Job-shop scheduling using timed automata

In this paper we show how the classical job-shop 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.