Travelling salesman problem ant system algorithm pheromone updating
Ant colony optimization (ACO) is a population-based metaheuristic technique to effectively solve combination optimization problems.
In this way, good solutions are utilized more and it makes the algorithm converge to the best solution more quickly.
TSP is a special case of the travelling purchaser problem and the vehicle routing problem.
In the theory of computational complexity, the decision version of the TSP (where, given a length L, the task is to decide whether the graph has any tour shorter than L) belongs to the class of NP-complete problems.
Finding good, if not optimal, solutions in a reasonable time requires a balance to be struck between exploring new solutions and exploiting known information about possible solutions already examined. [Show full abstract]Lately, much attention has been posited on evolutionary strategies that bring together self-organizing systems and nature selection inspired methods.
Among these, Ant Colony Optimization algorithms have been suggested by the foraging behaviour of real ants.
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Then, we establish a pheromone diffusion model based on info fountain of a path to reflect faithfully the intensity field of pheromone diffusion and strengthen the local collaborations and communications among ants.