Research Article
Advanced Harmony Search with Ant Colony Optimization for Solving the Traveling Salesman Problem
Pseudocode 1
The pseudo-code for the proposed algorithm (AHS-ACO).
Procedure: The proposed algorithm for the TSP | Begin | Objective function , | Generate initial harmonics (real number arrays) | Define harmony memory considering rate , pitch adjusting rate , mutation rate | Initialize the pheromone tables | Generate initial harmony randomly and apply pheromone update | while (not_termination) | for : number of nodes | Generate random number variable (rand) | if (rand < ) | Generate random number variable (rand) | if (rand < ), generate the nearest city to the previous harmonic | else choose an existing harmonic the highest fitness probability | end if | else generate new harmonics via randomization | end if | end for | Accept the new harmonics (solutions) if better | Generate random number variable (rand) | if (rand < ) operate inversion mutation end if | Apply the pheromone update | Create as many cities as the HMS based pheromone using Ant Colony Optimization | Update harmony memory and apply pheromone update | end while | Find the current best solutions | End |
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