Planning and scheduling attracts an unceasing attention of computer science community. However, despite of similar character of both tasks, in most current systems planning and scheduling problems are solved independently using different methods. Recent development of Constraint Programming brings a new breeze to these areas. It allows using the same techniques for modelling planning and scheduling problems as well as exploiting successful methods developed in Artificial Intelligence and Operations Research. In the paper we analyse the problems behind planning and scheduling in complex process environments and we propose to enhance the traditional schedulers by planning capabilities to solve these problems. We argue for using dynamic models to capture such mixed planning and scheduling environment. Despite of studying the proposed framework using the complex process environment background we believe that the results are applicable in general to other (nonproduction) problem areas where...