and backchase

an optimal solution, according to some objective function. The combination of a CSP and an objective function is called a constrained optimization problem (COP). Programs, procedures, and algorithms for constraint solving are called constraint solvers. For a tutorial, and textbooks on constraint programming

Abstract — Given some geometric elements such as points and lines in , subject to a set of pairwise distance constraints, the problem tackled in this paper is that of finding all possible configurations of these elements that satisfy the constraints. Many problems in Robotics (such

Treatment plan optimization for rotating-shield brachytherapy

present a characterization of the problem space of self-adaptation for service-oriented systems, thus providing a frame of reference where our and other approaches can be classified. Then, we present MOSES, a methodology and a software tool implementing it to support QoS-driven adaptation of a service

I herewith certify that all material in this dissertation which is not my own work has been properly acknowledged.

Abstract not found

The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large

to optimize and speed up a controlling process, however none of the existing solutions provides an any-time behavior. This study first introduces several constraints that should be satisfied in order to guarantee an any-time behavior. These constraints are related to aggregation and defuzzification phases

In presenting this thesis in partial fulfilment of the requirements for a Postgraduate degree