Modelling and optimal solving of dependent sensor-weapon/threat assignment and scheduling problem by a metaheuristic algorithm based on GRASP

Nowadays, smart systems are being widely used in combats because there exist a lot of applications for these systems which usually depend on sensors. Matching sensors to weapons and threats or in short sensor-weapon/threat assignment is a major challenge in modern wars and is classified as a complex resource assignment optimization problem. Consequently, the result of modern wars highly depends on effective usage of sensors and weapons. In this paper, the sensor-weapon/threat assignments and their scheduling problem have been formulated. The object of this model is maximizing the destruction of threats in a given time horizon subject to operational constraints. This model has been solved using CPLEX. Furthermore, a metaheuristic algorithm based on GRASP is developed. Finally, using a set of randomly generated test instances, the results of all developed solution approaches are reported and compared.