A Decoding Method for Applying Swarm Intelligence Optimization Algorithm to Solve the Cold Chain Vehicle Logistics Routing Problem

In order to apply swarm intelligence optimization algorithms to solve cold chain vehicle routing problem efficacy and conveniently, a simplified decoding method was proposed. Based on the common encoding form in continuous space for swarm intelligence optimization algorithms, it divided the decoding process into three sections: decoding the service sequence of customers, assigning customer and determining the route of each vehicle, calculating circularly and outputting the whole plan. It did not need to design new encoding form and executed efficacy. Experiments with two different scale problem were introduced to test the performance of the decoding method applied in 9 algorithms. The results showed that the method can be used in swarm intelligence algorithms to solve the cold chain logistics vehicle routing problem. In addition, it also can be seen that different algorithms showed different performances due to their search mechanisms, although they were based on the same decoding method.