A genetic algorithm approach for scheduling of resources in well-services companies

Abstract

In this paper, two examples of resources scheduling in well-services companies are solved by means of genetic algorithms: resources for call solving, people scheduling. The results demonstrate that the genetic algorithm approach can provide acceptable solutions to this type of call solving for scheduling in well-services companies. The suggested approach could be easily extended to various resource scheduling areas: process scheduling, transportation scheduling.