Result 1 to 20 of 67 total
Solving job shop scheduling with setup times through constraint-based iterative sampling: an experimental analysis. (English)
Ann. Math. Artif. Intell. 62, No. 3-4, 371-402 (2011).
1
MrSpock ‒ steps in developing an end-to-end space application. (English)
Comput. Intell. 27, No. 1, 83-102 (2011).
2
Constraint-based methods for scheduling discretionary services. (English)
AI Commun. 24, No. 1, 51-73 (2011).
3
Scheduling a single robot in a job-shop environment through precedence constraint posting. (English)
Mehrotra, Kishan G. (ed.) et al., Modern approaches in applied intelligence. 24th international conference on industrial engineering and other applications of applied intelligent systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 ‒ July 1, 2011. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-21826-2/pbk). Lecture Notes in Computer Science 6704. Lecture Notes in Artificial Intelligence, 216-225 (2011).
4
Mrspock - steps in developing an end-to-end space application (English)
Computational Intelligence 27, No. 1, 83-102 (2011).
5
Iterative flattening search for the flexible job shop scheduling problem (English)
IJCAI, 1991-1996 (2011).
6
Scheduling a single robot in a job-shop environment through precedence constraint posting (English)
IEA/AIE (2), 216-225 (2011).
7
Project scheduling as a Disjunctive Temporal Problem. (English)
Coelho, Helder (ed.) et al., ECAI 2010. 19th European conference on artificial intelligence, August 16‒20, 2010 Lisbon, Portugal. Including proceedings of the 6th prestigious applications of artificial intelligence (PAIS-2010). Amsterdam: IOS Press (ISBN 978-1-60750-605-8/pbk; 978-1-60750-606-5/ebook). Frontiers in Artificial Intelligence and Applications 215, 967-968 (2010).
8
Project scheduling as a disjunctive temporal problem (English)
ECAI, 967-968 (2010).
9
Solve-and-robustify. (English)
J. Sched. 12, No. 3, 299-314 (2009).
10
Iterative flattening search on RCPSP/max problems: recent developments. (English)
Oddi, Angelo (ed.) et al., Recent advances in constraints. 13th annual ERCIM international workshop on constraint solving and constraint logic programming, CSCLP 2008, Rome, Italy, June 18‒20, 2008. Revised selected papers. Berlin: Springer (ISBN 978-3-642-03250-9/pbk). Lecture Notes in Computer Science 5655. Lecture Notes in Artificial Intelligence, 99-115 (2009).
11
Recent advances in constraints. 13th annual ERCIM international workshop on constraint solving and constraint logic programming, CSCLP 2008, Rome, Italy, June 18‒20, 2008. Revised selected papers. (English)
Lecture Notes in Computer Science 5655. Lecture Notes in Artificial Intelligence. Berlin: Springer (ISBN 978-3-642-03250-9/pbk). ix, 147~p. EUR~45.96 (2009).
12
Solving resource-constrained project scheduling problems with time-windows using iterative improvement algorithms (English)
ICAPS (2009).
13
Developing an end-to-end planning application from a timeline representation framework (English)
IAAI (2009).
14
Hybrid variants for iterative flattening search. (English)
Perron, Laurent (ed.) et al., Integration of AI and OR techniques in constraint programming for combinatorial optimization problems. 5th international conference, CPAIOR 2008 Paris, France, May 20‒23, 2008. Proceedings. Berlin: Springer (ISBN 978-3-540-68154-0/pbk). Lecture Notes in Computer Science 5015, 355-360 (2008).
15
Combining variants of iterative flattening search (English)
Eng. Appl. of AI 21, No. 5, 683-690 (2008).
16
Continuous plan management support for space missions: the RAXEM case (English)
ECAI, 703-707 (2008).
17
Iterative flattening search on RCPSP/Max problems: recent developments (English)
CSCLP, 99-115 (2008).
18
Hybrid variants for iterative flattening search (English)
CPAIOR, 355-360 (2008).
19
Mexar2: AI solves mission planner problems. (English)
IEEE Intelligent Systems 22, No. 04, 12-19 (2007).
20
Result 1 to 20 of 67 total
Start
Contact
Print
General Help
