A Glimpse of Constraint Satisfaction

Constraint satisfaction has become an important field in computer science. This technology is embedded in millions of pounds of software used by major companies. Many researchers or software engineers in the industry could have benefited from using constraint technology without realizing it. The aim of this paper is to promote constraint technology by providing readers with a fairly quick introduction to this field. The approach here is to use the well known 8-queens problem to illustrate the basic techniques in constraint satisfaction (without going into great details), and leave interested readers with pointers to further study this field.

[1]  C. Reeves.  Modern heuristic techniques for combinatorial problems , 1993 .

[2]  Bernard A. Nadel,et al.  Representation selection for constraint satisfaction: a case study using n-queens , 1990, IEEE Expert.

[3]  Jean-François Puget,et al.  Applications of Constraint Programming , 1995, CP.

[4]  F. Glover,et al.  In Modern Heuristic Techniques for Combinatorial Problems , 1993 .

[5]  A. E. Eiben,et al.  Solving constraint satisfaction problems using genetic algorithms , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[6]  Rina Dechter,et al.  Network-Based Heuristics for Constraint-Satisfaction Problems , 1987, Artif. Intell..

[7]  Helmut Simonis,et al.  The CHIP System and Its Applications , 1995, CP.

[8]  Mark Wallace,et al.  Constraint logic programming for scheduling and planning , 1995 .

[9]  Bart Selman,et al.  Systematic Versus Stochastic Constraint Satisfaction , 1995, IJCAI.

[10]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[11]  Edward P. K. Tsang,et al.  Fast local search and guided local search and their application to British Telecom's workforce scheduling problem , 1997, Oper. Res. Lett..

[12]  Robert M. Haralick,et al.  Increasing Tree Search Efficiency for Constraint Satisfaction Problems , 1979, Artif. Intell..

[13]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[14]  Andrew J. Davenport,et al.  GENET: A Connectionist Architecture for Solving Constraint Satisfaction Problems by Iterative Improvement , 1994, AAAI.

[15]  C. Voudouris,et al.  Partial Constraint Satisfaction Problems and Guided Local Search , 1996 .

[16]  Kripa Shanker,et al.  A branch and bound based heuristic for multi-product resource constrained scheduling problem in FMS environment , 1999, Eur. J. Oper. Res..

[17]  Edward P. K. Tsang,et al.  Foundations of constraint satisfaction , 1993, Computation in cognitive science.

[18]  Stuart Alexander Grant,et al.  Phase transition behaviour in constraint satisfaction problems , 1997 .

[19]  Emile H. L. Aarts,et al.  Simulated annealing and Boltzmann machines - a stochastic approach to combinatorial optimization and neural computing , 1990, Wiley-Interscience series in discrete mathematics and optimization.

[20]  Toby Walsh,et al.  An Empirical Analysis of Search in GSAT , 1993, J. Artif. Intell. Res..

[21]  Edward P. K. Tsang,et al.  Tackling Car Sequencing Problems Using a Generic Genetic Algorithm , 1995, Evolutionary Computation.

[22]  Ehl Emile Aarts,et al.  Simulated annealing and Boltzmann machines , 2003 .

[23]  Mark S. Fox,et al.  Intelligent Scheduling , 1998 .

[24]  Alan K. Mackworth.  Consistency in Networks of Relations , 1977, Artif. Intell..

[25]  Bart Selman,et al.  Noise Strategies for Improving Local Search , 1994, AAAI.

[26]  P. R. Nachtsheim.  Solving constraint satisfaction problems , 1989 .

[27]  Eugene C. Freuder,et al.  Constraint-based reasoning , 1994 .

[28]  Edward P. K. Tsang,et al.  Guided local search and its application to the traveling salesman problem , 1999, Eur. J. Oper. Res..

[29]  Mark Wallace,et al.  Practical applications of constraint programming , 2004, Constraints.

[30]  Steven Minton,et al.  Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems , 1992, Artif. Intell..

[31]  Alain Colmerauer,et al.  An introduction to Prolog III , 1989, CACM.

[32]  Yuejun Jiang,et al.  1 Ng-backmarking-an algorithm for constraint satisfaction , 1995 .

[33]  Bart Selman,et al.  Domain-Independent Extensions to GSAT : Solving Large StructuredSatis ability , 1993 .

[34]  Edward P. K. Tsang,et al.  Solving the Processor Configuration Problems with a Mutation-Based Genetic Algorithm , 1997, Int. J. Artif. Intell. Tools.

[35]  Patrick Prosser,et al.  HYBRID ALGORITHMS FOR THE CONSTRAINT SATISFACTION PROBLEM , 1993, Comput. Intell..

[36]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..