Algoritma Ant Colony Optimization (ACO) dengan Mutasi dan Local Search Untuk Menyelesaikan Vehicle Routing Problem
Abstract: Vehicle routing problem (VRP) is one of the
transportation problem that can be described as a set of vehicles that start
and end its journey to serve a customer at a facility called a depot, with
every customer has a demand or request, and all of the vehicle has same
capacity and maximum total distance of vehicle. The thesis aims to determine
the optimal route for a number of vehicles as the solution of the problem of
vehicle routing problem using Ant Colony Optimization (ACO) algorithm with
mutation and local search process that furthermore called by Improved Ant
Colony Optimization (IACO) algorithm. IACO algorithm is ant colony optimization
(ant algorithm) which coupled with the process of mutation and local search to
improve solutions. Ant colony optimization algorithm is an algorithm that
mimics the behavior of ants in search of food by finding the shortest route
starts from the nest to the food place. IACO algorithm includes five basic processes,
namely the process of initialization parameters, construction of the route, the
process of mutation, local search, and update the pheromone. Mutation process
used is a reciprocal exchange, and the local search process used is a local
search 2-opt exchange. Data from some of the problems of vehicle routing
problem that has many variations on the customer, vehicle capacity, and maximum
total distance of vehicle implemented on IACO. Programs created with the Java
programming language and use the NetBeans IDE 7.0 software for implementing the
solution in the search algorithm IACO. Based on the comparison of results for
different parameter values, the smaller the value of alpha, rho, and the
constant Q, and the greater the value of beta produces a better solution.
Penulis: Muhammad Harun Ar
Rosyid, Herry Suprajitno, Miswanto
Kode Jurnal: jpmatematikadd130071
