Study of Direction Probability and Algorithm of Improved Marriage in Honey Bees Optimization for Weapon Network System

To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly described.With such method,we can avoid the inconformity of the description obtained from the traditional index systems.Three new indexes are also proposed,i.e.join index,overlap index and cover index,which help manage the relationship among several sub-weapon-networks.By normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well settled.Also,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement problem.Simulation is carried out to show the efficiency of the proposed indexes and the optimization algorithm.

To solve the weapon network system optimization problem against small raid objects with low attitude, the concept of direction probability and a new evaluation index system are proposed. By calculating the whole damaging probability that changes with the defending angle, the efficiency of the whole weapon network system can be subtly described. With such method, we can avoid the inconformity of the description obtained from the traditional index systems. Three new indexes are also proposed, i.e. join index, overlap index and cover index, which help manage the relationship among several subeapon-networks. By normalizing the computation results with the Sigmoid function, the matching problem between the optimization algorithm and indexes is well settled. Also, the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement problem. Simulation is carried out to show the efficiency of the proposed indexes and the optimization algorithm.