Department   Ritsumeikan Asia Pacific University  College of Sustainability and Tourism
   Position   Professor
Language English
Publication Date 2015/03
Type Research paper (Academic/Professional Journal)
Peer Review Peer reviewed
Title Optimization of Convenience Stores’ Distribution System with Web Scraping and Google API Service
Contribution Type Corresponding
Journal ICACT Transactions on Advanced Communications Technology (TACT)
Volume, Issue, Page 4(2),pp.596-606
Author and coauthor T. Q. Le, D. Pishva
Details Vehicle Routing Problem (VRP) has never become an obsolete research theme in the field of operations research and supply chain management. Considering that significant number of researchers have already tried addressing VRPs with mathematical modeling and algorithmic approaches, this paper focuses on a practical implementation and employs programming techniques to cope with a particular business problem in convenience stores’ distribution system. It optimizes goods distribution process of convenience stores business, which involves lorries delivering products from a warehouse to a network of several convenience stores in a single trip, collecting their garbage, passing by a gas station for re-fueling when needed, and returning back to the warehouse. A mathematical ‘network flow model’ is initially developed to examine the problem. Geographical data of convenience stores, their associated warehouses, garbage dumpsites and gas stations are subsequently retrieved through programming with the ‘web scraping’ technique. A prototype of web-based delivery navigation system that utilizes Google API service is then developed to solve the optimal convenience stores’ networking problem. Furthermore, a more general perspective of the problem is illustrated with cluster-first-route-second heuristic algorithm and a mobile version of the prototype, which can serve as a real time navigation system for delivery truck drivers, is developed. Validity of obtained results is also examined by other known methods to justify optimality and fast performance of the approach.
ISSN 2288-0003