그룹탐색최적화를 적용한 트럭-드론 스케줄링
Group Search Optimization for Truck-Drone Scheduling
김성수(강원대학교); 신민섭(강원대학교 에너지자원․산업공학부 산업공학전공)
47권 2호, 1~14쪽
초록
In parallel drone scheduling traveler salesman problem, the customer can be served by a single truck or by a fleet of one or more identical drones to minimize the completion time. The vehicle routes customer locations, while the drone fly back and forth between depot and customers. The objective of this paper is to propose novel Routing Group Search Optimization (RGSO) for truck-drone scheduling to find the best schedule and routing of a truck and a droneto better balance vehicle and drone delivery. The RGSO based on Group Search Optimization (GSO) is proposed for truck-drone system with scheduling solution representation. Our proposed RGSO is very effective in finding group which are generated by relative distances of customer locations for routing of truck. Our simulation results show that RGSO is very effective comparing to standard GSO based on the several experiments and analysis.
Abstract
In parallel drone scheduling traveler salesman problem, the customer can be served by a single truck or by a fleet of one or more identical drones to minimize the completion time. The vehicle routes customer locations, while the drone fly back and forth between depot and customers. The objective of this paper is to propose novel Routing Group Search Optimization (RGSO) for truck-drone scheduling to find the best schedule and routing of a truck and a droneto better balance vehicle and drone delivery. The RGSO based on Group Search Optimization (GSO) is proposed for truck-drone system with scheduling solution representation. Our proposed RGSO is very effective in finding group which are generated by relative distances of customer locations for routing of truck. Our simulation results show that RGSO is very effective comparing to standard GSO based on the several experiments and analysis.
- 발행기관:
- 한국경영과학회
- 분류:
- 경영학