• 제목/요약/키워드: Input constraints

검색결과 324건 처리시간 0.027초

A Study on Selection of Cross-Docking Center based on Existing Logistics Network (기존 물류 네트워크 기반에서 크로스 - 도킹 거점선정에 관한 연구)

  • Lee, In-Chul;Lee, Myeong-Ho;Kim, Nae-Heon
    • IE interfaces
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    • 제19권1호
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    • pp.26-33
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    • 2006
  • Many Firms consider the application of a cross-docking system to reduce inventory and lead-time. However, most studies mainly concentrate on the design of a cross-docking system. This study presents the method that selects the cross-docking center under the existing logistics network. Describing the operation environment to apply the cross-docking system, the selection criteria of the cross-docking center, and the main constraints of transportation planning under the environment of multi-level logistics network, we define the selection problem of the cross-docking center applied to a logistics field. We also define the simulation model that can analyze variously the cross-docking volume and develop the selection methodology of the cross-docking center. The simulation model presents the algorithm and influence factors of the cross-docking system, the decision criteria of the system, policy parameter, and input data. In addition, this study analyzes the effect of increasing the number of simultaneous receiving and shipping docks, and the efficiency of the overnight transportation and cross-docking by evaluating each scenario after simulating the scenarios with the practical data of the logistics field.

Preserving Mobile QoS during Handover via Predictive Scheduling in IMT Advanced System (IMT Advanced 시스템에서 예측 스케줄링을 통한 핸드오버시 모바일 QoS 보존 방법)

  • Poudyal, Neeraj;Lee, Byung-Seub
    • Journal of Advanced Navigation Technology
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    • 제14권6호
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    • pp.865-873
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    • 2010
  • In this paper, a novel schedulability criteria is developed to provide handover calls with Quality of Service (QoS) guarantees in terms of both minimum available bandwidth, maximum tolerated packet delay, and other additive QoS constraints as required by the real-time mobile traffic. This requires prediction of the handover time using mobility trends on the mobile station, which is used as input to this work. After the handover time and the QoS are negotiated, the destination base station makes attempts to give priority to handover calls over new calls, and pre-reserves resources that will have more chance of being available during the actual handover.

Test Set Generation for Pairwise Testing Using Genetic Algorithms

  • Sabharwal, Sangeeta;Aggarwal, Manuj
    • Journal of Information Processing Systems
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    • 제13권5호
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    • pp.1089-1102
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    • 2017
  • In software systems, it has been observed that a fault is often caused by an interaction between a small number of input parameters. Even for moderately sized software systems, exhaustive testing is practically impossible to achieve. This is either due to time or cost constraints. Combinatorial (t-way) testing provides a technique to select a subset of exhaustive test cases covering all of the t-way interactions, without much of a loss to the fault detection capability. In this paper, an approach is proposed to generate 2-way (pairwise) test sets using genetic algorithms. The performance of the algorithm is improved by creating an initial solution using the overlap coefficient (a similarity matrix). Two mutation strategies have also been modified to improve their efficiency. Furthermore, the mutation operator is improved by using a combination of three mutation strategies. A comparative survey of the techniques to generate t-way test sets using genetic algorithms was also conducted. It has been shown experimentally that the proposed approach generates faster results by achieving higher percentage coverage in a fewer number of generations. Additionally, the size of the mixed covering arrays was reduced in one of the six benchmark problems examined.

Model Predictive Control System Design with Real Number Coding Genetic Algorithm (실수코딩 유전알고리즘을 이용한 모델 예측 제어 시스템 설계)

  • Bang, Hyun-Jin;Park, Jong-Chon;Hong, Jin-Man;Lee, Hong-Gi
    • Journal of the Korean Institute of Intelligent Systems
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    • 제16권5호
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    • pp.562-567
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    • 2006
  • Model Predictive Control(MPC) system uses the current input which minimizes the difference between the desired output and the estimated output in the receding horizon scheme. In many cases (for example, system with constraints or nonlinear system), however, it is not easy to find the optimal solution to the above problem. In this paper, we show that real number coding genetic algorithm can be used to solve the optimal problem for MPC effectively. Also, we show by simulation that the real coding algorithm is mote natural and advantageous than the digital coding one.

A Minimum Cost Model for Merging Production Process with Final Product Quality Constraints (최종품질제약하의 병합공정을 갖는 생산라인의 최소비용 모형)

  • 이경록;박명규
    • Journal of the Korea Safety Management & Science
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    • 제5권4호
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    • pp.169-185
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    • 2003
  • Recently many researchers contributed to the understanding of Quality Control System, but the use of economics in the design of quality assurance system is limited in treatment of the relationship between the average incoming quality level (or average process quality level) of the incoming lot and the average outgoing quality level of this lot. In this study, a traditional concept of sampling inspection plan for the quality assurance system is extended to a consideration of economic aspects in total production system by representing and analyzing the effects between proceeding and succeeding production process including inspection process. This approach recognizes that the decision at each manufacturing process (or assembly process), is to be determined not only by the cost and the average outgoing quality level of that process, but also by the input parameters of the cost and the incoming quality to the succeeding process. By analyzing the effects of the average incoming and outgoing quality, manufacturing or assembly process quality level and sampling inspection plan on the production system, mathematical models and solution technique to minimize the total production cost for a general product manufacturing system with specified average outgoing quality limit are suggested.

