Algoritma Particle Swarm Optimization dengan Local Search (PSO-LS) sebagai Metode Penyelesaian Uncapacitated Facility Location Problem (UFLP)
Abstract: Uncapacitated
facility location problem is defined as a problem to find the optimal location
to build a facility that will serve the customer with the assumption that the
built facility does not have a limited number to serve the customers. Particle
Swarm Optimization with Local Search (PSO-LS) algorithm is combination of PSO
algorithm and Local Search (LS) Algorithm. The couple of optimization algorithm
expected to optimize searching UFLP solutions. The process of algorithm begins
by generating the initial positions and velocities of particles, determine the
open facility vector, and then make evaluation to obtain value of fitness.
Hereinafter specified for each personal best and global best particle to the
whole swarm. At iteration of algorithm, performed the particle velocity and
position update, and then performed the evaluation process and the personal
best and set a new global best. PSO algorithm solution (global best) is the
initial solution for Local Search Algorithms. Initial solution is then modified
to form new solutions. Flip operation is then performed on the new solution.
The process of making a conclusion is at the end of the iteration solution
PSO-LS, by taking the value of the minimum objective function. The data used is
the data 10 to 15 customer locations and data 50 locations with 50 customers
and solved by the programming language Java Netbeans IDE 7.1.2 with the
objective function (cost) for the minimum data 10 locations with 15 customers
amounted 149,690.47500000003 unit. While the data for 50 locations with 50
customer acquired a fee of 793,183.89900000000 unit.
Penulis: Umi Lailatul
Muyassaroh
Kode Jurnal: jpmatematikadd130071
