International Journal of Science, Engineering and TechnologyAuthors: Garima Goyal, Neti Thakkar, Shivani Goyal, Swastika Sakshi, Tavishi Jain
Abstract: Online food-delivery platforms must decide which vehicles serve which kinds of orders. This paper formulates that decision as a transportation problem and solves it with real operating data. Using 43,641 complete delivery records from the Metropolitan and Urban segments of a Zomato dataset (44 days, 11 February to 6 April 2022), delivery capacity by vehicle type (motorcycle, scooter, electric scooter) is treated as the supply, eight city-by-traffic conditions as the demand, and the historical mean delivery time of each vehicle in each condition as the unit cost. A dummy destination balances the table. The problem is solved with the North-West Corner, Least Cost and Vogel approximation methods, the optimality of the best starting solution is tested with the MODI method, and the result is confirmed in Excel Solver. On a typical day the optimal plan lowers total expected delivery time from 25,680 to 24,357 minutes, a reduction of 5.15% (27.12 to 25.72 minutes per order), by keeping motorcycles on low-traffic orders and giving scooters and electric scooters the congested ones. Over all 44 days the reduction is 5.06%. The saving remains positive under a 25% demand increase combined with a 10% workforce cut (2.87%) and falls to about 1.7% when partner capacity is set close to its observed average. Shadow prices show that an extra order of scooter or electric-scooter capacity saves about 2.3 and 2.8 minutes, while extra motorcycle capacity has no value on a typical day.
DOI: https://doi.org/10.5281/zenodo.23340443
