Particle Swarm Optimization (PSO) is a computational method for optimization of a problem by simulating a set of moving particles that move around a search-space. Now let’s say that you want to find the (global) minimum of the square function: f(x) = x[0]^2 + x[1]^2. The source code can be found on https://github.com/isachpaz/OptimizationSharp

As an example, calculating the NTCP based on the Lyman-Kutcher-Burman (LKB) model for the endpoint of urethra stricture, we use the following parameters TD50 = 116.7 Gy, m = 0.23, n = 0.3, and α/β = 5.0 Gy. (as published by Panitierri et al.[1], and used in the study of Spohn and Sachpazidis et al.[2]).…