• 제목/요약/키워드: near optimal solution

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A QoS Multicast Routing Optimization Algorithm Based on Genetic Algorithm

  • Sun Baolin;Li Layuan
    • Journal of Communications and Networks
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    • v.8 no.1
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    • pp.116-122
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    • 2006
  • Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

A Study on the Distribution of Injected Urea into the Exhaust Pipe in a SCR System (선택적 환원촉매(SCR)장치에서 배기관내에 분사된 환원제 분포에 관한 연구)

  • Choi, J.H.;Lee, Y.C.;LEE, S.W.;Cho, Y.S.;LEE, S.H.;Oh, S.K.;Dong, Y.H.
    • Journal of Power System Engineering
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    • v.14 no.1
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    • pp.16-21
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    • 2010
  • This research focused on the spray and distribution characteristics of urea solution by applying flow visualization techniques and did durability and driver test on injectors as well. The spray characteristics of urea solution was observed by CCD camera. Also, the distribution characteristics of urea solution was evaluated quantitatively as well by using 3D laser scanner equipment. It was considered that it was reasonable to use the injector for gasoline engine in order to inject the urea. The best distribution chart result was observed near 45cm distance difference between catalyst and urea spray injector. As a result of trapped urea distribution chart analysis, optimal pressure and volumetric flow rates of air and urea were derived in order to improve the distribution of Urea. This information may contribute to provide fundamental data in the future.

Simulated Annealing for Two-Agent Scheduling Problem with Exponential Job-Dependent Position-Based Learning Effects (작업별 위치기반 지수학습 효과를 갖는 2-에이전트 스케줄링 문제를 위한 시뮬레이티드 어닐링)

  • Choi, Jin Young
    • Journal of the Korea Society for Simulation
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    • v.24 no.4
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    • pp.77-88
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    • 2015
  • In this paper, we consider a two-agent single-machine scheduling problem with exponential job-dependent position-based learning effects. The objective is to minimize the total weighted completion time of one agent with the restriction that the makespan of the other agent cannot exceed an upper bound. First, we propose a branch-and-bound algorithm by developing some dominance /feasibility properties and a lower bound to find an optimal solution. Second, we design an efficient simulated annealing (SA) algorithm to search a near optimal solution by considering six different SAs to generate initial solutions. We show the performance superiority of the suggested SA using a numerical experiment. Specifically, we verify that there is no significant difference in the performance of %errors between different considered SAs using the paired t-test. Furthermore, we testify that random generation method is better than the others for agent A, whereas the initial solution method for agent B did not affect the performance of %errors.

Cold Acoustic Tests for the Elucidation of the Gap of Optimal Damping Capacity of Baffled Injectors in Liquid Rocket Combustors (로켓연소기에서 분사기형 배플의 간극에 따른 감쇠특성 파악을 위한 상온음향시험)

  • Kim, Hong-Jip;Lee, Kwang-Jin;Choi, Hwan-Seok
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.35 no.8
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    • pp.720-725
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    • 2007
  • Cold acoustic tests have been performed to elucidate the effect of baffle gaps on the optimal damping characteristics in a liquid rocket combustor where coaxial injectors are installed. For several axial baffle lengths, an optimal acoustic damping capacitance has been achieved in a certain gap range. Cold acoustic tests for simulating fluid viscosity by changing the pressure in a model chamber have been done to study the main mechanism of optimal damping. Experimental data have shown that the optimal gap for high damping capacity exists mainly due to the viscosity near the gap of baffles. Therefore, axial baffle length can be reduced by using the optimal baffle gap, providing a possible solution of thermal cooling problems. Also, these optimum characteristics can be some guidelines for manufacturing and assembling injectors in full-scaled rocket combustors.

Study on Vehicle Routing Problem with Minimum Delivery Completion Time (특송소화물 배송완료시간 최소화를 위한 차량경로문제 연구)

  • Lee, Sang-Heon
    • Journal of Korean Society of Transportation
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    • v.22 no.7 s.78
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    • pp.107-117
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    • 2004
  • The growing demand for customer-response, made-to-order manufacturing and satisfactory delivery are stimulating the importance of commercial fleet management problem. Moreover, the rapid transformation to the customer-oriented multi-frequency, relatively small fleet, such as home delivery and Perishable goods, requiring prompt delivery and advanced real-time operation of vehicle fleets. In this paper we consider the vehicle routing problem(VRP) to minimize delivery completion time which is equal to the time that last customer wait for the vehicle in fleet operation. The mathematical formulation is different from those for the classical VRP which is minimizing cost/distance/time by running vehicles in manager's point of view. The key aspect of this model is not considering the return time from the last customer to depot in every vehicle path. Thereby, the vehicle dispatcher can afford to dynamically respond to customer demand and vehicle availability. The customer's position concerned with minimizing waiting time that may be applied for the delivery of product required freshness or delivery time. Extensive experiments are carried out to compare the performance of minimizing delivery completion time by using the ILOG Solver which has the advantage of solving quickly an interim solution very near an optimal solution. The experimental results show that the suggested model can easily find near optimal solution in a reasonable computational time under the various combination of customers and vehicles.

