A Generic Framework for Constraint-Directed Search and Scheduling

AI Magazine

Volumn 19, Issue 4, 1998, Pages 101-130

  Beck, J Christopher ^a   Fox, Mark S ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CONSTRAINT THEORY; PROBLEM SOLVING;

CONSTRAINT DIRECTED SCHEDULING; CONSTRAINT DIRECTED SEARCH;

KNOWLEDGE ENGINEERING;

EID: 0346941162     PISSN: 07384602     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (74)

1. Applegate, D., and Cook, W. 1991. A Computational Study of the Job-Shop Scheduling Problem. ORSA Journal on Computing 3:149-156.
2. Baker, A. 1994. The Hazards of Fancy Backtracking. In Proceedings of the Twelfth National Conference on Artificial Intelligence, 288-293. Menlo Park, Calif.: American Association for Artificial Intelligence.
3. Baker, K. 1974. Introduction to Sequencing and Scheduling. New York: Wiley.
4. Baptiste, P.; Le Pape, C.; and Nuijten, W. 1995. Constraint-Based Optimization and Approximation for Job-Shop Scheduling. Paper presented at the IJCAI-95 Workshop on Intelligent Manufacturing Systems, 22-25 August, Montreal, Canada.
5. Beasley, J. E. 1990. OR-Library: Distributing Test Problems by Electronic Mail. Journal of the Operational Research Society 41(11): 1069-1072.
6. Burke, P., and Prosser, P. 1994. The Distributed Asynchronous Scheduler. In Intelligent Scheduling, eds. M. Zweben and M. Fox, 309-339. San Francisco: Morgan Kaufmann.
7. Carlier, J., and Pinson, E. 1994. Adjustment of Heads and Tails for the Job-Shop Problem. European Journal of Operational Research 78:146-161.
8. Carlier, J., and Pinson, E. 1989. An Algorithm for Solving the Job-Shop Problem. Management Science 35(2): 164-176.
9. Caseau, Y., and Laburthe, F. 1996. Cumulative Scheduling with Task Intervals. In Proceedings of the Joint International Conference and Symposium on Logic Programming. Cambridge, Mass.: MIT Press.
10. Caseau, Y., and Laburthe, F. 1995. Improving Branch and Bound for Job-Shop Scheduling with Constraint Propagation. In Proceedings of the Eighth FrancoJapanese Conference CCS'95, Brest, France.
11. Caseau, Y., and Laburthe, F. 1994. Improved CLP Scheduling with Task Intervals. In Proceedings of the Eleventh International Conference on Logic Programming, 369-383. Cambridge, Mass.: MIT Press.
12. Cheng, C., and Smith, S. F. 1997. Applying Constraint-Satisfaction Techniques to Job-Shop Scheduling. Annals of Operations Research (Special Volume on Scheduling: Theory and Practice) 70:327-378.
13. Collinot, A., and Le Pape, C. 1987. Controlling Constraint Propagation. In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, 1032-1034. Menlo Park, Calif.: International Joint Conferences on Artificial Intelligence.
14. Crawford, J. M., and Baker, A. B. 1994. Experimental Results on the Application of Satisfiability Algorithms to Scheduling Problems. In Proceedings of the Twelfth National Conference on Artificial Intelligence, 1092-1097. Menlo Park, Calif.: American Association for Artificial Intelligence.
15. Davis, E. D. 1994. ODO: A Constraint-Based Scheduler Founded on a Unified Problem-Solving Model. Master's thesis, Enterprise Integration Laboratory, Department of Industrial Engineering, University of Toronto.
16. Dechter, R. 1990. Enhancement Schemes for Constraint Processing: Backjumping, Learning, and Cutset Decomposition. Artificial Intelligence 41:273-312.
17. Dechter, R.; Dechter, A.; and Pearl, J. 1990. Optimization in Constraint Networks. In Influence Diagrams, Belief Nets, and Decision Analysis, eds. R. Oliver and J. Smith, 411-425. Chichester, U.K.: Wiley.
18. Erschler, J.; Roubellat, F.; and Vernhes, J. P. 1980. Characterizing the Set of Feasible Sequences for n Jobs to Be Carried Out on a Single Machine. European Journal of Operational Research 4:189-194.
19. Erschler, J.; Roubellat, F.; and Vernhes, J. P. 1976. Finding Some Essential Characteristics of the Feasible Solutions for a Scheduling Problem. Operations Research 24:772-782.
20. Fox, M. S. 1990. Constraint-Guided Scheduling - A Short History of Research at CMU. Computers in Industry 14:79-88.
21. Fox, M. 1986. Observations on the Role of Constraints in Problem Solving. In Proceedings of the Sixth Canadian Conference on Artificial Intelligence, May, Montreal, Canada.
22. Fox, M. S. 1983. Constraint-Directed Search: A Case Study of Job-Shop Scheduling. Ph.D. thesis, Intelligent Systems Laboratory, The Robotics Institute, Carnegie Mellon University.
