Global Optimization Methods for Assigning Collaborators to Multiple Problems Using Genetic Algorithm

As firms continuously come across new and complex problems in the fast-changing business environment, they have to find available collaborator with proper expertise that is required by a problem and assign them to the problem which requires their expertise, so that the best results can be reached from the firm´s holistic point of view. Since this kind of an optimization problem is taking place continuously in a firm as the business environment changes, Genetic Algorithm (GA) which has shown outstanding performance in obtaining a sub-optimal solution relatively fast seems to be the right choice for such an optimization problem, instead of the other approaches such as goal-programming, multi-attribute decision making, and branch and bound. Therefore, we propose a GA-based approach to solving the above problem of assigning collaborators to multiple complex problems as well as illustrate our proposed method with an example.