Title :
Solving the supermarket shopping route planning problem based on genetic algorithm
Author :
Xiaojia Chen ; Ying Li ; Tao Hu
Author_Institution :
Sch. of Comput., Commun. Univ. of China, Beijing, China
fDate :
June 28 2015-July 1 2015
Abstract :
Nowadays, the supermarket scale and items increase gradually. Customers will take a long time if they want to buy all things they need. Sometimes customers don´t know the location of the goods, or they have to walk a repeated route, which leading to a waste of time, so we need to find the best shopping route. In this paper, we use genetic algorithm to solve this problem for customers. Due to the particularity of this problem, the start and end points of route are fixed, so we need to do some change for operator of GA. This algorithm can calculate a shortest route that isn´t repeated and takes the shortest time to help customers shopping quickly. In the process of experiment, we apply it into a shopping route problem with twenty commodities. The results show that this algorithm can find the best solution after certain number of iterations.
Keywords :
customer services; genetic algorithms; path planning; travelling salesman problems; customers service; genetic algorithm; supermarket shopping route planning problem; Biological cells; Computers; Encoding; Floors; Genetic algorithms; Sociology; Statistics; GA; SRP; crossover operator; mutation operator; selection operator;
Conference_Titel :
Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on
Conference_Location :
Las Vegas, NV
DOI :
10.1109/ICIS.2015.7166649