OPTIMASI FUZZY ADAPTIF PARTIKEL SWARM PADA PERMASALAHAN RUTE KENDARAAN DENGAN PEMISAHAN PENGIRIMAN

Abstract

This study aims to find the shortest route models and the use of
utilities (vehicles) as little as possible so that costs can be minimized with
split delivery imposed. Split Delivery Routing Problem (SDVRP) is a
variation of the classical VRP, where the assumption of a single visit
eliminated and customers can be served by a different vehicle. This study
show that the cost savings of more than 50% would be obtained if split
delivery enforced. Parameters used in the simulation using Fuzzy
Adaptive Particle Swarm algorithm is NP = 40, T = 300, max = 0, min =
0,4, c1 = 2, c2 + c3 = 2 and maximum distance is 400 kilometer. And the
results obtained from simulation is used four vehicles and four route, and
minimum distance is 42.3149. After be compared with tabu search
Genreau et al method, FAPSO method can increase 1.84% achievement of
the best solution. While the tabu search method used Gendreau et al able
to increase 1.62% achievement of the best solution.