Set variables and local search

Authors:
Magnus Ågren;Pierre Flener;Justin Pearson
Affiliations:
Department of Information Technology, Uppsala University, Uppsala, Sweden;Department of Information Technology, Uppsala University, Uppsala, Sweden;Department of Information Technology, Uppsala University, Uppsala, Sweden
Venue:
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Year:
2005

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Abstract

Many combinatorial (optimisation) problems have natural models based on, or including, set variables and set constraints. This was already known to the constraint programming community, and solvers based on constructive search for set variables have been around for a long time. In this paper, set variables and set constraints are put into a local-search framework, where concepts such as configurations, penalties, and neighbourhood functions are dealt with generically. This scheme is then used to define the penalty functions for five (global) set constraints, and to model and solve two well-known applications.