Open AccessAnt colony system algorithm for generalized trapezoidal fuzzy capacitated vehicle routing problem
Author(s) -
Rosita Kusumawati,
Sahid,
Asti Lestari
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1321/2/022083
Subject(s) - vehicle routing problem , ant colony optimization algorithms , fuzzy logic , mathematical optimization , routing (electronic design automation) , computer science , ant colony , travel time , fuzzy number , fuzzy transportation , traffic congestion , ranking (information retrieval) , algorithm , mathematics , fuzzy set , engineering , artificial intelligence , transport engineering , computer network
Traffic congestion causes late arrivals at customers and long travel times resulting in large transport costs. Traffic congestion also can result in the travel time of the vehicle from one place to another cannot be determined precisely even though the distance travelled is the same. In this paper, fuzzy capacitated vehicle routing problem (FCVRP) with travel time expressed by generalized trapezoidal fuzzy numbers is addressed. The fuzzy model is reduced to corresponding crisp one using fuzzy ranking method. Then, we propose ant colony system (ACS) algorithm with the status transition rule, global pheromone trail update and local pheromone trail update for constructing the optimal vehicle routes of the reduced problem. A numerical example of Bright gas 5.5 kg distribution is demonstrated to find the optimal solution of the proposed method. Travel time are obtained basing on real data measured by an electronic system at ten different times. The proposed method is simpler and more computationally efficient when compared to existing methods.