KEYWORDS: Mathematical optimization, Genetic algorithms, Convex optimization, Internet of things, Berkelium, Mathematical modeling, Internet technology
Static bus scheduling cannot meet the requirements of bus operation well due to the uncertainty of passengers in the process of bus operation. In this paper, for the bus scheduling problem in the Internet of Things environment, a singleroute bus dynamic departure scheduling optimization model with the minimum total passenger waiting time as the objective function is established, and a genetic algorithm is used to adjust the bus departure time at the first stop in real time through a case of dynamic passenger flow change. The experimental results show that the optimized scheduling scheme reduces the total passenger waiting time by 6.8%, which verifies the effectiveness of the model.
Warehouse activity is the intermediate link between supply and consumption, which can buffer and balance the contradiction between supply and demand. The right choice of warehouse location can reduce transportation costs and improve service quality fundamentally. In this paper, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method are combined to construct an evaluation model. Taking two alternative warehouses in the urban area as examples, the analysis of site selection and fuzzy evaluation are completed, so as to determine the best site selection in order to provide a favorable decision for the reasonable choice of managers.
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