• Title/Summary/Keyword: Heuristic Rule

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Efficient Lambda Logic Based Optimisation Procedure to Solve the Large Scale Generator Constrained Economic Dispatch Problem

  • Adhinarayanan, T.;Sydulu, M.
    • Journal of Electrical Engineering and Technology
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    • v.4 no.3
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    • pp.301-309
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    • 2009
  • A simple and efficient Lambda logic (${\lambda}-logic$) based algorithm is proposed for the solution of the generator constrained economic dispatch problem when the generating units having prohibited zones. The proposed method solves the economic dispatch (ED) problem that takes into account ramprate limits, transmission losses and prohibited operating zones in the power system operation. The proposed method uses a simple heuristic rule based on average power of prohibited operating zones which produces the feasibility of solution for the restricted operating units. The effectiveness of the algorithm is tested on five different test systems and the performance compared with other relevant methods reported in the literature. In all the cases, the proposed algorithm performs better than the previous existing algorithms with a less computational burden.

Comparative Evaluation of Multipurpose Reservoir Operating Rules Using Multicriterion Decision Analysis Techniques

  • Ko, Seok-Ku;Lee, Kwang-Man;Ko, luk-Hwan
    • Korean Journal of Hydrosciences
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    • v.4
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    • pp.65-79
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    • 1993
  • Selection of the best operating rule among a set of alternatives for a multipurpose reservoir system operation requires to evaluate many minor criteria in addition to the major objectives assessed to the system. These problems are sufficiently complex and difficult that they are beyond heuristic decision rules and experiences in case several noncommensurable multiple criteria are included in the evaluation. With the assistance of multicriterion decision analysis techniques, it is possible to select the best one among various alternatives by systematically comparing and ranking the alternatives with respect to the criteria of choice. Evaluation criteria for multipurpose reservoir system operating rules were identified and defined, and the multicriterion decision analysis techniques were applied to evaluate the four existing operating rules of the Chungju multipurpose project according to the identified nine multiple criteria. The application results show that the methodology is very efficient to select the best operation alternative among a finite number of operating rules with many evaluation criteria for a large-scale reservoir system operation.

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A Study on the Development of an APS System for Job Shops (Job Shop을 위한 APS 시스템 개발에 관한 연구)

  • Ju, Cheol-Min
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.05a
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    • pp.64-66
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    • 2004
  • In general, the algorithms for production scheduling are developed with special objective under the special restrictions. Therefore, there is no common algorithm for APS system applied to various kind of production circumstances. The scheduling algorithm for APS system has to solve any problem that comes from any conditions of product kind, process, resource, machine, special rule for scheduling, and so forth. In addition, the algorithm finds solutions quickly because the need for real time based reschedule comes out often. In this paper, I am going to develop a scheduling algorithm using heuristic and genetic algorithm for APS system applied to various kind of production circumstances quickly and flexibly. The developed APS system with the algorithm will be introduced in this paper, also.

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Performance Improvement of Multi-Start in uDEAS Using Guided Random Bit Generation (유도된 이진난수 생성법을 이용한 uDEAS의 Multi-start 성능 개선)

  • Kim, Eun-Su;Kim, Man-Seak;Kim, Jong-Wook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.4
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    • pp.840-848
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    • 2009
  • This paper proposes a new multi-start scheme that generates guided random bits in selecting initial search points for global optimization with univariate dynamic encoding algorithm for searches (uDEAS). The proposed method counts the number of 1 in each bit position from all the previously generated initial search matrices and, based on this information, generates 0 in proportion with the probability of selecting 1. This rule is simple and effective for improving diversity of initial search points. The performance improvement of the proposed multi-start is validated through implementation in uDEAS and function optimization experiments.

A Hybrid Method for classifying User's Asking Points (하이브리드 방법의 사용자 질의 의도 분류)

  • Harksoo Kim;An, Young Hun;Jungyun Seo
    • Journal of KIISE:Software and Applications
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    • v.30 no.1_2
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    • pp.51-57
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    • 2003
  • For QA systems to return correct answer phrases, it is very important that they correctly and stably analyze users' intention. To satisfy this need, we propose a question type classifier (i.e. asking point identifier) for practical QA systems. The classifier uses a hybrid method that combines a statistical method with a rule-based method according to some heuristic rules. Owing to the hybrid method, the classifier can reduce the time to manually construct rules, yield high precision rate and guarantee robustness. In the experiment, we accomplished 80% accuracy of the question type classification.

