• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2011.06a
• /
• pp.218-219
• /
• 2011

This paper focuses on dispatching strategy for AGVs(Automated Guided Vehicle). The goal of AGV dispatching problem is allocating jobs to AGVs to minimizing QC delay and AGV total travel distance. Due to the highly dynamic nature of container terminal environment, the effect of dispatching is hard to predict thus it leads to frequent modification of dispatching results. Given this situation, single rule-based approach is widely used due to its simplicity and small computational cost. However, single rule-based approach has a limitation that cannot guarantee a satisfactory performance for the various performance measures. In this paper, dispatching strategy based on multicriteria heuristics is proposed. Proposed strategy consists of multiple decision criteria. A muti-objective evolutionary algorithm is applied to optimize weights of those criteria. The result of simulation experiment shows that the proposed approach outperforms single rule-based dispatching approaches.

• Journal of Navigation and Port Research
• /
• v.35 no.6
• /
• pp.501-507
• /
• 2011

This paper focuses on dispatching strategy for AGVs(Automated Guided Vehicle). The goal of AGV dispatching is assigning AGVs to requested job to minimizing the delay of QCs and the travel distance of AGVs. Due to the high dynamic nature of container terminal environment, the effect of dispatching is hard to predict thus it leads to frequent modification of dispatching decisions. In this situation, approaches based on a single rule are widely used due to its simplicity and small computational cost. However, these approaches have a limitation that cannot guarantee a satisfactory performance for the various performance measures. In this paper, dispatching strategy based on multicriteria heuristics is proposed. The Proposed strategy consists of multiple decision criteria. A multi-objective evolutionary algorithm is applied to optimize weights of those criteria. The result of simulation experiment shows that the proposed approach outperforms single rule-based dispatching approaches.

• Journal of Navigation and Port Research
• /
• v.32 no.10
• /
• pp.829-835
• /
• 2008

The objective of this study is to present the two-step dispatching strategy for the purpose of the transport vehicle with multi-function used in container terminal. The two-step dispatching is a method to save the waiting time between transport vehicle and cranes using real time location control. The first step dispatching is to allocate the destination location based on the real time location information. The second step dispatching is to indicate the specific job such as loading, unloading, and pick-up based on the condition of working area. This two-step dispatching strategy decreases the waiting times of the stevedoring system and will contribute at a productivity improvement in container terminal.

• Journal of Navigation and Port Research
• /
• v.44 no.3
• /
• pp.227-234
• /
• 2020

One of the most important operational goals in container terminals is to maximize the quay side productivity by minimizing the turnaround times of the vessels, for which the operations of the quay cranes (QC) to load/unload containers onto/from the vessels should be conducted efficiently without delays. This paper suggests using a policy-based dispatching method for YTs (Yard Tractor) that deliver containers between QCs and the storage yard. The goal of using such a dispatching policy is to maximize the efficiency of the YT operation and accordingly to minimize the QC delays because of late arrivals of the YTs. In particular, in this paper, we modified the previously proposed policy for its application to real container terminal and verified the effect through simulation experiments using real terminal data.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.4
• /
• pp.587-593
• /
• 2006

Development of digital information and internet technology causes the changes of technology environments and companies, and the variety of customers needs has been dynamically changed in terms of integrating information system with customers satisfaction. Moreover a new logistics concept is needed through the sharing information between suppliers and consumers, which maximizes the customers service and its flexibility by changing functional-oriented to process-oriented. Many research papers on transportation studies have focused on the Vehicle Routing Problem (VRP) and Vehicle Scheduling Problem (VSP). However in the real world, it is known that it takes long time to build vehicle scheduling in the process of transporting the amount of orders from the logistics center to the vendors due to the realistic constraints. This paper presents a framework design for each process enabling delivery planning automatically using heuristic algorithm. In addition, an interactive delivery planning system is implemented utilizing the proposed algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.6
• /
• pp.177-193
• /
• 2022

In the near future, it is expected that the use of autonomous mobility-on-demand services will increase. Considering its complicated service components, including vehicle convenience, driving and matching speed, and platform convenience, the priorities of them will need to be determined for a successful establishment. In this context, this study examined the importance rank of each service component through an online survey of potential users of autonomous mobility-on-demand services. As a result of the AHP (Analytic Hierarchy Process) with respect to the upper-level components, driving and matching speed component is selected as most important, followed by platform convenience and vehicle convenience. Mean rank analysis with respect to lower-level components showed that the in-vehicle congestion level of vehicle convenience, waiting time of driving and matching speed, and pre-booking availability of platform convenience each ranked first. Additional analysis regarding each group was conducted to establish a group-specific strategy. As a result, it would be better to focus on a vehicle than a mobile platform when designing services for the region with a high proportion of the older. Moreover, it is recommended to speed up the driving and matching speeds more than the current public transport, alleviate in-vehicle congestion, and enable the users to book the schedule in advance.

