• Title/Summary/Keyword: completion time algorithm

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Optimal Scheduling of Multi-product Batch Process for Common Intermediate Storage Policy; A Model for Batch Process Automation (다품종용 회분식 공정에서의 중간 저장 탱크 공유를 위한 최적 생산계획 ; 회분식 조업의 자동화 모델)

  • 정재학;이인범;양대륙;장근수
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.303-308
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    • 1992
  • In this study, we propose a shared storage system which is more efficient policy than MIS(Mixed Intermediate Storage) policy for relatively rare storage system and can be called CIS(Common Intermediate Storage) policy. Using this strategy, we develop a new completion time algorithm and apply it to two kinds of optimal or near optimal scheduling method; combinatorial search and simulated annealing method. We also extend this strategy to other storage policy, for example MIS policy, with PLC(Programmable Logic Controller) logic and on/off action of electronic valves. It thus can be accepted as a basic form of FMS(Flexible Manufacturing System) for operating various storage policies. Finally we suggest the interlocking block to compansate for the shortcoming of CIS policy, i.e, complication of operation and safety, resulting in a basic batch process automation mode.

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A Branch-and-Bound Algorithm on the Fire Sequencing for Planned Artillery Operations (포병부대 사격순서결정을 위한 분지한계 알고리즘 연구)

  • Yoon, Sang-Hum;Hwang, Won-Shik;Juhn, Jae-Ho;Lee, Ik-Sun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.33 no.3
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    • pp.154-161
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    • 2010
  • This paper considers the simultaneously firing model for the artillery operations. The objective of this paper is to find the optimal fire sequence minimizing the final completion time of the firing missions of multiple artillery units for multiple targets. In the problem analysis, we derive several solution properties to reduce the solution space. Moreover, two lower bounds of objective are derived and tested along with the derived properties within a branch-and-bound scheme. Two efficient heuristic algorithms are also developed. The overall performances of the proposed branch-and-bound and heuristic algorithms are evaluated through various numerical experiments.

Friction Coefficient, Torque Estimation, Smooth Shift Control Law for an Automatic Power Transmission

  • Jeong, Heon-Sul;Lee, Kyo-Ill
    • Journal of Mechanical Science and Technology
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    • v.14 no.5
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    • pp.508-517
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    • 2000
  • For shift quality improvement, torque sensors are currently too expensive to be used on production vehicles. To achieve smooth acceleration shift, the reference trajectory of the clutch slip speed for accomplishing the shift process within a designated shift completion time and its relationship with the clutch actuating torque were suggested by Jeong and Lee (1999). In order to facilitate the proposed algorithm, nonlinear estimators for necessary information such as the axle shaft torque, clutch friction and turbine torque were designed using only speed sensors. Accounting for the modeling error, a control law for this indirect smooth shift was proposed based on the above mentioned suggestions. Simulation results of the proposed estimators and shift controller were presented and further considerations for practical applications are discussed.

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An Offloading Strategy for Multi-User Energy Consumption Optimization in Multi-MEC Scene

  • Li, Zhi;Zhu, Qi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.10
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    • pp.4025-4041
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    • 2020
  • Mobile edge computing (MEC) is capable of providing services to smart devices nearby through radio access networks and thus improving service experience of users. In this paper, an offloading strategy for the joint optimization of computing and communication resources in multi-user and multi-MEC overlapping scene was proposed. In addition, under the condition that wireless transmission resources and MEC computing resources were limited and task completion delay was within the maximum tolerance time, the optimization problem of minimizing energy consumption of all users was created, which was then further divided into two subproblems, i.e. offloading strategy and resource allocation. These two subproblems were then solved by the game theory and Lagrangian function to obtain the optimal task offloading strategy and resource allocation plan, and the Nash equilibrium of user offloading strategy games and convex optimization of resource allocation were proved. The simulation results showed that the proposed algorithm could effectively reduce the energy consumption of users.

Comparison of Collision Avoidance Algorithm for a Mobile Robot using a Simulation (시뮬레이션을 이용한 이동 로봇의 충돌회피 알고리즘 비교)

  • Kim, Kwang-Jin;Ko, Nak-Yong;Park, Se-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.1
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    • pp.187-194
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    • 2012
  • This paper compares two collision avoidance algorithms using a simulator. The collision avoidance is vital for autonomous navigation of a mobile robot. Artificial potential field method and elastic force method are major approaches for the collision avoidance. The two algorithms are compared in the respect of the time for motion completion and the length of the motion path. The simulator is developed based on IPC(Inter Process Communication) and a differential drive mobile robot is used for the comparison.

