• Title/Summary/Keyword: Weighted sum

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Online Non-preemptive Deadline Scheduling for Weighted Jobs (가중치 작업들의 온라인 비선점 마감시한 스케줄링)

  • Kim Jae-Hoon;Chang Jung-Hwan
    • Journal of KIISE:Computer Systems and Theory
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    • v.32 no.2
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    • pp.68-74
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    • 2005
  • In deadline scheduling, jobs have deadlines by which they are completed. The scheduling algorithm determines which jobs are executed at each time. Then only the completed jobs contribute to the throughput or gain of the algorithm. The jobs have arbitrary weights and the gain of the algorithm is given as the sum of weights of the completed jobs. The goal of the scheduling algorithm is to maximize its gain. In this paper, we consider online non-preemptive scheduling, where jobs arrive online and the scheduling algorithm has no information about jobs arriving ahead. Also the jobs cannot be preempted or rejected while they are executed. For this problem, we obtain lower bounds for any online algorithms and also we propose an optimal online algorithm meeting the lower bounds.

Spatial Distribution Analysis of Metallic Elements in Dustfall using GIS (GIS를 이용한 강하분진 중 금속원소의 공간분포분석)

  • 윤훈주;김동술
    • Journal of Korean Society for Atmospheric Environment
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    • v.13 no.6
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    • pp.463-474
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    • 1997
  • Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

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An Analysis on the Climate Change Exposure of Fisheries and Fish Species in the Southern Sea under the RCP Scenarios: Focused on Sea Temperature Variation (RCP 시나리오에 따른 남해안 어업 및 어종의 기후변화 노출 분석 : 수온 변동을 대상으로)

  • Kim, Bong-Tae;Lee, Joon-Soo;Suh, Young-Sang
    • The Journal of Fisheries Business Administration
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    • v.47 no.4
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    • pp.31-44
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    • 2016
  • The purpose of this study is to analyze the climate change exposure of fisheries and fish species in the southern sea of Korea under the RCP climate change scenarios. The extent of exposure was calculated through weighted sum of the sea temperature forecasted by National Institute of Fisheries Science, and the weight were obtained from the time-space distribution of each fisheries or species, based on the micro-data for the fishing information reported by each fisherman. Results show that all the exposed sea temperature of RCP8.5 is higher than that of RCP4.5 in year 2100 as well as in near 2030, therefore it is thought to be very important to reduce the GHG emission even in the short term. The extent of exposure was analyzed to be comparatively high especially in the fisheries such as anchovy drag nets and species like cod, anchovy and squid. Meanwhile the method of this study is considered to be excellent to obtain the accurate extent of exposure under RCP scenarios, and therefore it is applicable on assessing the vulnerability of climate change in fisheries.

Multi-objective Optimization of an Injection Mold Cooling Circuit for Uniform Cooling (사출금형의 균일 냉각을 위한 냉각회로의 다중목적함수 최적설계)

  • Park, Chang-Hyun;Park, Jung-Min;Choi, Jae-Hyuk;Rhee, Byung-Ohk;Choi, Dong-Hoon
    • Transactions of the Korean Society of Automotive Engineers
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    • v.20 no.1
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    • pp.124-130
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    • 2012
  • An injection mold cooling circuit for an automotive front bumper was optimally designed in order to simultaneously minimize the average of the standard deviations of the temperature and the difference in mean temperatures of the upper and lower molds for uniform cooling. The temperature distribution for a specified design was evaluated by Moldflow Insight 2010, a commercial injection molding analysis tool. For efficient design, PIAnO (Process Integration, Automation and Optimization), a commercial PIDO tool, was used to integrate and automate injection molding analysis procedure. The weighted-sum method was used to handle the multi-objective optimization problem and PQRSM, a function-based sequential approximate optimizer equipped in PIAnO, to handle numerically noisy responses with respect to the variation of design variables. The optimal average of the standard deviations and difference in mean temperatures were found to be reduced by 9.2% and 56.52%, respectively, compared to the initial ones.

Signal Optimization Model Considering Traffic Flows in General Traffic Networks (일반적인 네트워크에서의 신호최적화모형 개발 연구)

  • 신언교;김영찬
    • Journal of Korean Society of Transportation
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    • v.17 no.2
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    • pp.127-135
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    • 1999
  • Most existing progression bandwidth models maximize the single or multi weighted sum of bandwidths in the both directions to improve traffic mobility on an arterial, but they cannot be applied to general networks. Even though a few models formulating a looped network problem cannot be applied to networks have not loops. Also they have some defects in optimizing phase sequences. Therefore, the objective of this study is to develope a mathematical formulation of the synchronization problem for a general traffic network. The goal is achieved successfully by introducing the signal phasing for each movement and expanding the mixed integer linear programming of MAXBAND. The experiments indicate that the proposed model can formulate the general traffic network problem mere efficiently than any other model. In conclusion, this model may optimize signal time to smooth progression in the general networks.

