Constraint partitioning in penalty formulations for solving temporal planning problems

Artificial Intelligence

Volumn 170, Issue 3, 2006, Pages 187-231

  Wah, Benjamin W ^a   Chen, Yixin ^b  

^a University of Illinois at Urbana Champaign   (United States)

^b WASHINGTON UNIVERSITY   (United States)

Author keywords

Constraint partitioning; Extended saddle point condition; Local search; Mixed space planning; Nonlinear constraints; Penalty function; Temporal planning

Indexed keywords

ALGORITHMS; BENCHMARKING; GLOBAL OPTIMIZATION; NONLINEAR PROGRAMMING; PROBLEM SOLVING;

CONSTRAINT PARTITIONING; EXTENDED SADDLE-POINT CONDITION; LOCAL SEARCH; MIXED SPACE PLANNING; NONLINEAR CONSTRAINTS; PENALTY FUNCTION; TEMPORAL PLANNING;

CONSTRAINT THEORY;

EID: 31144437356     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artint.2005.07.001     Document Type: Article

References (55)

1. E. Aarts, and J. Korst Simulated Annealing and Boltzmann Machines 1989 J. Wiley and Sons New York
2. M. Avriel Nonlinear Programming: Analysis and Methods 1976 Prentice-Hall Englewood Cliffs, NJ
3. R. Bellman, and S. Dreyfus Applied Dynamic Programming 1962 Princeton Univ. Press Princeton, NJ
4. D.P. Bertsekas Nonlinear Programming 1999 Athena Scientific Belmont, MA
5. A.L. Blum, and M.L. Furst Fast planning through planning graph analysis Artificial Intelligence 90 1997 281 300
6. B. Bonet, and H. Geffner Planning as heuristic search Artificial Intelligence 129 1 2001
7. Y.X. Chen, C.-W. Hsu, B.W. Wah, SGPlan: Subgoal partitioning and resolution in planning, in: Proc. Fourth Internat. Planning Competition, Internat. Conf. on Automated Planning and Scheduling, 2004
8. Y.X. Chen, B.W. Wah, Automated planning and scheduling using calculus of variations in discrete space, in: Proc. Internat. Conf. on Automated Planning and Scheduling, 2003, pp. 2-11
9. S. Chien ASPEN - Automating space mission operations using automated planning and scheduling Proc. SpaceOps 2000 Space Operations Organization
10. P. Doherty, and J. Kvarnstrom TALplanner: An empirical investigation of a temporal logic-based forward chaining planner Proc. Sixth Internat. Workshop on Temporal Logic-based Forward Chaining Planner 1999 AIPS 47 54
11. M.A. Duran, and I.E. Grossmann An outer approximation algorithm for a class of mixed-integer nonlinear programs Math. Programming 36 1986 306 307
12. S. Edelkamp Mixed propositional and numerical planning in the model checking integrated planning system Proc. Workshop on Planning in Temporal Domains 2002 AIPS 47 55
13. M.P. Fourman Propositional planning Proc. Workshop on Model Theoretic Approaches to Planning 2000 AIPS
14. M. Fox, and D. Long PDDL2.1: An extension to PDDL for expressing temporal planning domains J. Artificial Intelligence Res. 20 2003 61 124
15. A.M. Geoffrion Generalized Benders decomposition J. Optim. Theory Appl. 10 4 1972 237 241
16. A. Gerevini, and I. Serina LPG: A planner based on local search for planning graphs with action costs Proc. of the Sixth Internat. Conf. on AI Planning and Scheduling 2002 Morgan Kaufman Santa Mateo, CA 12 22
17. N.I.M. Gould, D. Orban, Ph.L. Toint, An interior-point L1-penalty method for nonlinear optimization, Technical Report, RAL-TR-2003-022, Rutherford Appleton Laboratory Chilton, Oxfordshire, UK, 2003
18. J. Hoffmann, and B. Nebel The FF planning system: Fast plan generation through heuristic search J. Artificial Intelligence Res. 14 2001 253 302
19. K. Holmberg On the convergence of the cross decomposition Math. Programming 47 1990 269 316
20. K. Holmberg Generalized cross decomposition applied to nonlinear integer programming problems: duality gaps and convexification in parts Optimization 23 1992 341 364
21. A.K. Jónsson, P.H. Morris, N. Muscettola, and K. Rajan Planning in interplanetary space: Theory and practice Proc. 2nd Internat. NASA Workshop on Planning and Scheduling for Space 2000 NASA
22. H. Kautz, and B. Selman Pushing the envelope: planning, propositional logic, and stochastic search Proc. 13th National Conference on Artificial Intelligence 1996 AAAI 1194 1201
23. H. Kautz, and B. Selman Unifying SAT-based and graph-based planning Proc. Internat. Joint Conf. on Artificial Intelligence 1999 IJCAI
24. H. Kautz, and J.P. Walser Integer optimization models of AI planning problems Knowledge Engrg. Rev. 15 1 2000 101 117
25. S. Kirkpatrick, C.D. Gelatt Jr., and M.P. Vecchi Optimization by simulated annealing Science 220 4598 1983 671 680
