Frontiers in Management Research

Download PDF (531.9 KB) PP. 75 - 80 Pub. Date: July 1, 2018

DOI: 10.22606/fmr.2018.23002

• Zhao Qingju^*
  School of Information Beijing Wuzi University, No.321, Fuhe Street, Tongzhou District, Beijing 101149, P.R.China

With the popularity of the Internet, the accelerating of the rhythm of people's life, ordering food online has become a new way of life. Under the background of ordering food on the Internet, how to arrange distribution routes and deliver meals to customers in time has become an urgent problem to be solved after the customer's order. The "first come first served" mode of traditional catering reduces the efficiency of orders and increases the operation cost of businesses. Sometimes, due to the shortage of distribution staff, the order waiting time increases. As a result, order delays and customer satisfaction are reduced. The reputation of the restaurant has also been affected. This paper starts from solving practical problems, considering customer location and customer needs, and tries to build two stage algorithm to optimize order routing problem. First, we use the idea of "clustering path optimization" to aggregate customers to K areas according to the location of our customers. On this basis, the capacity limit of distribution vehicles is increased. This will make the customer point in the region closer. And save operation cost. Then, the genetic algorithm is used to optimize the delivery path in the K class area. Finally, the practicability and effectiveness of the algorithm are verified by simulation experiments.

Online ordering; regional division; K-means clustering; genetic algorithm

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