Particle Swarm Optimization Algorithm Source Code for TSP Problem

A comprehensive Particle Swarm Optimization (PSO) source code implementation for solving the 50-city Traveling Salesman Problem (TSP), featuring customizable parameters and extendable to similar NP-hard optimization challenges.

Decision Making Method for Non-Independent Hierarchical Structures (NP Method)

The NP (Network Process) method, developed by Professor T.L. Saaty at the University of Pittsburgh in 1996, is an adaptation of the Analytic Hierarchy Process (AHP) specifically designed for non-independent hierarchical decision structures. This practical decision-making methodology involves key computational steps such as: 1) Factor identification and model establishment for network and control layers, 2) Creation of comparison matrices, 3) Column-wise normalization based on indicator types, 4) Calculation of maximum eigenvalues and corresponding eigenvectors for each comparison matrix, 5) Consistency validation with matrix element adjustment when required, 6) Unitization (normalization) of eigenvectors to form judgment matrices, 7) Multiplication of control layer and network layer judgment matrices to obtain weighted supermatrices, 8) Limit matrix computation through power iteration convergence.