alvgaona

def grasp_max_clique(
    graph: dict[int, set[int]], iterations: int = 100, alpha: float = 0.2
) -> set[int]:
    """
    GRASP (Greedy Randomized Adaptive Search Procedure) for maximum clique.
    Combines randomized greedy construction with local search.

    Args:
        graph: Dictionary representing adjacency list
        iterations: Number of GRASP iterations

alvgaona

class StandardCPP(CPPSolver):
    """
    Standard Chinese Postman Algorithm for complete graphs.

    Time Complexity: O(n³) for matching, O(n²) for circuit
    Space Complexity: O(n²)

    This is an EXACT algorithm that always finds the optimal solution.
    """

alvgaona

class TSPSolver:
    """Base class for TSP solvers."""

    def __init__(self, problem) -> None:
        """
        Initialize the TSP solver.

        Args:
            problem: tsplib95 problem instance
        """

alvgaona

import heapq
from typing import Dict, List, Tuple, Optional


def dijkstra(
    graph, start_node: int, end_node: Optional[int] = None
) -> Tuple[Dict[int, float], Dict[int, Optional[int]]]:
    """
    Implements Dijkstra's shortest path algorithm.

alvgaona

A = [
  -1 -1 1;
  1 3 3;
  -1 -1 5
];

[QQ,RR] = qr(A);

[m, n] = size(A);

alvgaona

x = 2;
 
ax = abs(x);

if (ax < 3.75)
  y = x/3.75;
  y = y*y;
  ans = 1.0+y*(3.5156229+y*(3.0899424+y*(1.2067492 + y*(0.2659732+y*(0.360768e-1+y*0.45813e-2)))));
else
  y=3.75/ax;