Truck-Drone Pickup and Delivery Problem with Drone Weight-Related Cost

Yang Xia, Tingying Wu (), Beixin Xia () and Junkang Zhang
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Yang Xia: School of Management, Shanghai University, Shanghai 200444, China
Tingying Wu: Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain (AKL-CLaS), International Institute of Finance, School of Management, University of Science and Technology of China, Hefei 230026, China
Beixin Xia: School of Management, Shanghai University, Shanghai 200444, China
Junkang Zhang: School of Management, Shanghai University, Shanghai 200444, China

Sustainability, 2023, vol. 15, issue 23, 1-15

Abstract: Truck-drone delivery is widely used in logistics distribution for achieving sustainable development, in which drone weight greatly affects transportation cost. Thus, we consider a new combined truck-drone pickup and delivery problem with drone weight-related cost in the context of last-mile logistics. A system of integer programming is formulated with the objective of minimizing the total cost of the drone weight-related cost, fixed vehicle cost and travel distance cost. An improved adaptive large neighborhood search algorithm (IALNS) is designed based on the characteristics of the problem, several effective destroy and repair operators are designed to explore the solution space, and a simulated annealing strategy is introduced to avoid falling into the local optimal solution. To evaluate the performance of the IALNS algorithm, 72 instances are randomly generated and tested. The computational results on small instances show that the proposed IALNS algorithm performs better than CPLEX both in efficiency and effectiveness. When comparing the truck-drone pickup and delivery problem with drone weight-related cost to the problem without drone weight-related cost, it is found that ignoring the drone weight constraints leads to an underestimate of the total travel cost by 12.61% based on the test of large instances.

Keywords: truck-drone pickup and delivery problem; drone weight-related cost; adaptive large neighborhood search algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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