From Declarative Model to Solution: Scheduling Scenario Synthesis
This work addresses scheduling scenario synthesis for researchers or practitioners in automated planning or scheduling, but it appears incremental as it builds on existing deductive programming and Petri net methods without claiming major breakthroughs.
The paper tackles the problem of generating scheduling scenarios by introducing a declarative model for the scheduling problem domain and interpreting it as both a scheduling domain language and a predicate transition Petri net, resulting in a reachability tree that presents the search space with solutions.
This paper presents deductive programming for scheduling scenario generation. Modeling for solution is achieved through program transformations. First, declarative model for scheduling problem domain is introduced. After that model is interpreted as scheduling domain language and as predicate transition Petri net. Generated reachability tree presents search space with solutions. At the end results are discussed and analyzed.