinations Office where they expressed support for further development: in its current form, the app would be used as a secondary tool after an initial solution has been manually obtained