26. H.W. Kuhn, and A.W. Tucker Nonlinear programming Proc. Second Berkeley Symp. Math. Stat. Prob. 1951 University of California Press 481 492
27. F. Lin A planner called R AI Magazine 2001 73 76
28. D. Long, and M. Fox Efficient implementation of the plan graph in STAN J. Artificial Intelligence Res. 10 1999 87 115
29. D.G. Luenberger Linear and Nonlinear Programming 1984 Addison-Wesley Reading, MA
30. D. Nau, H. Muoz-Avila, Y. Cao, A. Lotem, and S. Mitchell Total-order planning with partially ordered subtasks Proc. Internat. Joint Conf. on Artificial Intelligence 2001 IJCAI 425 430
31. R.S. Nigenda, X. Nguyen, S. Kambhampati, AltAlt: Combining the advantages of Graphplan and heuristic state search, Technical Report, Arizona State University, 2000
32. J. Penberethy, and D. Weld UCPOP: A sound, complete, partial order planner for ADL Proc. 3rd Internat. Conf. on Principles of Knowledge Representation and Reasoning 1992 KR Inc. 103 114
33. J. Penberethy, and D. Weld Temporal planning with continuous change Proc. 12th National Conf. on AI 1994 AAAI 1010 1015
34. G. Rabideau, S. Chien, C. Eggemeyer, T. Mann, J. Willis, S. Siewert, and P. Stone Interactive, repair-based planning and scheduling for shuttle payload operations Proc. Aerospace Conf. 1997 IEEE 325 341
35. G. Rabideau, R. Knight, S. Chien, A. Fukunaga, and A. Govindjee Iterative repair planning for spacecraft operations in the ASPEN system Proc. Internat. Symp. on Artificial Intelligence Robotics and Automation in Space 1999 European Space Agency
36. R.L. Rardin Optimization in Operations Research 1998 Prentice-Hall Englewood Cliffs, NJ
37. I. Refanidis, and I. Vlahavas The GRT planner AI Magazine 2001 63 66
38. I. Refanidis, and I. Vlahavas The MO-GRT system: Heuristic planning with multiple criteria Proc. Workshop on Planning and Scheduling with Multiple Criteria 2002 AIPS
39. T.J. Van Roy Cross decomposition for mixed integer programming Math. Programming 25 1983 46 63
40. H.S. Ryoo, and N.V. Sahinidis A branch-and-reduce approach to global optimization J. Global Optim. 8 2 1996 107 139
41. N.V. Sahinidis BARON: A general purpose global optimization software package J. Global Optim. 8 2 1996 201 205
42. D. Schuurmans, and F. Southey Local search characteristics of incomplete sat procedures Artificial Intelligence 132 2 2001 121 150
43. B. Selman, and H.A. Kautz An empirical study of greedy local search for satisfiability testing Proc. of 11th National Conf. on Artificial Intelligence 1993 AAAI 46 51
44. Y. Shang, and B.W. Wah A discrete Lagrangian based global search method for solving satisfiability problems J. Global Optim. 12 1 1998 61 99
45. M.B.D. Subbarao, S. Kambhampati, Sapa: A domain-independent heuristic metric temporal planner, Technical Report, Arizona State University, 2002
46. A. Tate, B. Drabble, and R. Kirby O-Plan2: an open architecture for command, planning and control Intelligent Scheduling 1994 Morgan Kaufmann 213 239
47. B.W. Wah, Y.X. Chen, Partitioning of temporal planning problems in mixed space using the theory of extended saddle points, in: Proc. IEEE Internat. Conf. on Tools with Artificial Intelligence, 2003, pp. 266-273
48. B.W. Wah, and Y.X. Chen Subgoal partitioning and global search for solving temporal planning problems in mixed space Internat. J. Artificial Intelligence Tools 13 4 2004 767 790
49. B.W. Wah, and Y.X. Chen Solving large-scale nonlinear programming problems by constraint partitioning Proc. Principles and Practice of Constraint Programming 2005 Springer-Verlag Berlin
50. B.W. Wah, and T. Wang Simulated annealing with asymptotic convergence for nonlinear constrained global optimization Proc. Principles and Practice of Constraint Programming 1999 Springer-Verlag Berlin 461 475
51. B.W. Wah, and Z. Wu The theory of discrete Lagrange multipliers for nonlinear discrete optimization Proc. Principles and Practice of Constraint Programming 1999 Springer-Verlag Berlin 28 42
52. D. Wilkins Can AI planners solve practical problems? Computational Intelligence 1990 232 246
53. J. Willis, G. Rabideau, and C. Wilklow The citizen explorer scheduling system Proc. Aerospace Conf. 1999 IEEE
54. S. Wolfman, and D. Weld Combining linear programming and satisfiability solving for resource planning Knowledge Engrg. Rev. 15 1 2000
55. Z. Wu, The theory and applications of nonlinear constrained optimization using Lagrange multipliers, Ph.D. Thesis, Department of Computer Science, Univ. of Illinois, Urbana, IL, 2001