• Proceedings of the KOR-KST Conference
• /
• 1998.10b
• /
• pp.466-466
• /
• 1998

도로 교통의 혼잡이 나날이 증가되고 있는 현실 상황에서 이를 해결하기 위한 새로운 도로의 무제한적 건설은 정보의 예산절약, 필요한 도로용지 확보의 어려움, 환경오염 문제 등으로 인해 현실적인 한계에 이르렀다. 따라서, 이러한 도로의 혼잡상황에 효과적으로 대처하기 위해서는 승용차를 이용하고자 하는 수요를 대량수송이 가능한 대중교통 이용수요로 전환시켜야 하며, 이를 위해서는 대중교통의 서비스수준 제고 및 운영 관리 체계 등의 개선이 필요하다. 이를 위한 전략적 및 운영적 측면에서의 대중교통계획은 미래 대중교통수요의 정확한 예측을 전제로 하여 수립되며, 이러한 수요의 예측은 필수적으로 현실을 보다 더 정확하게 묘사해 줄 수 있는 통행배정모형을 필요로 한다. 대중교통 통행배정은 규칙적인 배차시간과 정해진 노선을 운행하는 고정서비스 시스템으로 구성되어 있어서 한 링크 상에서도 여러 개의 운행노선을 고려해야 하기 때문에 승용차 통행배정과는 독립적으로 취급되어 왔으며, 이로 인해 그 동안 많은 연구가 선행되어 있지 않은 실정이다. 본 연구는 교통예측 프로그램 중의 하나인 EMME/2에서 사용하고 있는 대중교통수요 통행배정 모형인 최적전략모형(Optimal Strategy Model)의 단점을 보완하기 위한 것이다. 최적전략모형은 수요 배정시, 최적전략에 속하는 경로들에 대해 단순히 운행횟수에 비례하여 수요를 배정함으로 인해서, 예를 들면 운행횟수는 많지만 환승이 많은 경로에 수요를 많이 배정하는 것과 같은 비현실적인 결과가 발생하기도 한다. 본 연구는 이를 개선하기 위해서, 두 가지 대안을 제시했다. 먼저, 노선배정에 우선되는 최적경로 탐색시 환승노드에서의 환승에 대한 벌점을 그 노선의 운행회수에 줌으로써 환승이 많은 경로에 수요의 배정이 적게 되도록 하는 방법과 두 번째로 수요의 배정시 운행횟수가 아닌 목적지까지의 통행시간과 대시시간에 따른 확률적 배분을 통해 기존 모형의 단점을 보완하고자 했다.

• Journal of the Korea Safety Management & Science
• /
• v.15 no.2
• /
• pp.167-184
• /
• 2013

A cross docking operation involves multiple inbound trucks that deliver items from suppliers to a distribution center and multiple outbound trucks that ship items from the distribution center to customers. Based on customer demands, an inbound truck may have its items transferred to multiple outbound trucks. Similarly, an outbound truck can receive its consignments from multiple inbound trucks. The objective of this study is to find the best truck spotting sequence for both inbound and outbound trucks in order to minimize total operation time of the cross docking system under the condition that multiple visits to the dock by a truck to unload or load its consignments is allowed. The allocations of the items from inbound trucks to outbound trucks are determined simultaneously with the spotting sequences of both the inbound and outbound trucks.

• Proceedings of the Safety Management and Science Conference
• /
• 2005.05a
• /
• pp.65-80
• /
• 2005

대부분의 국가들이 노선버스의 운영을 공공부문에서 담당하고 있으나 우리나라를 비롯한 일부에서만 민간이 운영하고 있어 시민들을 위한 공익성만을 추구 할 수는 없는 입장이며 노선의 선정 또한 사업자와 공공이 협의하여 시행할 수밖에 없다. 이를 개선하기 위하여 버스노선 개편, 공동배차제 등 개선방안을 많은 지자체에서 시행하였지만 시민${\cdot}$업체${\cdot}$공공부문에서의 합의 도출은 지난한 상황이며 실행력이 없는 계획이 되고 있음을 여러 사례에서 볼 수 있다. Internet등 통신기술의 급속한 발달에 따라 통신을 통한 의사표출이 자유롭고 용이해지면서 일반지자체의 경우에 전체 민원 중 교통부문이 차지하는 민원이 $50\%$를 상회하고 있으며, 교통민원 중 $45.3\%$가 노선버스의 정시성 확보 및 운전기사의 불친절, 무정차 통과 등에 관한 것으로써 시민들이 가장 알고싶어 하는 사항이 버스의 실시간 운행상황임을 알 수 있었다. 따라서 본 연구에서는 실시간 버스정보제공을 통해 노선버스 이용자들의 대기시간 감소 및 이용편의를 증진시키고, 이를 통해 승용차 이용자를 대중교통수단으로 유도하여 대중교통을 활성화시키는 버스정보시스템(BIS ; Bus Information System)을 정립하며, 충주시 교통여건을 감안한 버스정보시스템 도입전략을 수립하고, 도입에 따른 기대효과를 분석하여 합리적이고 효과적으로 적용할 수 있는 지방자치단체 특히 충주시의 지능형 교통정보 시스템을 마련하는데 그 목적이 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.6
• /
• pp.118-133
• /
• 2020

Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.