Affiliation:
1. College of Energy and Mining Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Abstract
In this study, a bi-objective optimization model was established to solve the cooperative distribution problem of a multi-center hybrid fleet by integrating reverse logistics under real-time road conditions. According to the characteristics of the problem and considering the power level and battery capacity of electric vehicles, the multi-objective immune genetic algorithm (MOIGA) was designed and compared with an elitist strategy genetic algorithm, i.e., the fast non-dominated sorting genetic algorithm (NSGA-II). The scale of the MOIGA solution set exceeded that of the NSGA-II, which proved that the global search ability of MOIGA was better than that of the NSGA-II. The operating efficiency of the MOIGA was lower than that of the NSGA-II, but it could also find the optimal solution within an acceptable time range. This method can reduce the total cost of operating a hybrid fleet and can meet the needs of customers, and therefore, improve customer satisfaction.
Funder
Natural Science Foundation of China
Research on the Development Trend and Countermeasures of Industrial Internet in Shandong Province
Research on the Construction Path and Effect Evaluation System of First-Class Undergraduate Majors in Shandong Province
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
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