Constraint Programming and Genetic Algorithms to Solve Layout Design Problem

Real world optimization problems are typically complex and difficult to solve. In this work it is intended to address these problems through a combination of two techniques: Constraint Logic Programming (CLP) and Genetic Algorithms (GA). This approach aims to benefit, on the one hand, from the easiness and naturalness of the CLP to express problems whose formulation is based on constraints, and on the other hand, from the ability that GA have in attaining good solutions to a particular problem, manly when specific and efficient methods to solve the problem suitable way do not exist. As a case study these ideas were tested to solve the Facility Layout Problem which is one of the most difficult problems that face researchers experimenting with complex systems to real world applications. It relies with the design and location of production lines, machinery and equipment, inventory storage and shipping facilities. Key-words: Facilities Layout Design, Constraint Satisfaction, Constraint Logic Programming, Genetic Algorithms.