NP Problem Ecosystem
The NP Problem Ecosystem is a comprehensive suite of exact and heuristic solvers for the Traveling Salesman Problem — featuring Exact TSP Solver (Rust) , Exact TSP Solver (Go) and Smart TSP Oracle (Python) for provably optimal solutions via branch-and-bound, Smart TSP Solver (Python) for large-scale heuristic routing with Dynamic Gravity and Angular-Radial algorithms, and Smart TSP Benchmark for professional algorithm testing - all grounded in the Position-Candidate-Hypothesis (PCH) paradigm for NP-complete problems.
Dual-mode TSP solver in Rust: exact Branch & Bound with proven optimality, plus heuristic threshold search with reference gap.
Dual-mode TSP solver in Go: exact Branch & Bound plus heuristic threshold search
Exact solver in Python with adaptive thresholding for optimal solutions
Professional testing infrastructure with configurable scenarios
Spatial intelligence algorithms - improve TSP solutions by up to 25%
Full list on Applications page
Universal TSP path improver using the PCH (Position-Candidate-Hypothesis) paradigm. PCH takes ANY TSP path (from ANY algorithm), statistically analyzes it, and synthesizes a shorter path.
A high-performance Rust library for solving the Traveling Salesman Problem (TSP) using the novel Dynamic Gravity algorithm.
High-performance Python library - outperforms classical methods by ~25%
Professional testing infrastructure for TSP algorithms
Full list on Libraries page
Structural-statistical approach to NP-complete problems
Full list on Research page
4 paradigms with DOI and Ecosystems
Full list on Ecosystems page