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Jonghoe Kim

Bio: Jonghoe Kim is an academic researcher from KAIST. The author has contributed to research in topics: Port (computer networking) & Integer programming. The author has an hindex of 7, co-authored 14 publications receiving 317 citations.

Papers
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Journal ArticleDOI
TL;DR: A Mixed Integer Linear Programming (MILP) formulation for derivation of persistent UAV delivery schedules is proposed and a Receding Horizon Task Assignment (RHTA) heuristic is developed and tested with numerical examples for island-area delivery.

131 citations

Journal ArticleDOI
TL;DR: A genetic algorithm is developed to find feasible solutions to the problem of scheduling a system of UAVs and multiple shared bases in disparate geographic locations when a state-of-the-art solver such as CPLEX cannot.
Abstract: The duration of missions that can be accomplished by a system of unmanned aerial vehicles (UAVs) is limited by the battery or fuel capacity of its constituent UAVs. However, a system of UAVs that is supported by automated refueling stations may support long term or even indefinite duration missions. We develop a mixed integer linear program (MILP) model to formalize the problem of scheduling a system of UAVs and multiple shared bases in disparate geographic locations. There are mission trajectories that must be followed by at least one UAV. A UAV may hand off the mission to another in order to return to base for fuel. To address the computational complexity of the MILP formulation, we develop a genetic algorithm to find feasible solutions when a state-of-the-art solver such as CPLEX cannot. In practice, the approach allows for a long-term mission to receive uninterrupted UAV service by successively handing off the task to replacement UAVs served by geographically distributed shared bases.

82 citations

Journal ArticleDOI
TL;DR: An improved mixed integer linear programming (MILP) model is developed that can serve to support the system’s efforts to orchestrate the operations of numerous UAVs, missions and logistics facilities.
Abstract: The flight duration of unmanned aerial vehicles (UAVs) is limited by their battery or fuel capacity. As a consequence, the duration of missions that can be pursued by UAVs without supporting logistics is restricted. However, a system of UAVs that is supported by automated logistics structures, such as fuel service stations and orchestration algorithms, may pursue missions of conceivably indefinite duration. This may be accomplished by handing off the mission tasks to fully fueled replacement UAVs when the current fleet grows weary. The drained UAVs then seek replenishment from nearby logistics support facilities. To support the vision of a persistent fleet of UAVs pursuing missions across a field of operations, we develop an improved mixed integer linear programming (MILP) model that can serve to support the system's efforts to orchestrate the operations of numerous UAVs, missions and logistics facilities. Further, we look toward the future implementation of such a persistent fleet outdoors and develop prototype components required for such a system. In particular, we develop and demonstrate the concerted operation of a scheduling model, UAV onboard vision-based guidance system and replenishment stations.

54 citations

Journal ArticleDOI
Jonghoe Kim1, James R. Morrison1
28 May 2013
TL;DR: A branch and bound algorithm that guarantees an optimal solution and is faster than solving the MILP directly via CPLEX, and a modified receding horizon task assignment heuristic that includes the design problem (RHTAd).
Abstract: A fleet of unmanned aerial vehicles (UAVs) supported by logistics infrastructure, such as automated service stations, may be capable of long-term persistent operations. Typically, two key stages in the deployment of such a system are resource selection and scheduling. Here, we endeavor to conduct both of these phases in concert for persistent UAV operations. We develop a mixed integer linear program (MILP) to formally describe this joint design and scheduling problem. The MILP allows UAVs to replenish their energy resources, and then return to service, using any of a number of candidate service station locations distributed throughout the field. The UAVs provide service to known deterministic customer space-time trajectories. There may be many of these customer missions occurring simultaneously in the time horizon. Each customer mission may be addressed by several UAVs. Multiple tasks may be conducted by each UAV between visits to the service stations. The MILP jointly determines the number and locations of resources (design) and their schedules to provide service to the customers. We then develop a modified receding horizon task assignment algorithm including the design problem (RHTAd) to address the computational complexity of the MILP. Numerical experiments assess the performance of RHTAd relative to the MILP solved via CPLEX. RHTAd is substantially faster with quite acceptable loss of optimality. As such, problems of much larger size can be addressed.

