Article ID: | iaor200971043 |
Country: | Germany |
Volume: | 6 |
Issue: | 3 |
Start Page Number: | 269 |
End Page Number: | 280 |
Publication Date: | Aug 2009 |
Journal: | Computational Management Science |
Authors: | Delias Pavlos, Matsatsinis Nikolaos |
Enterprises often implement a measurement system to monitor their march towards their strategic goals. Although this way it is possible to assess the progress of each goal, there is no structured way to reconsider resource allocation to those goals and to plan an optimal (or near optimal) allocation scheme. In this study we propose a genetic approach to match each goal with an autonomous entity (agent) with a specific resource sharing behavior. The overall performance is evaluated through a set of functions and genetic algorithms are used to eventuate in approximate optimal behavior's schemes. To outline the strategic goals of the enterprise we used the balanced scorecard method. Letting agents deploy their sharing behavior over simulation time, we measure the scorecard's performance and detect distinguished behaviors, namely recommendations for resource allocation.