Invited Review Constraint satisfaction problems: Algorithms and applications

A constraint satisfaction problem (CSP) requires a value, selected from a given ®nite domain, to be assigned to each variable in the problem, so that all constraints relating the variables are satis®ed. Many combinatorial problems in operational research, such as scheduling and timetabling, can be formulated as CSPs. Researchers in arti®cial intelligence (AI) usually adopt a constraint satisfaction approach as their preferred method when tackling such problems. However, constraint satisfaction approaches are not widely known amongst operational researchers. The aim of this paper is to introduce constraint satisfaction to the operational researcher. We start by de®ning CSPs, and describing the basic techniques for solving them. We then show how various combinatorial optimization problems are solved using a constraint satisfaction approach. Based on computational experience in the literature, constraint satisfaction approaches are compared with well-known operational research (OR) techniques such as integer programming, branch and bound, and simulated annealing. Ó 1999 Elsevier Science B.V. All rights reserved.