협업적 차량경로관리를 위한 개미군 최적화 방법
Ant Colony Optimization for Collaborative Vehicle Routing Management
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초록
본 연구의 목적은 건자재 물류시장의 효율적인 협업적 차량경로관리를 위한 개미군 최적화 방법을 제시하고자 한다. 건자재 물류는 출발지 석산에서 모래, 자갈을 덤프트럭을 이용하여 목적지 레미콘공장까지 운송함에 있어 덤프트럭의 운송이 단위 석산별로 개별 운송방식을 취하고 있다. 보통의 경우 대부분의 차량들이 출발지로 복귀 시 공차운행을 하게 되어 운송효율이 저하되는 원인이 되고 있다. 따라서 본 연구에서는 협업적 차량경로관리를 위한 개미군 최적화 방법을 적용하는 방법을 제시하고 파라미터 설정에 따른 개미군 최적화 방법의 결과를 비교 분석하였다. 개미군 최적화 방법의 파라미터 중 α값과 β값의 변화에 따른 결과를 실험하였으며 가장 좋은 결과를 보여준 α값과 β값을 제시하였다.
Abstract
This paper proposes Ant Colony Optimization (ACO) for Collaborative Vehicle Routing Problem (CVRP) in the aggregate industry. The objective of the method is to minimize total traveling distances. In the aggregate industry the individual companies are main operators, which resulted in low utilization of vehicles because of lack of collaboration. Dump trucks carry the sand and gravels from the origin to the destination in one direction and they can carry waste materials when returning. More efficient operation can reduce empty returning vehicles. The data we used in the analysis is a part of real data in Seoul Metropolitan Areas in 2006. In this paper, Ant Colony Optimization Algorithm is adopted for simulation. We found the best value of α and β to this case.
참고문헌 (25)
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