Solving an assignment–selection problem with verbal information and using genetic algorithms

The assignment–selection problems deal with finding the best one-to-one match for each of the given number of ‘candidates’ to ‘positions’. Different benefits or costs are involved in each match and the goal is to minimise the total expense. In this paper we propose the use of verbal information for representing the vague knowledge available. Doing it, natural linguistic labels allow the problem to be recognised as it is in real life. This paper is an attempt to supply a satisfactory solution to real assignment–selection problems with verbal information and using genetic algorithms, showing the application of this model to the staff selection problem.