한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제24권1호
  • /
  • Pages.167-178
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  • 2019
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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Multi Objective Vehicle and Drone Routing Problem with Time Window

  • Park, Tae Joon (Dept. of Yonsei School of Business, Yonsei University) ;
  • Chung, Yerim (Dept. of Yonsei School of Business, Yonsei University)
  • 투고 : 2018.10.02
  • 심사 : 2018.12.28
  • 발행 : 2019.01.31
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초록

In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.

키워드

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Fig. 1. Network Model for MOVDRPTW

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Fig. 2. Structure of HMOEA

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Fig. 3. Random Generation of Initial Solutions

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Fig. 4. Variable Length Chromosome in the HMOEA

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Fig. 5. Route Exchange Crossover

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Fig. 6. Pseudo Code of Pareto Ranking and Elitism

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Fig. 7. Off-set Local Search Range

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Fig. 8. Desired Time Window and Arrival Time of the Two Customers in the Off-set Relationship

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Fig. 9. Customer Locations in Songpagu in Seoul

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Fig. 10. Average total cost

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Fig. 11. Total costs and the number of used vehicles and drones in each of four Scenarios

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Fig. 12. Average Service Cost

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Fig. 13. Time Cost and Operating Cost

Table 1. The operating cost and time cost per customer in drone and vehicle route in the drone mixed strategy./ () indicated the value of upper 20% of EA population

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