To fully take the advantages of conventional bus and subway, and to maximize the overall feeder efficiency of the public transport system, the topic of feeder bus route optimization is studied in this paper. Considering the origin destination demand of passenger flow between subway stations and bus stations and transfer characteristics, the objective function is established with the minimum sum of bus operation cost and passenger travel cost. Taking into account the integrity of the feeder bus route, the rationality of the route, the route capacity and the station transfer factors, the constraints of the optimization model are constructed. Based on the idea of the genetic algorithm, the solution algorithm of the optimization model is developed. The genetic algorithm and enumeration algorithm are used to solve the optimization of the feeder bus route in this case, and the accuracy and efficiency of the solution are analyzed. The influence of the number of feeder bus routes on the system in the case network is compared and discussed. We compare and analyze the differences between the original bus network and the feeder bus network in terms of bus operation cost, passenger flow demand and total passenger travel cost. The research shows that the model and algorithm can find the approximate optimal solution of the feeder bus network scheme related to the subway through fewer iterations. The number of routes in the model has little impact on the whole feeder system, and the optimization scheme using five routes is effective and reasonable in this paper. Compared with the existing bus network, the optimization scheme has obvious advantages in improving the passenger-carrying rate, reducing the per capita travel cost and improving the overall operation efficiency of the system.
Energy harvesting (EH) from ambient environment is an attractive and green solution to the problem of limited lifetime of wireless and mobile devices such as cognitive relay nodes. In this paper, we extend the previous works on cognitive two-way relaying network by introducing energy harvesting transceiver nodes that can accumulate energy to improve the lifetime of the relay network. We investigate an optimal offline joint relay selection and power allocation scheme where secondary transceivers and relays are energy harvesting nodes. We put forward an offline optimization problem of the maximization of the amplify-and-forward (AF) cooperative communication system throughput which can be solved by Lagrange function. Numerical results show that the proposed scheme performs better than random relay selection scheme on the restriction of transmit power and primary user (PU) interference.
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