A Constraint Programming Framework for Local Search Methods

We propose in this paper a novel integration of local search algorithms within a constraint programming framework for combinatorial optimization problems, in an attempt to gain both the efficiency of local search methods and the flexibility of constraint programming while maintaining a clear separation between the constraints of the problem and the actual search procedure. Each neighborhood exploration is performed by branch-and-bound search, whose potential pruning capabilities open the door to more elaborate local moves, which could lead to even better approximate results. Two illustrations of this framework are provided, including computational results for the traveling salesman problem with time windows. These results indicate that it is one order of magnitude faster than the customary constraint programming approach to local search and that it is competitive with a specialized local search algorithm.

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

[2]  Hector J. Levesque,et al.  A New Method for Solving Hard Satisfiability Problems , 1992, AAAI.

[3]  Michel Gendreau,et al.  A View of Local Search in Constraint Programming , 1996, CP.

[4]  Gilbert Laporte,et al.  New Insertion and Postoptimization Procedures for the Traveling Salesman Problem , 1992, Oper. Res..

[5]  Marius M. Solomon,et al.  Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints , 1987, Oper. Res..

[6]  Shen Lin.  Computer solutions of the traveling salesman problem , 1965 .

[7]  Fred W. Glover,et al.  A user's guide to tabu search , 1993, Ann. Oper. Res..

[8]  F. Glover.  HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS , 1977 .

[9]  Michel Gendreau,et al.  A Generalized Insertion Heuristic for the Traveling Salesman Problem with Time Windows , 1998, Oper. Res..

[10]  Yves Crama,et al.  Local Search in Combinatorial Optimization , 2018, Artificial Neural Networks.

[11]  Martin W. P. Savelsbergh,et al.  Local search in routing problems with time windows , 1984 .

[12]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[13]  Michel Gendreau,et al.  GENIUS-CP: a Generic Single-Vehicle Routing Algorithm , 1997, CP.

[14]  J.-F. Puget.  Object oriented constraint programming for transportation problems , 1993 .

[15]  Jacques Desrosiers,et al.  An Optimal Algorithm for the Traveling Salesman Problem with Time Windows , 1991, Oper. Res..

[16]  Brian W. Kernighan,et al.  An Effective Heuristic Algorithm for the Traveling-Salesman Problem , 1973, Oper. Res..

[17]  Michel Gendreau,et al.  An Exact Constraint Logic Programming Algorithm for the Traveling Salesman Problem with Time Windows , 1998, Transp. Sci..

[18]  Steven Minton,et al.  Solving Large-Scale Constraint-Satisfaction and Scheduling Problems Using a Heuristic Repair Method , 1990, AAAI.

[19]  Ibrahim H. Osman,et al.  Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem , 1993, Ann. Oper. Res..

[20]  François Laburthe,et al.  Disjunctive Scheduling with Task Intervals , 1995 .

[21]  Jean-Yves Potvin,et al.  An Exchange Heuristic for Routeing Problems with Time Windows , 1995 .

[22]  Michel Gendreau,et al.  A Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows , 1997, Transp. Sci..

[23]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .