A Mathematical Optimization Model for the Pharmaceutical Waste Location-Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

Algorithm 1

Genetic Algorithm (GA).

Input:

  Population size (n)

  Maximum number of iterations (MAX)

Output:

  Global best solution, Y_bt

Begin

   # Create an initial population of n chromosomes Y_i (i = 1, 2,…, n)

   For i = 1 to n

    Y_i = generate_chromosome()

   compute_fitness(Yi)

   Set iteration counter t = 0

   While (t < MAX)

    A selection of two chromosomes is made from the initial population based on fitness

    Apply crossover operation on selected pair with crossover probability

    Apply mutation on the offspring with mutation probability

    Replace old population with new offspring

    Increase the current iteration t by one.

  end while

  return the best solution found, Y_bt

end