A New Metaheuristic Farmland Fertility Algorithm to Solve Asymmetric Travelling Salesman Problem
Abstract
Asymmetric travelling salesman problem (ATSP) is an optimization problem which a salesman needs to visit all the city. In ATSP case, range from city A to city B is not the same as city B to city A. The purpose from this problem is to find a route that conclude the shortest possible route for the salesman. In this experiment, Farmland Fertility (FF) Algorithm is used to find the solution for ATSP problem. FF is a metaheuristic that inspired from farming activity. FF sees farmers that farm to get a high-quality plant to sell with high price. The farmers usually divide their farmland into some sections, and they try to give that section special materials or treatments depend on the soils. There are 3 parameters that will be the focus in this experiment. This study will design the farmland fertility algorithm to solve ATSP and find which parameters affect the result. The 3 parameters are ???? that act as special materials to give to the worst section, ???? that act as special materials to give to other sections, and ???? is possible combining soils. ANOVA is used for 27 combinations parameter to implement into five ATSP benchmarks. From the result of ANOVA, ???? have a significant impact to the algorithm performance. After all the parameters are set, the algorithm is implemented to study cases from BR17, FTV33, FTV44. FTV55 and FTV70. This algorithm only can find the best known solution on BR17, while on other study cases this algorithm cannot find the best known solution.
Copyright (c) 2021 Kevin Grahadian, Ignatius A. Sandy
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