In this paper we show how the classical job-shop scheduling problem
(as well as many other scheduling problem) can be modeled as a special
class of acyclic timed automata. Finding an optimal schedule
corresponds, then, to finding a shortest (in terms of elapsed time)
path in the timed automaton. This representation provides new
techniques for solving the optimization problem and, more importantly,
it allows to model naturally more complex dynamic resource allocation
problems which are not captured so easily in traditional models of
operation research. We present several algorithms and heuristics for
finding the shortest paths in timed automata and test their
implementation in the tool Kronos on numerous benchmark examples.
