Z. Indra, Chairunisah, N.R. Refisis
Every company cannot be separated from transportation problems, both for the procurement of raw materials or in allocating finished goods. One method that can be used to minimize transportation costs is to optimize the distribution of goods as possible, using transportation methods. Given the complexity of supply chain problems, the use of metaheuristic methods such as genetic algorithms is expected to be able to quickly resolve supply chain problems, where time is a mandatory requirement to satisfy the market. The problem in the application of genetic algorithms in this study is the distribution of three levels. This study uses 3 producers, 3 agents, 5 distributors and 7 retails. Optimal solutions were obtained from population sizes of 10, 20, and 30 with a combination of mutation probabilities, 0.1 and 0.2, crossover probabilities of 0.1 and 0.2, amounting to 100.454, by conducting experiments 20 times for each genetic parameter. The lowest cost distribution is obtained at population size 20, mutation probability 0.1 and crossover probability 0.2. Based on these results obtained goods distribution channels from each producer, agent and distributor. © Published under licence by IOP Publishing Ltd.
Mathematic Departement, Universitas Negeri Medan, Jl. Willem Iskandar, Medan, Indonesia
