Travelling salesman problem ant system algorithm pheromone updating

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To implement this algorithm, we use the Isula Framework.For the berlin52 problem instance, the optional solution has a total distance of 7542 units.Under the current configuration, the solutions produced by the algorithm are around 7795 after an execution time of 1.5 seconds.The code uploaded to this Git Hub Repository corresponds to a Maven Java Project.The problem is regarded as NP-complete, and hence traditional optimization algorithms are inefficient when applied to solve larger scale TSPTW problems.Consequently, the development of approximation algorithms has received considerable attention in recent years.

travelling salesman problem ant system algorithm pheromone updating-70

travelling salesman problem ant system algorithm pheromone updating-79

travelling salesman problem ant system algorithm pheromone updating-70

" It is an NP-hard problem in combinatorial optimization, important in operations research and theoretical computer science.Ant colony optimization (ACO), inspired by the foraging behaviour of real ants, is one of the most attractive approximation algorithms.Accordingly, this study develops a modified ant algorithm, named ACS-TSPTW, based on the ACO technique to solve the TSPTW.The TSP has several applications even in its purest formulation, such as planning, logistics, and the manufacture of microchips.Slightly modified, it appears as a sub-problem in many areas, such as DNA sequencing.

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