Self-Adaptive Discrete Cuckoo Search Algorithm for the Service Routing Problem with Time Windows and Stochastic Service Time
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Abstract
Making house calls is very crucial to deal with the competitive pressures of the service business and to improve service quality. We design a model called service routing problem with time windows and stochastic service time (SRPTW-SST) that is based on vehicle routing problem with time windows. A self-adaptive discrete cuckoo search algorithm with genetic mechanism (sDCS-GM) is proposed for the model SRPTW-SST. Moreover, we design a selection mechanism to improve the logicality of the algorithm based on the strong randomness of the Lévy flight. We introduce a genetic mechanism and design a neighborhood search mechanism for improving the robustness of the algorithm. In addition, an adaptive parameter adjustment method is designed to eliminate the impact of fixed parameters. The experimental results show that the sDCS-GM algorithm is more robust and effective than the state-of-the-art methods.
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