A heuristic approach to incremental and reactive scheduling

An heuristic approach to incremental and reactive scheduling is described. Incremental scheduling is the process of modifying an existing schedule if the initial schedule does not meet its stated initial goals. Reactive scheduling occurs in near real-time in response to changes in available resources or the occurrence of targets of opportunity. Only minor changes are made during both incremental and reactive scheduling because a goal of re-scheduling procedures is to minimally impact the schedule. The described heuristic search techniques, which are employed by the Request Oriented Scheduling Engine (ROSE), a prototype generic scheduler, efficiently approximate the cost of reaching a goal from a given state and effective mechanisms for controlling search

Designing optimal urban transport strategies : the role of individual policy instruments and the impact of financial constraints

This paper presents a methodology for the design of optimal transport strategies and the case study results of the methodology for the City of Edinburgh, using the two multi-modal transport/land-use models MARS and TPM. First, a range of policy instruments are optimised in turn and their relative impacts explored. Second, optimisations with and without financial constraints are performed and compared. Although both models produce similar optimal policies, the relative contribution of the instruments differs between models as does the impact on outcome indicators. It is also shown that by careful design it is possible to identify a strategy which costs no more than the do-minimum but which can generate substantial additional benefits. The optimisation methodology is found to be robust, and is able to be used with different transport models, and with and without financial constraints

Cardinality heterogeneities in Web service composition: Issues and solutions

Data exchanges between Web services engaged in a composition raise several heterogeneities. In this paper, we address the problem of data cardinality heterogeneity in a composition. Firstly, we build a theoretical framework to describe different aspects of Web services that relate to data cardinality, and secondly, we solve this problem by developing a solution for cardinality mediation based on constraint logic programming

Remote Sensing Information Sciences Research Group, Santa Barbara Information Sciences Research Group, year 3

Research continues to focus on improving the type, quantity, and quality of information which can be derived from remotely sensed data. The focus is on remote sensing and application for the Earth Observing System (Eos) and Space Station, including associated polar and co-orbiting platforms. The remote sensing research activities are being expanded, integrated, and extended into the areas of global science, georeferenced information systems, machine assissted information extraction from image data, and artificial intelligence. The accomplishments in these areas are examined