CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem
Dynamic Programming (DP) and Constraint Programming (CP) are well-established paradigms for solving combinatorial optimization problems. Usually, these two approaches are used separately. This paper aims to show that the two can be combined effectively and elegantly, with DP serving as the primary search framework and CP used as a subroutine to leverage global constraint propagation. This paper presents such an approach for the Partial Shop Scheduling Problem (PSSP), for which a pure DP method has previously been proposed, and efficient CP filtering algorithms are available. The PSSP is a general scheduling problem where each job consists of a set of operations with arbitrary precedence c...
| Authors | Emma Legrand, Roger Kameugne, Pierre Schaus |
|---|---|
| Primary category | cs.AI |
| Published | 22 May 2026 |
| Last updated at source | 22 May 2026 |
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