A fuzzy collaboration system for ubiquitous loading/unloading space recommendation in the logistics industry. (June 2017) - Chen, Toly; Lin, Chi-Wei
Abstract: A fuzzy collaboration system was designed for ubiquitous loading/unloading space recommendation in the logistics industry. The designed system allows drivers to share information regarding the availability of loading/unloading spaces without providing the exact number of available loading/unloading spaces, thus promoting drivers to use the system. To derive the exact number of loading/unloading spaces from the inexact information, a quadratic programming problem was formulated and solved. In addition, driver location and speed were modeled using fuzzy numbers to account for the uncertainty of their locations. Subsequently, fuzzy cross-referencing was used so that loading/unloading space information can be referenced from more than one location. The proposed methodology was applied to a small region in Seatwen District, Taichung City, Taiwan. The designed system reduced the average time required for a driver to locate a nearby loading/unloading space by 72%. Highlights: Loading/unloading spaces are required to support the smooth operations of a logistics company. A fuzzy collaboration system was designed for ubiquitous loading/unloading space recommendation. The designed system reduced the average time to locate a nearby loading/unloading space by 72%.