A Branch-and-Bound Algorithm for U-line Line Balancing (U라인 라인밸런싱을 위한 분지한계법)

  • 김여근;김재윤;김동묵;송원섭
    • Journal of the Korean Operations Research and Management Science Society
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    • v.23 no.2
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    • pp.83-101
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    • 1998
  • Assembly U-lines are increasingly accepted in industry, especially just-in-time production systems, for the efficient utilization of workforce. In this paper, we present an integer programming formulation and a branch-and-bound method for balancing the U-line with the objective of minimizing the number of workstations with a fixed cycle time. In the mathematical model, we provide the method that can reduce the number of variables and constraints. The proposed branch-and-bound method searches the optimal solution based on a depth-first-search. To efficiently search for the optimal solutions to the problems, an assignment rule is used in the method. Bounding strategies and dominance rules are also utilized. Some problems require a large amount of computation time to find the optimal solutions. For this reason. some heuristic fathoming rules are also proposed. Extensive experiments with test-bed problems in the literature are carried out to show the performance of the proposed method. The computational results show that our method is promising in solution quality.

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Sequential Paging under Delay Bound for Next Generation Mobile Systems (차세대 이동통신에서의 지연을 고려한 순차적 페이징)

  • Lee, Chae-Yong;Ku, Sang-Hoon
    • Korean Management Science Review
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    • v.23 no.3
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    • pp.13-25
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    • 2006
  • To reduce the signaling tost of paging in mobile communication, sequential paging schemes are proposed by partitioning a location area into several paging areas such that each area is paged sequentially. Necessary conditions for the optimal partition of cells with delay bound are examined by considering the mobiles location probability at each cell. The Optimal Cell Partitioning (OCP) is proposed based on the necessary conditions and the fathoming rule which trims off the unnecessary solution space and expedite the search process. Two Heuristics, BSG and BNC are also presented to further increase the computational efficiency in real-world paging scheme for the next generation mobile systems. The effectiveness of the 1)reposed paging schemes is illustrated with computational results. The Heuristic BSG that performs the search in the most promising solution group outperforms the best existing procedure with the 6-69% gain in paging cost in problems with 100 cells.

Power Distribution System Planning with Demand Uncertainty Consideration

  • Wattanasophon, Sirichai;Eua-arporn, Bundhit
    • Journal of Electrical Engineering and Technology
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    • v.3 no.1
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    • pp.20-28
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    • 2008
  • This paper proposes a method for solving distribution system planning problems taking into account demand uncertainty and geographical information. The proposed method can automatically select appropriate location and size of a substation, routing of feeders, and appropriate sizes of conductors while satisfying constraints, e.g. voltage drop and thermal limit. The demand uncertainty representing load growth is modeled by fuzzy numbers. Feeder routing is determined with consideration of existing infrastructure, e.g. streets and canals. The method integrates planner's experience and process optimization to achieve an appropriate practical solution. The proposed method has been tested with an actual distribution system, from which the results indicate that it can provide satisfactory plans.

A Job Loading Procedure as a Kernel Part of FMS Integrated Operating System and Its Evaluation

  • Katayama, Hiroshi
    • Management Science and Financial Engineering
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    • v.2 no.1
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    • pp.1-18
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    • 1996
  • FMS operating system consists of several subsystems in general. i.e. tool grouping subsystem. tool/job assignment subsystem. job dispatching subsystem, and papers dealing with each subsystem were published by many researchers [1], [4], [6], [8], [9], [10], [11], [12], [13], [14], [15], [16]. This paper mainly discusses about tool/job assignment subsystem as a job loading procedure. that occupies the kernel position of overall FMS operating system. Its performance is evaluated through simulation experiments of an integrated operating system under a typical FMS hardware configuration implemented in many machining factories, which is composed of the proposed procedure as well as a job dispatching procedure including several heuristic dispatching rules in terms of rule-base.

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A Variable Selection Procedure for K-Means Clustering

  • Kim, Sung-Soo
    • The Korean Journal of Applied Statistics
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    • v.25 no.3
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    • pp.471-483
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    • 2012
  • One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".