• Title/Summary/Keyword: 동적 휴리스틱

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Thermal Sensor Allocation and Placement Algorithm on FPGA Based Design (FPGA 기반 설계의 온도 센서 최적 배치 알고리즘)

  • Hyeon, Cheol-Hwan;Nam, Hyoung-Wook;Kim, Yong-Ju;Kim, Tae-Whan
    • Proceedings of the Korean Information Science Society Conference
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    • 2008.06b
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    • pp.292-297
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    • 2008
  • 본 논문은 FPGA 기반 설계에서 주변보다 급격한 온도 변화를 보이는 hotspot들을 탐지하기 위한 열 감지 센서 수를 정하고, 센서의 놓여야 할 배치 장소를 결정하는 알고리즘을 제안한다. 열 감지 센서로는 동적으로 설계가 가능한 ring oscillator 센서 기술을 사용한다는 가정 하에, 센서의 사용 개수를 최소화함과 동시에 최적의 센서 배치 위치 찾는다. 기존의 연구의 단점은 센서가 감지하는 영역 범위를 적당한 크기의 정사각형으로 간주하였기에, 실제 원형의 관측 범위를 보이는 센서 감지 영역의 현실을 올바로 반영하지 못하였으며, 또한 잘 알려진 회로 분할(partition) 기법에 의존한 휴리스틱으로 최적의 결과를 보장하지는 못하였다. 이와는 달리 본 연구에서는 센서의 관측 범위를 원형으로 할 수도 있게 함과 동시에 최적의 해를 보장하는 센서 할당 및 배치 알고리즘을 제안한다. 구체적으로 본 제안 알고즘에서는 소위 “Candidate Coloring 기법”을 통해 센서가 놓여야 할 모든 후보 영역을 표시하며, “Candidate Filtering 기법”을 통해 불필요한 후보 영역들을 완전히 삭제하여 탐색 공간을 줄이게 되며 (해의 최적 해는 항상 유지 되도록 하면서), 마지막으로 Branch-and-Bound 알고리즘을 적용해 최적의 센서 할당 및 배치 결과를 찾아내었다.

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An Algorithm for Design of a Multiple Ring Network Using ROADM in WDM Mesh Networks (WDM Mesh 네트워크에서 ROADM을 이용한 멀티플-링 네트워크 설계 방안)

  • Kim, Eal-Lae;Lee, Sung-Kuen;Lim, Tae-Hyung;Lee, Myung-Moon;Park, Jin-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.11B
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    • pp.663-672
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    • 2007
  • This paper proposes an algorithm for design of a multiple ring network that can be applied to an arbitrary topology in the WDM optical transport networks. Especially, we suggest an integer linear program(ILP) formulation with the objective of minimizing the total cost of nodes based on the reconfigurable OADM(ROADM) architecture and propose a heuristic algorithm to reduce computational complexity of the exact problem formulation. To evaluate the performance and validity of this scheme, we applied it to an NSFnet topology assuming the dynamic or static traffic condition and compared it with a mesh methodology about capacity of connection requests and the total cost of the nodes.

Using Traffic Prediction Models for Providing Predictive Traveler Information : Reviews & Prospects (교통정보 제공을 위한 교통예측모형의 활용)

  • Ran, Bin;Choi, Kee-Choo
    • Journal of Korean Society of Transportation
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    • v.17 no.1
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    • pp.141-157
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    • 1999
  • This paper first reviews current practices of traveler information providing and provides some perspectives regarding the possible near term milestones in traveler information providing. Then, reviews of four types of prediction models: 1) dynamic traffic assignment (DTA) model; 2) statistical model; 3) simulation model; and 4) heuristic model are described in the sense that various prediction models are needed to support providing predictive traveler information in the near future. Next, the functional requirements and capabilities of the four types of prediction models are discussed and summarized along with some advantages and disadvantages of these models with reference to short-term travel time prediction. Furthermore, a comprehensive prediction procedure, which combines the four types of prediction models, is presented, together with the data requirements for each type of prediction model.

