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… Click to show full 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%. 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%.
               
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