CROWD SHIPPING DELIVERIES THROUGH COMMERCIAL AIRLINES USING MATCHING ALGORITHMS

Abstract

With the overgrowing population and digitalization, crowds are always looking for innovative ways to reduce costs. Crowdsourcing tasks have become the center of attention to reduce costs while achieving similar results, dependent on the assigned task. Crowd shipping, a discipline of crowdsourcing, no doubt has attracted many businesses applications and research interests due to the academic challenges of network flow, but also considerable return rate at freeing up resources and reducing overall businesses costs. In this paper, we propose a crowd shipping application that focuses on using commercial airlines as the means of transportation to reduce worldwide air-fuel consumption by using the available resources instead of manufacturing new air fleets. We achieve this by creating a generic crowd shipping business model that reflects all the domains needed for a successful application. A process flow and two mathematical models were used; the Mixed-Integer Linear Programming (IP) to optimize the matching between peers and Goal Programming (GP) to see the effects of relaxing the constraints in the mathematical model. The work was tested on the North African country regions due to variations in travelers, airports, and airport distributions. It was shown that the greater the ratio of travelers to the customers, the fewer deviations were needed and the higher the package distribution among the travelers. This study demonstrates that as the network becomes broader with more parties, big data analytics and faster matches are required to secure the future of these applications.

Date of Award	2022
Original language	American English
Awarding Institution	HBKU College of Science and Engineering