- 著者
- Yohei HAZAMA Hitoshi IIMA Yoshiyuki KARUNO Kosuke MISHIMA
- 出版者
- The Japan Society of Mechanical Engineers
- 雑誌
- Journal of Advanced Mechanical Design, Systems, and Manufacturing (ISSN:18813054)
- 巻号頁・発行日
- vol.15, no.6, pp.JAMDSM0069, 2021 (Released:2021-10-15)
- 参考文献数
- 33
- 被引用文献数
- 11
In recent years, efficient logistics has become indispensable, and using unmanned aerial vehicles (UAVs) or drones is promising for considerably reducing the cost and time required for parcel delivery. This paper addresses a parcel delivery scheduling problem. In this problem, a truck loaded with drones and parcels leaves a distribution center and stops at some points on a fixed route. At each point, the drones take off and deliver parcels to customers. We define this problem as finding the assignment of customers to both the drones and their takeoff points. Then, we propose a genetic algorithm (GA) for finding a near-optimal solution in a short time. In the proposed GA, a solution is represented using sets of customers assigned to the takeoff points, and a heuristic rule determines the assignment to the drones. The crossover operation enables offspring to inherit the customer sets. Experimental results show that the proposed GA can successfully find an optimal or a near-optimal solution faster than an integer programming solver for almost all instances. In addition, it significantly outperforms other GAs using a different crossover.
- 著者
- Kazuhiro SHIN-IKE Hitoshi IIMA
- 出版者
- The Society of Instrument and Control Engineers
- 雑誌
- SICE Journal of Control, Measurement, and System Integration (ISSN:18824889)
- 巻号頁・発行日
- vol.9, no.3, pp.144-150, 2016 (Released:2016-06-25)
- 参考文献数
- 11
- 被引用文献数
- 1
In this study, we propose a method for determining the classroom seating arrangements considering relationships between one student and the other students sitting around him or her. The method for determining the classroom seating arrangements is constructed based on our proposed genetic algorithm. In order to determine the optimal classroom seating arrangements, the genetic algorithm is applied on the basis of the questionnaire result of how students feel when they take a class on the seats assigned to them and the analysis of each student's personality. Experiments are carried out in order to verify the effectiveness of the proposed method.