With the increasing interest in online shopping, the Last Mile delivery is regarded as one of the most expensive and pollutive—and yet the least efficient—stages of the e-commerce supply chain. To address this challenge, a novel location-routing problem with simultaneous home delivery and customer’s pickup is proposed. This problem aims to build a more effective Last Mile distribution system by providing two kinds of service options when delivering packages to customers. To solve this specific problem, a hybrid evolution search algorithm by combining genetic algorithm (GA) and local search (LS) is presented. In this approach, a diverse population generation algorithm along with a two-phase solution initialization heuristic is first proposed to give high quality initial population. Then, advantaged solution representation, individual evaluation, crossover and mutation operations are designed to enhance the evolution and search efficiency. Computational experiments based on a large family of instances are conducted, and the results obtained indicate the validity of the proposed model and method.

Since transmission towers are generally located in areas with complex geological environments, such as mountains and rivers, relying only on conduct regular personnel inspections wastes considerable human and material resources. At present, the existing monitoring system has also the problems of data transmission, parameter accuracy and transmission distance. Based on this premise, a novel transmission tower tilt monistoring system was proposed in this paper. This research adopted the latest Low-Power Wide-Area Network (LPWAN) technology. Among tehm, LoRa (Long Range) is a modulation technology that provides a longer communication distance. NB-IoT (Narrow Band-Internet of Things ) technology is an emerging technology in the IoT field that supports the cellular data connection of low-power devices in a wide area network. The proposed system through the data transmission of a LoRa multinode network, the tilt parameters of tower were uploaded to an online real-time monitoring system through NB-IoT. Each subnode included MPU6050 tilt sensors and a wireless communication LoRa module. The main node contained an NB-IoT module. It can upload the tilt information to the cloud platform. After uploading the data, administrators can arrange timely targeted maintenance for transmission towers with faults according to the analysis results. The proposed approach covers a wide range, has high service quality, and supports many connections.