23. Fox, M. S.; Sadeh, N.; and Baykan, C. 1989. Constrained Heuristic Search. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, 309-316. Menlo Park, Calif.: International Joint Conferences on Artificial Intelligence.
24. Freuder, E. C. 1982. A Sufficient Condition for Backtrack-Free Search. Journal of the Association for Computing Machinery 29(1): 24-32.
25. Freuder, E. C. 1978. Synthesizing Constraint Expressions. Communications of the Association for Computing Machinery 21(11): 958-966.
26. Garey, M. R., and Johnson, D. S. 1979. Computers and Intractability: A Guide to the Theory of NP-Completeness. New York: Freeman.
27. Gaschnig, J. 1979. Performance Measurement and Analysis of Certain Search Algorithms. Technical report, CMU-CS-79-124, Department of Computer Science, Carnegie Mellon University.
28. Gent, I.; Maclntyre, E.; Prosser, P.; Smith, B.; and Walsh, T. 1996. An Empirical Study of Dynamic Variable-Ordering Heuristics for the Constraint-Satisfaction Problem. In Proceedings of the Second International Conference on Principles and Practice of Constraint Programming (CP96), ed. E. Freuder, 179-193. New York: Springer-Verlag.
29. Ginsberg, M. 1993. Dynamic Backtracking. Journal of Artificial Intelligence Research 1:25-46.
30. Glover, F. 1990. Tabu Search Part II. Operations Research Society of America (ORSA) Journal on Computing 2(1):4-32.
31. Glover, F. 1989. Tabu Search Part I. Operations Research Society of America (ORSA) Journal on Computing 1(3): 109-206.
32. Goldberg, D. 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, Mass.: Addison-Wesley.
33. Haralick, R. M., and Elliot, G. L. 1980. Increasing Tree Search Efficiency for Constraint-Satisfaction Problems. Artificial Intelligence 14:263-314.
34. Harvey, W. D. 1995. Nonsystematic Backtracking Search. Ph.D. thesis, Department of Computer Science, Stanford University.
35. Harvey, W. D., and Ginsberg, M. L. 1995. Limited Discrepancy Search. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 607-613. Menlo Park, Calif.: International Joint Conferences on Artificial Intelligence.
36. Havens, W. 1997. Nogood Caching for Multiagent Backtrack Search. Paper presented at the AAAI-97 Constraints and Agents Workshop, 26 July, Providence, Rhode Island.
37. Holland, J. 1975. Adaptation in Natural Systems. Ann Arbor, Mich.: University of Michigan Press.
38. Hooker, J. N. 1996. Testing Heuristics: We Have It All Wrong. Journal of Heuristics 1:33-42.
39. Hooker, J. N. 1993. Needed: An Empirical Science of Algorithms. Technical report, Graduate School of Industrial Administration, Carnegie Mellon University.
40. Hooker, J. N., and Vinay, V. 1995. Branching Rules for Satisfiability. Journal of Automated Reasoning 15:359-383.
41. Kirkpatrick, S.; Gelatt, C. D.; and Vecchi, M. P. 1983. Optimization by Simulated Annealing. Science 220:671-680.
42. Korf, R. 1996. Improved Limited Discrepancy Search. In Proceedings of the Thirteenth National Conference on Artificial Intelligence. Menlo Park, Calif.: American Association for Artificial Intelligence.
43. Kumar, V. 1992. Algorithms for Constraint-Satisfaction Problems: A Survey. AI Magazine 13(1): 32-44.
44. Le Pape, C. 1994a. Constraint-Based Programming for Scheduling: An Historical Perspective. Paper presented at the Operations Research Seminar on Constraint-Handling Techniques, London, United Kingdom.
45. Le Pape, C. 1994b. Using a Constraint-Based Scheduling Library to Solve a Specific Scheduling Problem. In Proceedings of the AAAI-SIGMAN Workshop on Artificial Intelligence Approaches to Modeling and Scheduling Manufacturing Processes, New Orleans, Louisiana.
46. Le Pape, C., and Baptiste, P. 1996. Constraint-Propagation Techniques for Disjunctive Scheduling: The Preemptive Case. Paper presented at the Twelfth European Conference on Artificial Intelligence, 11-16 August, Budapest, Hungary.
47. Lhomme, O. 1993. Consistency Techniques for Numeric CSPs. In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, 232-238. Menlo Park, Calif.: International Joint Conference on Artificial Intelligence.
48. Little, J.; Murty, K.; Sweeney, D.; and Karel, C. 1963. An Algorithm for the Traveling Salesman Problem. Operations Research 11(6): 972-989.
49. Mackworth, A. K. 1977. Consistency in Networks of Relations. Artificial Intelligence 8:99-118.
50. Minton, S.; Johnston, M.; Philips, A.; and Laird, P. 1992. Minimizing Conflicts: A Heuristic Repair Method for Constraint-Satisfaction and Scheduling Problems. Artificial Intelligence 58:161-205.