51 citations

Journal ArticleDOI
TL;DR: A mixed integer linear programming (MILP) formulation for the problem of providing simultaneous UAV escort service to multiple customers across a field of operations with multiple sharable LSSs is developed and efficient heuristics to rapidly derive near optimal solutions are developed.
Abstract: A networked system consisting of unmanned aerial vehicles (UAVs), automated logistic service stations (LSSs), customer interface software, system orchestration algorithms and UAV control software can be exploited to provide persistent service to its customers. With efficient algorithms for UAV task planning, the UAVs can autonomously serve the customers in real time. Nearly uninterrupted customer service may be accomplished via the cooperative hand-off of customer tasks from weary UAVs to ones that have recently been replenished at an LSS. With the goal of enabling the autonomy of the task planning tasks, we develop a mixed integer linear programming (MILP) formulation for the problem of providing simultaneous. UAV escort service to multiple customers across a field of operations with multiple sharable LSSs. This MILP model provides a formal representation of our problem and enables use in a rolling horizon planner via allowance of arbitrary UAV initial locations and consumable reservoir status (e.g., battery level). As such, it enables automation of the orchestration of system activities. To address computational complexity, we develop efficient heuristics to rapidly derive near optimal solutions. A receding horizon task assignment (RHTA) heuristic and sequential task assignment heuristic (STAH) are developed. STAH exploits properties observed in optimal solutions obtained for small problems via CPLEX. Numerical studies suggest that RHTA and STAH are 45 and 2100 times faster than solving the MILP via CPLEX, respectively. Both heuristics perform well relative to the optimal solution obtained via CPLEX. An example demonstrating the use of the approach for rolling horizon planning is provided.

46 citations


Cited by
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01 Jan 2016
TL;DR: The linear and nonlinear programming is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can download it instantly.
Abstract: Thank you for downloading linear and nonlinear programming. As you may know, people have search numerous times for their favorite novels like this linear and nonlinear programming, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some infectious bugs inside their desktop computer. linear and nonlinear programming is available in our book collection an online access to it is set as public so you can download it instantly. Our digital library spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the linear and nonlinear programming is universally compatible with any devices to read.

943 citations

Journal ArticleDOI
01 Dec 2018-Networks
TL;DR: This article describes the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning, and provides insights into widespread and emerging modeling approaches to civil applications of UAVs.
Abstract: Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

576 citations

Journal ArticleDOI
TL;DR: A heuristic solution approach that consists of solving a sequence of three subproblems that effectively solves problems of practical size within reasonable runtimes is proposed and supports anticipated future systems that feature automation for UAV launch and retrieval.
Abstract: This paper considers a last-mile delivery system in which a delivery truck operates in coordination with a fleet of unmanned aerial vehicles (UAVs, or drones). Deploying UAVs from the truck enables customers located further from the depot to receive drone-based deliveries. The problem is first formulated as a mixed integer linear program (MILP). However, owing to the computational complexity of this problem, only trivially-sized problems may be solved directly via the MILP. Thus, a heuristic solution approach that consists of solving a sequence of three subproblems is proposed. Extensive numerical testing demonstrates that this approach effectively solves problems of practical size within reasonable runtimes. Additional analysis quantifies the potential time savings associated with employing multiple UAVs. The analysis also reveals that additional UAVs may have diminishing marginal returns. An analysis of five different endurance models demonstrates the effects of these models on UAV assignments. The model and heuristic also support anticipated future systems that feature automation for UAV launch and retrieval.

220 citations

Journal ArticleDOI
TL;DR: This paper surveys established and novel last-mile concepts and puts special emphasis on the decision problems to be solved when setting up and operating each concept, and systematically record the alternative delivery concepts in a compact notation scheme.
Abstract: In the wake of e-commerce and its successful diffusion in most commercial activities, last-mile distribution causes more and more trouble in urban areas all around the globe. Growing parcel volumes to be delivered toward customer homes increase the number of delivery vans entering the city centers and thus add to congestion, pollution, and negative health impact. Therefore, it is anything but surprising that in recent years many novel delivery concepts on the last mile have been innovated. Among the most prominent are unmanned aerial vehicles (drones) and autonomous delivery robots taking over parcel delivery. This paper surveys established and novel last-mile concepts and puts special emphasis on the decision problems to be solved when setting up and operating each concept. To do so, we systematically record the alternative delivery concepts in a compact notation scheme, discuss the most important decision problems, and survey existing research on operations research methods solving these problems. Furthermore, we elaborate promising future research avenues.

169 citations

Journal ArticleDOI
TL;DR: An in-depth updated overview of the seaside operations at container terminals is presented and new avenues for academic research based on current trends and developments in the container terminal industry are identified.
Abstract: Seaside operations are considered the bottleneck operation in most container terminals around the world. This paper presents an in-depth updated overview of the seaside operations at container terminals and highlights current trends and developments. We review and classify scientific journal papers on container terminal seaside operations, published between 2004 and 2012. The paper also discusses and challenges the current operational paradigms on seaside operations. Lastly, the paper identifies new avenues for academic research based on current trends and developments in the container terminal industry.

162 citations