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Reinforcement Learning based Job Dispatching Model for Single Machine with Sequence Dependent Setup Time (순서 의존적 작업 준비시간을 갖는 단일기계 작업장을 위한 강화학습 기반 작업 배정 모형)

  • Jin-Sung Park;Jun-Woo Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.327-329
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    • 2023
  • 순서 의존적 준비시간을 갖는 단일기계 생산라인에서 주어진 작업들을 효율적으로 수행하기 위해서는 최대한 동일하거나 유사한 유형의 작업물들을 연속적으로 처리하여 다음 번 작업물의 처리를 시작하기 전에 발생하는 준비시간을 최소화하여야 한다. 따라서, 대기 중인 것들 중 기계에 투입할 작업물을 적절히 선택하는 것이 중요하며, 이를 위해 작업 배정 규칙과 같은 휴리스틱을 사용할 수도 있지만, 이러한 해법들은 일반적으로 다양한 상황을 동적으로 고려하지 못하는 한계점을 갖는다. 따라서, 본 논문에서는 상용 3D 시뮬레이션 소프트웨어인 FlexSim을 사용하여 모형을 구성한 다음, 강화학습을 적용하여 대기 중인 작업물 중 최적의 후보를 선택하기 위한 작업 배정 모형을 개발하고자 한다. 세부적으로는 강화학습의 상태 및 보상을 달리 설정하면서 학습된 모형의 성능을 비교하고자 한다. 실험 결과를 통해 적절한 시뮬레이션 모형 구성과 강화학습의 파라미터 변수들을 적절히 조합하여 적절한 작업 배정 모형의 개발이 가능하다는 점을 알 수 있었다.

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Ramp Activity Expert System for Scheduling and Co-ordination (공항의 계류장 관리 스케줄링 및 조정을 위한 전문가시스템)

  • Jo, Geun-Sik;Yang, Jong-Yoon
    • Journal of Advanced Navigation Technology
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    • v.2 no.1
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    • pp.61-67
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    • 1998
  • In this paper, we have described the Ramp Activity Coordination Expert System (RACES) which can solve aircraft parking problems. RACES includes a knowledge-based scheduling problem which assigns every daily arriving and departing flight to the gates and remote spots with the domain specific knowledge and heuristics acquired from human experts. RACES processes complex scheduling problem such as dynamic inter-relations among the characteristics of remote spots/gates and aircraft with various other constraints, for example, custome and ground handling factors at an airport. By user-driven modeling for end users and knowledge-driven near optimal scheduling acquired from human experts, RACES can produce parking schedules of aircraft in about 20 seconds for about 400 daily flights, whereas it normally takes about 4 to 5 hours by human experts. Scheduling results in the form of Gantt charts produced by the RACES are also accepted by the domain experts. RACES is also designed to deal with the partial adjustment of the schedule when unexpected events occur. After daily scheduling is completed, the messages for aircraft changes and delay messages are reflected and updated into the schedule according to the knowledge of the domain experts. By analyzing the knowledge model of the domain expert, the reactive scheduling steps are effectively represented as rules and the scenarios of the Graphic User Interfaces (GUI) are designed. Since the modification of the aircraft dispositions such as aircraft changes and cancellations of flights are reflected to the current schedule, the modification should be notified to RACES from the mainframe for the reactive scheduling. The adjustments of the schedule are made semi-automatically by RACES since there are many irregularities in dealing with the partial rescheduling.

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A Fair Scheduling of Heterogeneous Multi-Server Systems by Cumulative Extra Capacity Sharing (누적적 잉여용량 공유를 통한 이질적 다중 서버 시스템의 공정 스케줄링)

  • Park, Kyeong-Ho;Hwang, Ho-Young
    • The KIPS Transactions:PartA
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    • v.14A no.7
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    • pp.451-456
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    • 2007
  • In this paper, we regard computer systems as heterogeneous multi-server systems and propose a cumulative fair scheduling scheme that pursues long-term fairness. GPS(generalized processor sharing)-based scheduling algorithms, which are usually employed in single-server systems, distribute available capacity in an instantaneous manner. However, applying them to heterogeneous multi-server systems may cause unfairness, since they may not prevent the accumulation of scheduling delays and the extra capacities are distributed in an instantaneous manner. In our scheme, long-term fairness is pursued by proper distribution of extra capacities while guaranteeing reserved capacities. A reference capacity model to determine the ideal progresses of applications is derived from long-term observations, and the scheduler makes the applications gradually follow the ideal progresses while guaranteeing their reserved capacities. A heuristic scheduling algorithm is proposed and the scheme is examined by simulation.

