War Strategy Optimization Algorithm: A New Effective Metaheuristic Algorithm for Global Optimization

This paper proposes a new metaheuristic optimization algorithm based on ancient war strategy. The proposed War Strategy Optimization (WSO) is based on the strategic movement of army troops during the war. War strategy is modeled as an optimization process wherein each soldier dynamically moves towards the optimum value. The proposed algorithm models two popular war strategies, attack and defense strategies. The positions of soldiers on the battlefield are updated in accordance with the strategy implemented. To improve the algorithm's convergence and robustness, a novel weight updating mechanism and a weak soldier's relocation strategy are introduced. The proposed war strategy algorithm achieves good balance of the exploration and exploitation stages. A detailed mathematical model of the algorithm is presented. The efficacy of the proposed algorithm is tested on 50 benchmark functions and four engineering problems. The performance of the algorithm is compared with ten popular metaheuristic algorithms. The experimental results for various optimization problems prove the superiority of the proposed algorithm.

Automated summary

This paper proposes a metaheuristic optimization algorithm based on ancient war strategy, which achieves a good balance between exploration and exploitation stages by simulating the strategic movements of army troops during war. The algorithm introduces a novel weight updating mechanism and a weak soldier's relocation strategy to improve its convergence and robustness.