Fuzzy Numbers and Memetic Algorithm Based Approach

Evaluating worker’s suitability for a job is an important tool for Human Resources Managers (HRMs) to select the better candidates under various evaluation criteria. A problem of workers' assignment is studied in this paper in order to find the best assignment of workers to vacancies ensuring assigning a specified worker in a specified job. The objectives might be minimizing the total time to complete a set of tasks, minimizing the cost of assignments, and maximizing skill ratings. The problem is not so simple to quantify all those measures in one tangible variable. Therefore, in this paper the use of verbal information for representing the vague knowledge in terms of natural linguistic labels is proposed. It allows the problem to be recognized as it is in a real life. For such types of problems, an analysis using the fuzzy number approach promises to be potentially effective. The fuzzy suitability evaluation is executed coupled with the memetic algorithm. Also, real case study is presented. The results demonstrate that the workers' assignment problem can be solved effectively for the multiple-criteria decision-making processes. Index Term-Decision Making, Fuzzy Numbers, Memetic Algorithm, Staff Assignment.