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A Systematic Approach to Order Fulfillment of On-demand Delivery Service for Bento Industry
Author(s) -
Rong-Chang Chen,
Chih-Hui Shieh,
KaiTing Chan,
Shin-Yi Chiu,
Jyun-You Fan,
Yu-Ting Chang,
Nuo-Jhen Ma
Publication year - 2013
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2013.05.014
Subject(s) - computer science , profit (economics) , order (exchange) , service (business) , operations research , destinations , service system , tourism , marketing , business , finance , engineering , political science , law , economics , microeconomics
[[abstract]]This paper proposes a three-stage approach to solve the order fulfillment problem of on-demand delivery service with large quantities of orders for bento (boxed meal) industry. At the first stage, a geographic information system (GIS) is used to locate the delivery destinations designated by customers. Then the k-means algorithm is utilized to cluster customer orders based on locations and according to the number of delivery vehicles. At the final stage, a genetic algorithm (GA) is employed to minimize the total travel distance of deliveries. Experimental results show that the proposed approach is highly feasible and very potential in dealing with the present order fulfillment problem. In addition, the influences of increasing the number of clusters on the profit and the service level are discussed

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