Heuristic Aspects of the Branch and Bound Procedure for a Job Scheduling Problem (작업 스케쥴링 문제 해결을 위한 Branch & Bound 해법의 비교분석)

  • Koh, Seok-Joo;Lee, Chae-Y.
    • Journal of Korean Institute of Industrial Engineers
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    • v.18 no.2
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    • pp.141-147
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    • 1992
  • This article evaluates the efficiency of three branch-and-bound heuristics for a job scheduling problem that minimizes the sum of absolute deviations of completion times from a common due date. To improve the performance of the branch-and-bound procedure, Algorithm SA is presented for the initial feasible schedule and three heuristics : breadth-first, depth-first and best-first search are investigated depending on the candidate selection procedure. For the three heuristics the CPU time, memory space, and the number of nodes generated are computed and tested with nine small examples (6 ${\leq}$ n ${\leq}$ 4). Medium sized random problems (10 ${\leq}$ n ${\leq}$ 30) are also generated and examined. The computational results are compared and discussed for the three heuristics.

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Determining Checkpoint Intervals of Non-Preemptive Rate Monotonic Scheduling Using Probabilistic Optimization (확률 최적화를 이용한 비선점형 Rate Monotonic 스케줄링의 체크포인트 구간 결정)

  • Kwak, Seong-Woo;Yang, Jung-Min
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.1
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    • pp.120-127
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    • 2011
  • Checkpointing is one of common methods of realizing fault-tolerance for real-time systems. This paper presents a scheme to determine checkpoint intervals using probabilistic optimization. The considered real-time systems comprises multiple tasks in which transient faults can happen with a Poisson distribution. Also, multi-tasks are scheduled by the non-preemptive Rate Monotonic (RM) algorithm. In this paper, we present an optimization problem where the probability of task completion is described by checkpoint numbers. The solution to this problem is the optimal set of checkpoint numbers and intervals that maximize the probability. The probability computation includes schedulability test for the non-preemptive RM algorithm with respect to given numbers of checkpoint re-execution. A case study is given to show the applicability of the proposed scheme.

Fountain Code-based Hybrid P2P Storage Cloud (파운틴 코드 기반의 하이브리드 P2P 스토리지 클라우드)

  • Park, Gi Seok;Song, Hwangjun
    • KIISE Transactions on Computing Practices
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    • v.21 no.1
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    • pp.58-63
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    • 2015
  • In this work, we present a novel fountain code-based hybrid P2P storage system that combines cloud storage with P2P storage. The proposed hybrid storage system minimizes data transmission time while guaranteeing high data retrieval and data privacy. In order to guarantee data privacy and storage efficiency, the user transmits encoded data after performing fountain code-based encoding. Also, the proposed algorithm guarantees the user's data retrieval by storing the data while considering each peer's survival probability. The simulation results show that the proposed algorithm enables fast completion of the upload transmission while satisfying the required data retrieval and supporting the privacy of user data under the system parameters.

Object Detection and Localization on Map using Multiple Camera and Lidar Point Cloud

  • Pansipansi, Leonardo John;Jang, Minseok;Lee, Yonsik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.422-424
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    • 2021
  • In this paper, it leads the approach of fusing multiple RGB cameras for visual objects recognition based on deep learning with convolution neural network and 3D Light Detection and Ranging (LiDAR) to observe the environment and match into a 3D world in estimating the distance and position in a form of point cloud map. The goal of perception in multiple cameras are to extract the crucial static and dynamic objects around the autonomous vehicle, especially the blind spot which assists the AV to navigate according to the goal. Numerous cameras with object detection might tend slow-going the computer process in real-time. The computer vision convolution neural network algorithm to use for eradicating this problem use must suitable also to the capacity of the hardware. The localization of classified detected objects comes from the bases of a 3D point cloud environment. But first, the LiDAR point cloud data undergo parsing, and the used algorithm is based on the 3D Euclidean clustering method which gives an accurate on localizing the objects. We evaluated the method using our dataset that comes from VLP-16 and multiple cameras and the results show the completion of the method and multi-sensor fusion strategy.

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Many-objective joint optimization for dependency-aware task offloading and service caching in mobile edge computing

  • Xiangyu Shi;Zhixia Zhang;Zhihua Cui;Xingjuan Cai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.5
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    • pp.1238-1259
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    • 2024
  • Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constraints, and multiple users on policy formulation. To remedy this deficiency, this paper proposes a many-objective joint optimization dependency-aware task offloading and service caching model (MaJDTOSC). MaJDTOSC considers the impact of dependencies between subtasks on the joint optimization problem of task offloading and service caching in multi-user, resource-constrained MEC scenarios, and takes the task completion time, energy consumption, subtask hit rate, load variability, and storage resource utilization as optimization objectives. Meanwhile, in order to better solve MaJDTOSC, a many-objective evolutionary algorithm TSMSNSGAIII based on a three-stage mating selection strategy is proposed. Simulation results show that TSMSNSGAIII exhibits an excellent and stable performance in solving MaJDTOSC with different number of users setting and can converge faster. Therefore, it is believed that TSMSNSGAIII can provide appropriate sub-task offloading and service caching strategies in multi-user and resource-constrained MEC scenarios, which can greatly improve the system offloading efficiency and enhance the user experience.