The centralized sequential investment problem with regional characteristics effect by using genetic algorithms

This research aims to find a non-recurring directed path that will enable all investment regions to achieve the target revenues within the shortest period of time. We call this optimization problem the centralized sequential investment problem (CSIP). “Regional characteristics effect (RC effect)” is assumed to be the major factor that affects the expected time to achieve the target revenue for an investment region. Using the RC effect definition, we introduce the concepts of path effectiveness and sequential effectiveness. Furthermore, we define a completely memoryless property of the RC effect and consider the scenario that the RC effect of a prior investment region on a subsequent investment region follows a linear fashion. Accordingly, this paper explores CSIP's structural properties and constructs a binary integer programming model for transnational sequential investment. Also, a simple method of estimating model parameters and a GA-based solution procedure are proposed for solving CSIP.