Open AccessAnt Colony Optimization Implementation on Traveling Salesman Problem to Achieve the Shortest Logistic Route
Author(s) -
Mariani Sembiring,
Steven Chailes
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1003/1/012045
Subject(s) - travelling salesman problem , ant colony optimization algorithms , truck , mathematical optimization , computer science , transportation theory , traveling purchaser problem , 2 opt , ant colony , extremal optimization , supply chain , operations research , optimization problem , mathematics , engineering , business , marketing , meta optimization , aerospace engineering
Transportation refers to the movement of everything from raw materials to finished goods between various facilities in the supply chain. In transportation, the exchange between responsiveness and efficiency is manifested in the choice of transportation modes. Because transportation costs can be as much as one third of the supply chain operating costs, the decision made here is very important. Traveling Salesman Problem is one of the best-known NP-hard problems where there is no precise algorithm to solve it in polynomial time. The ACO algorithm has good potential for problem solving and recent research that has attracted a lot of attention, in particular is the case of solving NP-Hard problems. One of the earliest best works is completing TSP using ACS (Ant Colony System). Ant System is the first ACO algorithm with its main characteristics being that at each iteration, the pheromone values are updated by all (m) ants who have built a solution in the iteration itself. From the arrangement of the shipping routes that have been implemented by the Ant Colony Optimization on the Traveling Salesman Problem, the amount of savings in the transportation mode of trucks to mileage is 37%.