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Battlefield Optimization Algorithm☆
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DOI：10.1016/j.eswa.2024.126097.png)
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Abstract
En 中文
This paper proposes anew metaheuristic optimization algorithm named Battlefield Optimization Algorithm (BfOA). As the name implies, it is inspired by the simulation of a battlefield, where two opposing squads battle each other. The squad with the stronger position defends its position and the weaker squad attacks using Supit Urang formation (an Indonesian traditional battle formation). Each squad is led by a commander. The commander leads three types of soldiers (cavaliers, special forces, and builders). Before the battle started, in the first phase each squad employs airplanes to scan the best position to begin the battle. The airplanes' movements are highly explorative. In the second phase, the defending squad's movement is highly exploitative, while the attacking squad is in the mid-explorative movement. The proposed algorithm is examined using twentythree benchmark functions and compared with one classic and five newer algorithms. To further examine the capability of the algorithm, CEC 2021 Single Objective Bound Constrained Numerical Optimization benchmark functions are used. Then the algorithm is tested in a real-world engineering optimization problem by solving the Three-Bar Truss problem.
Keywords:
Battlefield Optimization Algorithm
Battle-inspired algorithm
Metaheuristic optimization
Swarm intelligence
Scalable algorithm
Supit Urang formation
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W
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