n iv-m rs .fr * Supported by the European Community Project IST-2001-35304 (AMETIST), h t tp : // a m e t i s t.c s .u t w e n te .n l. ** Peter Niebert suggested the method for efficient computation of canonical represen tatives at an AMETIST project meeting, and was therefore invited to join the list of authors after acceptance of the paper.
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In this paper we describe a case study on lacquer production scheduling that was performed in the European IST-project AMETIST and was provided by one of the industrial partners. The approach is to derive schedules by means of reachability analysis: with this technique the search mechanism of model checkers, in our case here Uppaal, is used to find feasible or optimal schedules. The advantage of this approach is that the expressiveness of timed automata allows to model scheduling problems of different kinds, unlike many classical approaches, and the problem class is robust against changes in the parameter setting. To fight the typical state space explosion problem a number of standard heuristics have to be used. We discuss the difficulties when modelling an industrial case of this kind, describe the experiments we performed, the heuristics used, and the techniques applied to allow to optimize costs (storage costs, delay costs, etc.) while searching for schedules.
The timed automaton framework of Alur and Dill is a natural choice for the specification of partially synchronous distributed systems. The past has shown, however, that verification of these systems by model checking usually is very difficult. Therefore, model checking techniques have thus far not really been used for their design, even though these techniques are widely used in other areas, e.g., hardware verification. The present paper demonstrates that the revolutionary development of both the usability and the efficiency of model checking tools may change this. It is shown that a complex partially synchronous distributed algorithm can easily be modeled with the Uppaal model checker, and that it is possible to analyze some interesting and non-trivial instances with reasonable computational resources. Clearly, such analysis results can greatly support the design of these systems: model checking tools may provide valuable early feedback on subtle design errors and hint at system invariants that can subsequently be used in the general correctness proof.
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