Particle Swarm Optimization Algorithm

Source code represents a computer program that can be both executed and modified. It contains instructions and data structures implementing specific computational methods, particularly the particle swarm optimization algorithm which simulates collective intelligence through population-based search techniques. The executability of source code means it can be interpreted and run by computational systems, producing desired optimization results through iterative position updates and velocity calculations for each particle in the swarm. The modifiable nature allows developers to edit core parameters including swarm size, inertia weight, cognitive and social coefficients, enabling customization for different optimization scenarios. This flexibility is crucial for software development and algorithm customization, providing researchers with adaptable implementation frameworks that support various objective functions and constraint handling mechanisms. The code typically includes key functions for initialization, fitness evaluation, velocity updating, and position updating, following standard PSO algorithmic procedures.