A novel differential evolution algorithm for threat-oriented weapon system planning

Weapon system planning is of vital importance to a country´s national security. Currently, a number of countries are under threat from potential hostile countries, especially those with advanced weapons. In this regard, weapon systems must be developed as the countermeasures that eliminate potential threats. A model of threat-oriented weapon system planning is first proposed, wherein countries must decide how much and when to develop weapons under a number of certain constrains to mitigate or even neutralize threats as much as possible. Then, a novel differential evolution with neighborhood revision algorithm is presented to optimize this problem. Finally, the experimental results illustrate that the proposed differential evolution with neighborhood revision algorithm has a more outstanding performance than two other algorithms.