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Efficient Heuristics for Flowshop Scheduling for Minimizing the Makespan and Total Flowtime of Jobs

  • Hirakawa, Yasuhiro;Ishigaki, Aya
    • Industrial Engineering and Management Systems
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    • v.10 no.2
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    • pp.134-139
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    • 2011
  • The problem of scheduling in permutation flowshops has been extensively investigated by many researchers. Recently, attempts are being made to consider more than one objective simultaneously and develop algorithms to obtain a set of Pareto-optimal solutions. Varadharajan et al. (2005) presented a multi-objective simulated-annealing algorithm (MOSA) for the problem of permutation-flowshop scheduling with the objectives of minimizing the makespan and the total flowtime of jobs. The MOSA uses two initial sequences obtained using heuristics, and seeks to obtain non-dominated solutions through the implementation of a probability function, which probabilistically selects the objective of minimizing either the makespan or the total flowtime of jobs. In this paper, the same problem of heuristically developing non-dominated sequences is considered. We propose an effective heuristics based on simulated annealing (SA), in which the weighted sum of the makespan and the total flowtime is used. The essences of the heuristics are in selecting the initial sequence, setting the weight and generating a solution in the search process. Using a benchmark problem provided by Taillard (1993), which was used in the MOSA, these conditions are extracted in a large-scale experiment. The non-dominated sets obtained from the existing algorithms and the proposed heuristics are compared. It was found that the proposed heuristics drastically improved the performance of finding the non-dominated frontier.

Intelligent Allocation of Transporting Resources in Logistics using Genetic Algorithm (유전자 알고리즘을 이용한 물류에서의 지능적 운송 자원 할당)

  • Kim, Ju-Won;Cha, Yeong-Pil;Jeong, Mu-Yeong
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.05a
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    • pp.23-26
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    • 2004
  • Recently, most of countries in the world are investing huge amount of capital for the infrastructure of logistics and trying to gain dominating position in logistics. To play the role of important hub in logistics, an efficient, flexible, and fault-tolerant transportation process should be developed. Minimization of transportation cost and timely deliveries in the unpredictable environment are a few of the important issues in logistics. This study suggests a way of transporting goods to destinations at the minimal cost and with the minimal delay by optimally allocating transporting resources. Various attributes in transportation such as due date, priority etc. are also considered. Appropriate transporting resources for each work item is selected by calculating the weighted sum of the cost factor and the delay factor assuming that initial sequences of work items are given. A policy to reallocate transporting resources is also suggested when work items or transporting resources are added or deleted because of accidents or disturbances. This policy provides adaptability to the allocation methodology which enables the system to cope with changing environment by controlling various attributes in transportation. Genetic algorithm is used for this approach.

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Adaptive Noise Reduction of Speech using Wavelet Transform (웨이브렛 변환을 이용한 음성의 적응 잡음 제거)

  • Im Hyung-kyu;Kim Cheol-su
    • Journal of the Korea Computer Industry Society
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    • v.6 no.2
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    • pp.271-278
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    • 2005
  • This paper proposed a new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in level 3 approximation and weighted level 1 detail. Level 3 approximation coefficients represent the voiced sound with low frequency and level 1 detail coefficients represent the unvoiced sound with high frequency. After reducing noise by soft thresholding with the proposed time adapted threshold, there are still residual noises in silent interval. To reduce residual noises in silent interval, a detection algorithm of silent interval is proposed. From simulation results, it is demonstrated that the proposed algorithm improves SNR and MSE performance more than Wavelet transform and Wavelet packet transform does.

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Moving Object Detection Robust to Sudden illumination Change using Modified Texture Information (개선된 텍스쳐 정보를 이용한 갑작스러운 조명 변화에 강인한 이동 물체 탐지)

  • O, Yoe-Han;Chang, Hyung-Jin;Kim, Soo-Wan;Choi, Jin-Young
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.268-269
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    • 2008
  • Moving object detection is a fundamental technique in visual surveillance. Robust technique to enhance performance of moving object detection is required for several bad conditions in real external circumtance. In case of sudden illumination change in outdoor condition, many objects are determined as moving object though they are not really moving, but just their illumination changes. This makes the detection result untrustworthy. In this paper, robust moving object detection to sudden illumination change using gaussian mixture background model and new texture information using background from the weighted sum of recent images is proposed.

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Metaheuristics of the Rail Crane Scheduling Problem (철송 크레인 일정계획 문제에 대한 메타 휴리스틱)

  • Kim, Kwang-Tae;Kim, Kyung-Min
    • IE interfaces
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    • v.24 no.4
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    • pp.281-294
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    • 2011
  • This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.