51. Muscettola, N. 1992. Scheduling by Iterative Partition of Bottleneck Conflicts. Technical Report, CMU-RI-TR-92-05, The Robotics Institute, Carnegie Mellon University.
52. Neiman, D.; Hildum, D.; Lesser, V.; and Sandholm, T. 1994. Exploiting Metalevel Information in a Distributed Scheduling System. In Proceedings of the Twelfth National Conference on Artificial Intelligence, 394-400. Menlo Park, Calif.: American Association for Artificial Intelligence.
53. Nuijten, W. P. M. 1994. Time- and Resource-Constrained Scheduling: A Constraint-Satisfaction Approach. Ph.D. thesis, Department of Mathematics and Computing Science, Eindhoven University of Technology.
54. Nuijten, W., and Aarts, E. 1996. A Computational Study of Constraint Satisfaction for Multiple Capacitated Job-Shop Scheduling. European Journal of Operational Research 90: 269-284.
55. Nuijten, W. P. M.; Aarts, E. H. L.; van Arp, T.; Kip, D. A. A.; and van Hee, K. M. 1993. Randomized Constraint Satisfaction for Job-Shop Scheduling. Paper presented at the IJCAI'93 Workshop on Knowledge-Based Production, Scheduling, and Control, 29 August, Chambery, France.
56. Prosser, P. 1993. Hybrid Algorithms for the Constraint-Satisfaction Problem. Computational Intelligence 9(3): 268-299.
57. Rosenfeld, A.; Hummel, R. A.; and Zucker, S. W. 1976. Scene Labeling by Relaxation Operations. IEEE Transactions on Systems, Man, and Cybernetics 6:420-433.
58. Sadeh, N. 1994. Microopportunistic Scheduling. In Intelligent Scheduling, eds. M. Zweben and M. Fox, 99-138. San Francisco: Morgan Kaufmann.
59. Sadeh, N. 1991. Lookahead Techniques for Microopportunistic Job-Shop Scheduling. Ph.D. thesis, Computer Science Department, CMU-CS-91-102, Carnegie-Mellon University.
60. Sadeh, N., and Fox, M. S. 1996. Variable and Value-Ordering Heuristics for the Job-Shop-Scheduling Constraint-Satisfaction Problem. Artificial Intelligence Journal 86(1): 1-41.
61. Sadeh, N., and Fox, M. 1989. Focus of Attention in an Activity-Based Scheduler. Paper presented at the NASA Conference on Space Telerobotics, January, Pasadena, California.
62. Sadeh, N.; Sycara, K.; and Xiong, Y. 1995. Backtracking Techniques for the Job-Shop-Scheduling Constraint Satisfaction. Artificial Intelligence 76:455-480.
63. Shapiro, L. G., and Haralick, R. M. 1981. Structural Descriptions and Inexact Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 3(11): 504-519.
64. Smith, B., and Grant, S. 1997. Trying Harder to Fail First. Technical Report, 97.45, School of Computer Science, University of Leeds.
65. Smith, S. F.; Ow, P.; Matthys, D.; and Potvin, J. 1989. OPIS: An Opportunistic Factory-Scheduling System. Paper presented at the International Symposium for Computer Scientists, August, Beijing, China.
66. Smith, S. F., and Cheng, C. C. 1993. Slack-Based Heuristics for Constraint-Satisfaction Scheduling. In Proceedings of the Eleventh National Conference on Artificial Intelligence, 139-144. Menlo Park, Calif.: American Association for Artificial Intelligence.
67. Stallman, R., and Sussman, G. 1977. Forward Reasoning and Dependency-Directed Backtracking in a System for Computer-Aided Circuit Analysis. Artificial Intelligence 9:135-196.
68. Sycara, K.; Roth, S.; Sadeh, N.; and Fox, M. 1991. Distributed Constrained Heuristic Search. IEEE Transactions on Systems, Man, and Cybernetics SMC-21(6): 1446-1461.
69. Tsang, E. P. K. 1993. Foundations of Constraint Satisfaction. San Diego, Calif.: Academic.
70. Vaessens, R. J. M.; Aarts, E. H. L.; and Lenstra, J. K. 1994. Job-Shop Scheduling by Local Search. Technical Report, COSOR Memorandum 94-05, Eindhoven University of Technology.
71. Van Hentenryck, P. 1989. Constraint Satisfaction in Logic Programming. Cambridge, Mass.: MIT Press.
72. Waltz, D. 1975. Understanding Line Drawings of Scenes with Shadows. In The Psychology of Computer Vision, ed. P. Winston, 19-91. New York: McGraw-Hill.
73. Zweben, M.; Daun, B.; Davis, E.; and Deale, M. 1994. Scheduling and Rescheduling with Iterative Repair. In Intelligent Scheduling, eds. M. Zweben and M. Fox, 241-256. San Francisco: Morgan Kaufmann.
74. Zweben, M.; Davis, E.; Daun, B.; and Deale, M. 1993. Informedness versus Computational Cost of Heuristics in Iterative Repair Scheduling. In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, 1416-1422. Menlo Park, Calif.: International Joint Conferences on Artificial Intelligence.