Name
Abstract | ||
|---|---|---|
This paper presents a new approach to solve rostering, planning and resource management problems. This is achieved by transforming several kinds of finite domain constraints of a given constraint satisfaction problem (CSP) into a set of regular membership constraints; and then these regular membership constraints are combined together to a more specific regular membership constraint. The purpose of this approach is to improve the speed of CSPs resolution and to remove undesirable redundant constraints (constraints which slow down the resolution speed) by replacing part of or all constraints of a CSP with a set of regular membership constraints followed by the combination of multiple regular membership constraints into a new, more precise regular membership constraint. A concise rostering example has demonstrated that our approach enables a significant improvement of the performance of the CSP resolution due to the pruning of the search tree. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-92007-8_18 | ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2018 |
Keywords | Field | DocType |
Constraint programming, CSP, Refinement, Planning, Resource management, Scheduling | Resource management,Mathematical optimization,Computer science,Scheduling (computing),Constraint programming,Constraint satisfaction problem,Regularization (mathematics),Artificial intelligence,Machine learning,Search tree | Conference |
Volume | ISSN | Citations |
519 | 1868-4238 | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sven Löffler | 1 | 0 | 1.01 |
| Ke Liu | 2 | 20 | 16.97 |
| Petra Hofstedt | 3 | 50 | 18.83 |