Multi-swarm optimization is a variant of particle swarm optimization (PSO), a computational method that optimizes a problem by iteratively improving a candidate solution. This method is inspired by the behavior of natural swarms, such as flocks of birds or schools of fish, where each individual follows simple rules that result in the collective behavior of the group.

• Aerospace engineering
• Computer science
• Electrical engineering
• Mechatronics
• Robotics
• Biology
• Environmental science

For example, consider a problem of optimizing the design of an aircraft wing. The optimization process can be modeled as a multi-swarm optimization algorithm, where each swarm represents a different design parameter (such as wing shape, size, or material). Each swarm follows simple rules based on the positions and velocities of its neighbors, and the collective behavior of all the swarms leads to an optimal solution for the aircraft wing design.

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