A Joint Allocation Algorithm of Computing and Communication Resources Based on Reinforcement Learning in MEC System

  • Liu, Qinghua;Li, Qingping
    • Journal of Information Processing Systems
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    • 제17권4호
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    • pp.721-736
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    • 2021
  • For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

Simulation Study for Feature Identification of Dynamic Medical Image Reconstruction Technique Based on Singular Value Decomposition (특이값분해 기반 동적의료영상 재구성기법의 특징 파악을 위한 시뮬레이션 연구)

  • Kim, Do-Hui;Jung, YoungJin
    • Journal of radiological science and technology
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    • 제42권2호
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    • pp.119-130
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    • 2019
  • Positron emission tomography (PET) is widely used imaging modality for effective and accurate functional testing and medical diagnosis using radioactive isotopes. However, PET has difficulties in acquiring images with high image quality due to constraints such as the amount of radioactive isotopes injected into the patient, the detection time, the characteristics of the detector, and the patient's motion. In order to overcome this problem, we have succeeded to improve the image quality by using the dynamic image reconstruction method based on singular value decomposition. However, there is still some question about the characteristics of the proposed technique. In this study, the characteristics of reconstruction method based on singular value decomposition was estimated over computational simulation. As a result, we confirmed that the singular value decomposition based reconstruction technique distinguishes the images well when the signal - to - noise ratio of the input image is more than 20 decibels and the feature vector angle is more than 60 degrees. In addition, the proposed methode to estimate the characteristics of reconstruction technique can be applied to other spatio-temporal feature based dynamic image reconstruction techniques. The deduced conclusion of this study can be useful guideline to apply medical image into SVD based dynamic image reconstruction technique to improve the accuracy of medical diagnosis.

Cycle-accurate NPU Simulator and Performance Evaluation According to Data Access Strategies (Cycle-accurate NPU 시뮬레이터 및 데이터 접근 방식에 따른 NPU 성능평가)

  • Kwon, Guyun;Park, Sangwoo;Suh, Taeweon
    • IEMEK Journal of Embedded Systems and Applications
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    • 제17권4호
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    • pp.217-228
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    • 2022
  • Currently, there are increasing demands for applying deep neural networks (DNNs) in the embedded domain such as classification and object detection. The DNN processing in embedded domain often requires custom hardware such as NPU for acceleration due to the constraints in power, performance, and area. Processing DNN models requires a large amount of data, and its seamless transfer to NPU is crucial for performance. In this paper, we developed a cycle-accurate NPU simulator to evaluate diverse NPU microarchitectures. In addition, we propose a novel technique for reducing the number of memory accesses when processing convolutional layers in convolutional neural networks (CNNs) on the NPU. The main idea is to reuse data with memory interleaving, which recycles the overlapping data between previous and current input windows. Data memory interleaving makes it possible to quickly read consecutive data in unaligned locations. We implemented the proposed technique to the cycle-accurate NPU simulator and measured the performance with LeNet-5, VGGNet-16, and ResNet-50. The experiment shows up to 2.08x speedup in processing one convolutional layer, compared to the baseline.

Visualization of Vector Fields from Density Data Using Moving Least Squares Based on Monte Carlo Method (몬테카를로 방법 기반의 이동최소제곱을 이용한 밀도 데이터의 벡터장 시각화)

  • Jong-Hyun Kim
    • Journal of the Korea Computer Graphics Society
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    • 제30권2호
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    • pp.1-9
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    • 2024
  • In this paper, we propose a new method to visualize different vector field patterns from density data. We use moving least squares (MLS), which is used in physics-based simulations and geometric processing. However, typical MLS does not take into account the nature of density, as it is interpolated to a higher order through vector-based constraints. In this paper, we design an algorithm that incorporates Monte Carlo-based weights into the MLS to efficiently account for the density characteristics implicit in the input data, allowing the algorithm to represent different forms of white noise. As a result, we experimentally demonstrate detailed vector fields that are difficult to represent using existing techniques such as naive MLS and divergence-constrained MLS.

Resource allocation for Millimeter Wave mMIMO-NOMA System with IRS

  • Bing Ning;Shuang Li;Xinli Wu;Wanming Hao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권7호
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    • pp.2047-2066
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    • 2024
  • In order to improve the coverage and achieve massive spectrum access, non-orthogonal multiple access (NOMA) technology is applied in millimeter wave massive multiple-input multiple-output (mMIMO) communication network. However, the power assumption of active sensors greatly limits its wide applications. Recently, Intelligent Reconfigurable Surface (IRS) technology has received wide attention due to its ability to reduce power consumption and achieve passive transmission. In this paper, spectral efficiency maximum problem in the millimeter wave mMIMO-NOMA system with IRS is considered. The sparse RF chain antenna structure is designed at the base station based on continuous phase modulation. Furthermore, a joint optimization problem for power allocation, power splitting, analog precoding and IRS reconfigurable matrices are constructed, which aim to achieve the maximum spectral efficiency of the system under the constraints of user's quality of service, minimum energy harvesting and total transmit power. A three-stage iterative algorithm is proposed to solve the above mentioned non-convex optimization problems. We obtain the local optimal solution by fixing some optimization parameters firstly, then introduce the relaxation variables to realize the global optimal solution. Simulation results show that the spectral efficiency of the proposed scheme is superior compared to the conventional system with phase shifter modulation. It is also demonstrated that IRS can effectively assist mmWave communication and improve the system spectral efficiency.