• IE interfaces
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• v.11 no.1
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• pp.119-129
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• 1998

The relative importance of Logistics in steelworks industry is rather higher among other business activities. The objective of the paper is to propose the methodology for real-time vehicle scheduling for scrap disposal in the steelworks industry. Currently, the rule necessary to assign vehicles to a specific job is strictly fixed. The paper adopts the multi-pass rule selector (MPRS) that suggests a promising rule used for vehicle dispatching for a period of time. The MPRS is regularly invoked if necessary and then evaluates a set of rule candidates to select the best rule with respect to the system performance criteria. The experiment shows that the proposed approach outperforms the current single-pass strategy.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.103-110
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• 2010

Due to the increasing amount of electronic control system in a vehicle, the automotive software is increasingly sophisticated and complicated. Therefore it may be faced a time critical problem caused by its complexity. In order to solve such problems, the automotive electronic system can use a real-time scheduling mechanism based on predictability. We first consider the standard specification of the AUTOSAR OS and uC/OS-II such as its scheduling theory with time determinism. In this paper, we propose the scheduling algorithm to be conformable to a conformance class of OSEK/VDX specification. Algorithm analysis shows that our scheduling algorithm outperforms an existing Trampoline OS by intuition.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.249-252
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• 2004

The automatic determination of vehicle operation status as well as continuous tracking of vehicle location with intelligent management is one of major elements to achieve the goals. Especially, vehicle operation status can only be analyzed in terms of expert experiences with real-time location data with scheduling information. However the scheduling information of individual vehicle is very difficult to be interpreted immediately because there are hundreds of thousand vehicles are run at the same time in the national wide range workplace. In this paper, we propose the location-based knowledge management system(LKMs) using the active trajectory analysis method with routing and scheduling information to cope with the problems. This system uses an inference technology with dispatching and geographic information to generate the logistics knowledge that can be furnished to the manager in the central vehicle monitoring and controlling center.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• Proceedings of the Korean DIstribution Association Conference
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• 2003.05a
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• pp.55-70
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• 2003

The most transport companies are placing increasing emphasis on powerful new techniques for planning their vehicle operations. They have tried to improve their vehicle control and customer service capability by adopting tile advanced information technology, such as GPS(Global Position System) and Using Digital Map. But researches on the VRSP(vehicle routing St schedule problem) in this situation were very few. The purpose of this research is to develop vehicle scheduling heuristics for making a real-time dynamic VRSP under the situation that GPS and using Digital Map are equipped to the transport company. Modified savings techniques are suggested for the heuristic method and an insertion technique is suggested for the dynamic VRSP. The urgent vehicle schedule is based on the regular vehicle schedule. This study suggest on VRSP system using GPS and Digital Map and the performance of the suggested heuristics is illustrated through an real case example.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.114-120
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• 2002

In a distributed real-time control system, it is essential to confirm the timing behavior of all tasks because these tasks of each real-time controller have to finish their processes within the specified time intervals called a deadline. In order to satisfy this objective, the timing analysis of a distributed real-time system such as shcedulability test must be performed during the system design phase. In this study, a simple application of CAN fur a vehicle body network system is formulated to apply to a holistic scheduling analysis, and the worst-case execution time (WCET) and the worst-case end-to-end response time (WCRT) are evaluated in the point of holistic system view.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.1
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• pp.59-64
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• 2020

Scheduling of electric vehicles and optimizing for charging waiting time have been critical. Meanwhile, it is challengeable to exploit the fluctuating data from electric vehicles in real-time. We introduce an optimal routing algorithm and a simulator with electric vehicles obeying the Poisson distribution of the observed information about time, space and energy-demand. Electric vehicle routing is updated in every cycle even it is already set. Also, we suggest an electric vehicle routing algorithm for minimizing total trip time, considering a threshold of the waiting time. Total trip time and charging waiting time are decreased 34.3% and 86.4% respectively, compared to the previous algorithm. It can be applied to the information service of charging stations and utilized as a reservation service.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.1-8
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• 2014

In recent years, much attention has been paid to the development of intelligent vehicles that integrate automotive technology into the information technology, with the aim of improving user friendliness and stability. The representative function is a autonomous driving and a cruise control. In designing such vehicles, it is critical to address the real-time issues (i.e., real-time vehicle control and timely response). However, previous research excluded the real-time scheduling. We develop a model car with unmanned cruise control, design the real-time scheduler using cyclic executive to easily adapt the model car, and provide some insight into potential solutions based on various experiments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1170-1177
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• 2006

We apply VRP(Vehicle Routing Problem) to sludge collection system in this study. Sewage stores of villages are located in each village around a multipurpose dam. Sludge which is produced in sewage store of village is transported from the sewage store of village to the sewage treatment plants by the special purpose vehicle such as the tank lorry. In this paper, we propose sludge collection strategies which allocate each sewage store of village to sewage treatment plants and decide the schedule of sludge collection in order to collect sludge efficiently. The strategies aim to decrease transportation cost with deciding proposed vehicle routing and scheduling the sludge collection. When we decide route of vehicles, we consider the collection time in sewage store of village, distance between sewage store of villages and vehicle information as average velocity of vehicle, operation time of vehicle driver. We also develop the SCMS(Sludge Collection Management System) based on windows system with real data which is used in certain circumstance. And we experiment to figure out vehicle route and transportation cost throughout changing input data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.105-114
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• 2007

In this paper, we propose sludge collection strategies which allocate each sewage store of village to sewage treatment plants and decide the schedule of sludge collection in order to collect sludge efficiently. The strategies aim to decrease transportation cost with deciding proposed vehicle routing and scheduling the sludge collection. When we decide route of vehicles, we consider the collection time in sewage store of village, distance between sewage store of villages and vehicle information as average velocity of vehicle, operation time of vehicle driver. We also develop the SCMS (Sludge Collection Management System) based on windows system with real data which is used in certain circumstance. And we experiment to figure out vehicle route and transportation cost throughout changing input data.