Distributed Genetic Algorithm using aster/slave model for the TSP (TSP를 위한 마스터/슬레이브 모델을 이용한 분산유전 알고리즘)

  • Jung-Sook Kim
    • Journal of the Korea Computer Industry Society
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    • v.3 no.2
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    • pp.185-190
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    • 2002
  • As the TSP(Traveling Salesman Problem) belongs to the class of NP-complete problems, various techniques are required for finding optimum or near optimum solution to the TSP. This paper designs a distributed genetic algorithm in order to reduce the execution time and obtain more near optimal using multi-slave model for the TSP. Especially, distributed genetic algorithms with multiple populations are difficult to configure because they are controlled by many parameters that affect their efficiency and accuracy. Among other things, one must decide the number and the size of the populations (demes), the rate of migration, the frequency of migrations, and the destination of the migrants. In this paper, I develop random dynamic migration rate that controls the size and the frequency of migrations. In addition to this, I design new migration policy that selects the destination of the migrants among the slaves

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A Study on Determining Job Sequence of Job Shop by Sampling Method (샘플링 기법(技法)에 의한 잡. 샵(Job Shop)의 작업순서(作業順序) 결정(決定))

  • Gang, Seong-Su;No, In-Gyu
    • Journal of Korean Society for Quality Management
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    • v.17 no.1
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    • pp.69-81
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    • 1989
  • This study is concerned with a job sequencing method using the concept of sampling technique in the case of Job Shop. This is the follow study of Kang and Ro (1988) which examined the possibility of application of sampling technique to determine the Job Sequence in the case of Flow Shop. Not only it is very difficult, but also it takes too much time to develop the appropriate job schedules that satisfy the complex work conditions. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions or assumptions. The application areas of these algorithms are also very narrow, so it is very hard to find the appropriate algorithm which satisfy the complex work conditions. In this case it is very desirable to develop a simple job sequencing method which can select the optimal job sequence or near optimal job sequence with a little effort. This study is to examine the effect of sampling job sequencing which can select the good job of 0.01%~5% upper good group. The result shows that there is the sets of 0.05%~23% job sequence group which has the same amount of performance measure with the optimal job sequence in the case of experiment of N/M/G/$F_{max}$. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with consuming a small amount of time. The results of ANOVA show that the only one factor, number of machines is the significant factor for determining the job sequence at ${\alpha}=0.01$. It takes about 10 minutes to compare the number of 10,000 samples of job sequence by personal computer and it is proved that the selection rate of the same job sequence with optimal job sequence is 23.0%, 3.9% and 0.065% in the case of 2 machines, 3 machines and 4 machines, respectively. The area of application can readily be extended to the other work condition.

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An Adaptive Approximation Method for the Interconnecting Highways Problem in Geographic Information Systems (지리정보시스템에서 고속도로 연결 문제의 가변적 근사기법)

  • Kim, Joon-Mo;Hwang, Byung-Yeon
    • Journal of Korea Spatial Information System Society
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    • v.7 no.2 s.14
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    • pp.57-66
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    • 2005
  • The Interconnecting Highways problem is an abstract of many practical Layout Design problems in the areas of VLSI design, the optical and wired network design, and the planning for the road constructions. For the road constructions, the shortest-length road layouts that interconnect existing positions will provide many more economic benefits than others. That is, finding new road layouts to interconnect existing roads and cities over a wide area is an important issue. This paper addresses an approximation scheme that finds near optimal road layouts for the Interconnecting Highways problem which is NP-hard. As long as computational resources are provided, the near optimality can be acquired asymptotically. This implies that the result of the scheme can be regarded as the optimal solution for the problem in practice. While other approximation schemes can be made for the problem, this proposed scheme provides a big merit that the algorithm designed by this scheme fits well to given problem instances.

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Reinforcement Learning-based Dynamic Weapon Assignment to Multi-Caliber Long-Range Artillery Attacks (다종 장사정포 공격에 대한 강화학습 기반의 동적 무기할당)

  • Hyeonho Kim;Jung Hun Kim;Joohoe Kong;Ji Hoon Kyung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.45 no.4
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    • pp.42-52
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    • 2022
  • North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel's "Iron Dome", designed to protect against North Korea's arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea's multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

The Allocation of Inspection Efforts Using a Knowledge Based System

  • Kang, Kyong-sik;Stylianides, Christodoulos;La, Seung-houn
    • Journal of Korean Society for Quality Management
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    • v.18 no.2
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    • pp.18-24
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    • 1990
  • The location of inspection stations is a significant component of production systems. In this paper, a prototype expert system is designed for deciding the optimal location of inspection stations. The production system is defined as a single channel of n serial operation stations. The potential inspection station can be located after any of the operation stations. Nonconforming units are generated from a compound binomial distribution with known parameters at any given operation station. Traditionally Dynamic programming, Zero-one integer programming, or Non-linear programming techniques are used to solve this problem. However a problem with these techniques is that the computation time becomes prohibitively large when t be number of potential inspection stations are fifteen or more. An expert system has the potential to solve this problem using a rule-based system to determine the near optimal location of inspection stations. This prototype expert system is divided into a static database, a dynamic database and a knowledge base. Based on defined production systems, the sophisticated rules are generated by the simulator as a part of the knowledge base. A generate-and-test inference mechanism is utilized to search the solution space by applying appropriate symbolic and quantitative rules based on input data. The goal of the system is to determine the location of inspection stations while minimizing total cost.

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