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NTIS 바로가기The journal of Bigdata = 한국빅데이터학회지, v.5 no.1, 2020년, pp.155 - 180
It takes the most important role the problem of assigining vehicles and desigining optimal routes for each vehicle in order to enhance the logistics service level. While solving the problem, various cost factors such as number of vehicles, the capacity of vehicles, total travelling distance, should ...
핵심어 | 질문 | 논문에서 추출한 답변 |
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VRP 알고리즘은 어느 시스템에 탑재되는가? | 이러한 VRP 알고리즘은 Transportation Management system (TMS)에 탑재된다(Ko & Evans, 2007; Karadimas, et al., 2008). | |
TMS의 운영 목적은? | , 2008). TMS는 전체 시스템의 효율성 극대화 및 비용 최소화를 목적으로 운영되는데, 이를 위해 투입 차량 대수, 총 운행 및 시간으로 구성되는 비용함수를 최소화하기 위한 방안을 수립한다. 그러나 앞의 비용 항목 외에도 실제 현장에서는 정량적으로 측정하기 어려운 항목이 존재하여 수리 모형으로 인해 도출된 최적해가 반드시 실제 현장에 적용될 수 있다고 보장할 수는 없다. | |
Cluster-First Route-Second 접근법이란 어떤 방법인가? | 이를 위해 본 연구에서는 전통적인 VRP 를 해결하기 위한 방법 중 Cluster-First Route-Second (CFRS) 접근법을 활용한다. CFRS는 배송기사가 방문해야 할 위치를 다수의 군집으로 나눈 다음 군집 내에서의 최적의 배송 경로를 설계하는 방법이다. CFRS는 단순히 배송 거리 혹은 시간을 기준으로 개별 차량의 이동경로를 설정하는 기존의 방법과는 달리 방문지 사이의 특성을 고려하여 군집을 구성하게 되면 앞서 언급한 배송차량 혹은 기사들 사이의 불균형을 사전에 방지할 수 있다. |
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