Intelligent Nature-Inspired Approaches for Optimal Resource Levelling in a High Voltage Alternating Current Submarine Link Terminal Station Project

Optimal resource allocation is a challenging problem which is faced by Project Managers. In large projects, where multiple resources have to be properly allocated taking into consideration the total cost of project and the time needed to be completed, the optimization problem becomes even more difficult. Therefore, intelligent techniques have been widely used to cope with such demanding problems. This study applies a nature-inspired intelligent algorithm, i.e. Sonar Inspired Optimization (SIO), to face the Resource Leveling problem of a real world project, i.e. a High Voltage Alternating Current Submarine Link Terminal Station. The specific application domain is a NP-hard optimization problem as it can receive a very large number of possible solutions. Furthermore, a hybrid scheme of this algorithm with Simulated Annealing (SIO-SA) is used to improve the performance of SIO. Comparative results show that both approaches (SIO and SIO-SA) perform almost equally well.