Searching a Navigation Path to Avoid Danger Area for Safe Driving (안전운전을 위해 위험지역을 회피하는 내비게이션 경로탐색)

  • Lee, Yong-Hu;Kim, Sang-Woon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.8
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    • pp.171-179
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    • 2013
  • The primary function of navigation system is to provide route search and road guidance for safe driving for drivers. However, the existing route search system provides a simple service that looks up the shortest route using a safe driving DB without considering different road characteristics for the safety of the drivers. In order to maintain the safe driving, rather than searching the shortest path, a navigation system, in which the danger areas and/or the dangerous time zones have been considered, is required. Therefore, in this paper we propose a strategy of searching a navigation path to avoid danger areas for safe driving by using the A* algorithm. In the strategy, when evaluating the path-specific fitness of the navigation nodes, different heuristic weights were assigned to different types of risk areas. In particular, we considered three kinds of danger areas, such as accident-prone sections where accidents occur frequently, school zones, and intersection regions, as well as the time slots when the probability of danger is high. From computer simulation, the results demonstrate that the proposed scheme can provide the way to avoid danger areas on the route searching and confirm the possibility of providing the actual service.

Enhanced Methods of Path Finding Based on An Abstract Graph with Extension of Search Space (탐색 영역 확장 기법들을 활용한 추상 그래프 기반의 탐색 알고리즘 성능 개선)

  • Cho, Dae-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.1
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    • pp.157-162
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    • 2011
  • In this paper, we propose enhanced methods of path finding based on an abstract graph with extension of search space to improve the quality of path. The proposed methods that are called simple buffering method, velocity constrained method and distance constrained method are to extract buffering-cells for using search space with valid-cells. The simple buffering method is to extract adjacent cells of valid-cells as buffering-cells. velocity constrained method and distance constrained method are based on simple buffering method, these eliminate buffering-cells through each of threshold. In experiment, proposed methods can improve the quality of path. The proposed methods are applicable to develop various kinds of telematics application, such as path finding and logistics.

A Fusion of the Period Characterized and Hierarchical Bayesian Techniques for Efficient Cluster Analysis of Time Series Data (시계열자료의 효율적 군집분석을 위한 구간특징화와 계층적 베이지안 기법의 융합)

  • Jung, Young-Ae;Jeon, Jin-Ho
    • Journal of Digital Convergence
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    • v.13 no.7
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    • pp.169-175
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    • 2015
  • An effective way to understand the dynamic and time series that follows the passage of time, as valuation is to establish a model to analyze the phenomena of the system. Model of the decision process is efficient clustering information of the total mass of the time series data of the relevant population been collected in a particular number of sub-groups than to look at all a time to an understand of the overall data through each community-specific model determination. In this study, a sub-grouping of the group and the first of the two process model of each cluster by determining, in the following in sub-population characterized by a fusion with heuristic Bayesian clustering techniques proposed a process which can reduce calculation time and cost was confirmed by experiments using actual effectiveness valuation.

Optimal Supply Chain formation using Agent Negotiation in SET Model based Make-To-Order (최적 공급사슬 구성을 위한 에이전트 협상방법론 개발)

  • Kim Hyun-Soo;Cho Jae-Hyung;Choi Hyung-Rim;Hong Soon-Goo
    • Journal of Intelligence and Information Systems
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    • v.12 no.2
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    • pp.99-123
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    • 2006
  • In an effect to composite an optimal supply chain, this study has introduced an agent-based negotiation as a method to assign a lot of orders to a large number of participants. As a resources allocation mechanism to form a strategic cooperation based on information sharing between supply chain members(buyers, manufacturers, suppliers), this agent negotiation provides coordination functions allowing all participants to make a profit and accomplishing Pareto optimum solution from the viewpoint of a whole supply chain. A SET model-based scheduling takes into consideration both earliness production cost and tardiness production cost, along with a competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under the dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.

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