| dc.description.abstract | The multi-depot capacitated vehicle routing problem (MDCVRP) is a variation of the vehicle routing problem (VRP) modeled from distribution problems in the industrial world. This problem is a complex optimization problem in the field of operations research in applied mathematics. The MDCVRP is very interesting to discuss and find the best solution method. In this study, the authors apply the modified migrating birds' optimization (MMBO) algorithm, which is a hybrid of the migrating birds' optimization (MMBO) and iterated local search (ILS) algorithms. The purpose of this study is to analyze the results of applying the algorithm in solving MDCVRP. We used 20 MDCVRP data in simulation, grouped into four sizes (25, 50, 75, and 100 points). Based on the results of this research, it is known that the MMBO algorithm can produce the following solutions. First, on the data of 25 points, the experiment reaches the optimal value with small convergent iterations. Second, the best results on the data of 50 points have reached optimal value, but some other results have not been optimal. And, third, for data of 75 and 100 points, there is no optimal solution obtained by the MMBO algorithm. These results conclude that the MMBO algorithm effectively solves the MDCVRP problem with small data, but the bigger data, the more ineffective. | en_US |
