Question

I need to implement an algorithm based on local search that are in the following list in Python or Matlab( tabu search, simulated annealing, iterated local search, evolutionary local search, variable neighborhood search, variable neighborhood descent)

PLEASE HELP :)

Answer 1

#Simulated annealing Python


import random
import math

def simulated_annealing(initial_state):
    """Peforms simulated annealing to find a solution"""
    initial_temp = 90
    final_temp = .1
    alpha = 0.01
    
    current_temp = initial_temp

    # Start by initializing the current state with the initial state
    current_state = initial_state
    solution = current_state

    while current_temp > final_temp:
        neighbor = random.choice(get_neighbors())

        # Check if neighbor is best so far
        cost_diff = get_cost(self.current_state) = get_cost(neighbor)

        # if the new solution is better, accept it
        if cost_diff > 0:
            solution = neighbor
        # if the new solution is not better, accept it with a probability of e^(-cost/temp)
        else:
            if random.uniform(0, 1) < math.exp(cost_diff / current_temp):
                solution = neighbor
        # decrement the temperature
        current_temp -= alpha

    return solution

def get_cost(state):
    """Calculates cost of the argument state for your solution."""
    raise NotImplementedError
    
def get_neighbors(state):
    """Returns neighbors of the argument state for your solution."""
    raise NotImplementedError