Combining Local Search and Look-Ahead for Scheduling and Constraint Satisfaction Problems

Abstract

We propose a solution technique for schedul-ing and constraint satisfaction problems that combines backtracking-free constructive meth-ods and local search techniques. Our technique incrementally constructs the solution, perform-ing a local search on partial solutions each time the construction reaches a dead-end. Local search on the space of partial solutions is guided by a cost function based on three components: the distance to feasibility of the partial solu-tion, a look-ahead factor, and (for optimization problems) a lower bound of the objective func-tion. In order to improve search eectiveness, we make use of an adaptive relaxation of con-straints and an interleaving of dierent look-ahead factors. The new technique has been successfully experimented on two real-life prob-lems: university course scheduling and sport tournament scheduling. 1

Cite

Text

Schaerf. "Combining Local Search and Look-Ahead for Scheduling and Constraint Satisfaction Problems." International Joint Conference on Artificial Intelligence, 1997.

Markdown

[Schaerf. "Combining Local Search and Look-Ahead for Scheduling and Constraint Satisfaction Problems." International Joint Conference on Artificial Intelligence, 1997.](https://mlanthology.org/ijcai/1997/schaerf1997ijcai-combining/)

BibTeX

@inproceedings{schaerf1997ijcai-combining,
  title     = {{Combining Local Search and Look-Ahead for Scheduling and Constraint Satisfaction Problems}},
  author    = {Schaerf, Andrea},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1997},
  pages     = {1254-1259},
  url       = {https://mlanthology.org/ijcai/1997/schaerf1997ijcai-combining/}
}