• Title/Summary/Keyword: TABU Algorithm

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Tabu Search Algorithm for designing broadband converged access networks (광대역 융합 엑세스 가입자 망 설계를 위한 타부서치 알고리즘 개발)

  • Yun, Hyeon-Jeong;Lee, Yeong-Ho;Kim, Yeong-Jin;Jo, Eun-Seong;Lee, Sun-Seok;Park, No-Ik
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.11a
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    • pp.277-280
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    • 2006
  • This paper deals with a heuristic algorithm for solving a broadband converged access networks (BCAN) design problem. The problem is to minimize the total cost of switches and cables while satisfying demand and QoS constraints. We propose a Tabu Search (TS) algorithm for finding a good feasible solution within a reasonable time limit.

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A Tabu Search Heuristic Algorithm for Hierarchical Location Allocation Problem (광대역 융합 가입자 망 설계를 위한 타부서치 알고리즘 개발)

  • Park, Gi-Gyeong;Lee, Yeong-Ho;Kim, Yeong-Uk
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2008.10a
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    • pp.131-135
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    • 2008
  • In this paper, we deal with a hierarchical location-allocation problem in designing the broadband convergence networks (BcN). The objective is to minimize the total cost of switch and cable while satisfying the quality of service (QoS). We formulate the problem as an integer programming model and develop the Tabu Search (TS) heuristic algorithm to find a good feasible solution within a reasonable time limit. Initial solution is obtained by using the tree structure. Three neighborhood generation mechanisms are used by local search heuristic: insertion, switch up, and switch down. In order to demonstrate the effectiveness of the proposed algorithm, we generate lower bounds from nonlinear QoS relaxation problem. We present promising computational results of the proposed solution procedures.

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Study on Hybrid Search Method Using Neural Network and Simulated Annealing Algorithm for Apparel Pattern Layout Design (뉴럴 네트워크와 시뮬레이티드 어닐링법을 하이브리드 탐색 형식으로 이용한 어패럴 패턴 자동배치 프로그램에 관한 연구)

  • Jang, Seung Ho
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.24 no.1
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    • pp.63-68
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    • 2015
  • Pattern layout design is very important to the automation of apparel industry. Until now, the genetic algorithm and Tabu search method have been applied to layout design automation. With the genetic algorithm and Tabu search method, the obtained values are not always consistent depending on the initial conditions, number of iterations, and scheduling. In addition, the selection of various parameters for these methods is not easy. This paper presents a hybrid search method that uses a neural network and simulated annealing to solve these problems. The layout of pattern elements was optimized to verify the potential application of the suggested method to apparel pattern layout design.

Optimal Design of Fluid Mount Using Artificial Life Algorithm (인공생명을 이용한 유체마운트의 최적화)

  • 안영공;송진대;양보석
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.11a
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    • pp.427-432
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    • 2001
  • This paper shows the optimum design of the fluid engine mount. The design has been modified by trial and error because there is many design parameters that can be varied in order to obtain resonant and notch frequencies, and notch depth. It seems to be a great application for optimal design for the mount. Many combinations of parameters are possible to give us the desired resonant and notch frequencies, but the question is which combination provides the lowest resonant peak and notch depth\ulcorner In this study, the enhanced artificial life algorithm is applied to get the desired notch frequency of a fluid mount and minimize transmissibility at the notch frequency. The present hybrid algorithm is the synthesis of an artificial life algorithm with the random tabu (R-tabu) search method. The hybrid algorithm has some advantages, which is not only faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. The results show that the performance of a conventional engine mount can be improved significantly compared with the optimized mount.

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DEVELOPMENT OF A TABU SEARCH HEURISTIC FOR SOLVING MULTI-OBJECTIVE COMBINATORIAL PROBLEMS WITH APPLICATIONS TO CONSTRUCTING DISCRETE OPTIMAL DESIGNS

  • JOO SUNG JUNG;BONG JIN YUM
    • Management Science and Financial Engineering
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    • v.3 no.1
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    • pp.75-88
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    • 1997
  • Tabu search (TS) has been successfully applied for solving many complex combinatorial optimization problems in the areas of operations research and production control. However, TS is for single-objective problems in its present form. In this article, a TS-based heuristic is developed to determine Pareto-efficient solutions to a multi-objective combinatorial optimization problem. The developed algorithm is then applied to the discrete optimal design problem in statistics to demonstrate its usefulness.

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Optimal Routing and Uncertainty Processing using Geographical Information for e-Logistics Chain Execution

  • Kim, Jin Suk;Ryu, Keun Ho
    • Management Science and Financial Engineering
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    • v.10 no.2
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    • pp.1-28
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    • 2004
  • The integrated supply chain of business partners for e-Commerce in cyber space is defined as Logistics Chain if the cooperative activities are logistics-related. Logistics Chain could be managed effectively and efficiently by cooperative technologies of logistics chain execution. In this paper, we propose a routing and scheduling algorithm based on the Tabu search by adding geographical information into existing constraint for pick-up and delivery process to minimize service time and cost in logistics chain. And, we also consider an uncertainty processing for the tracing of moving object to control pick-up and delivery vehicles based on GPS/GIS/ITS. Uncertainty processing is required to minimize amount of telecommunication and database on vehicles tracing. Finally, we describe the Logistics Chain Execution (LCE) system to perform plan and control activities for postal logistics chain. To evaluate practical effects of the routing and scheduling system, we perform a pretest for the performance of the tabu search algorithm. And then we compare our result with the result of the pick-up and delivery routing plan generated manually by postmen.

A New Optimization Model for Designing Broadband Convergence Network Access Networks

  • Lee Young-Ho;Jung Jin-Mo;Kim Young-Jin;Lee Sun-Suk;Park No-Ik;Kang Kuk-Chang
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1616-1640
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    • 2006
  • In this paper, we deal with a network optimization problem arising from the deployment of Ethernet-based BcN access network. BcN convergence services require that access networks satisfy QoS measures. BcN services have two types of traffics: stream traffic and elastic traffic. Stream traffic uses blocking probability as a QoS measure, while elastic traffic uses delay factor as a QoS measure. Incorporating the QoS requirements, we formulate the problem as a nonlinear mixed-integer programming model. The proposed model seeks to find a minimum cost dimensioning solution, while satisfying the QoS requirement. We propose tabu search heuristic algorithms for solving the problem, and simulate tabu result. We demonstrate the computational efficacy of the proposed algorithm by solving a network design problem.

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Unit Commitment Using Parallel Genetic Algorithms and Parallel Tabu Search (병렬 유전알고리즘과 병렬 타부탐색법을 이용한 발전기 기동정지계획)

  • Cho, Deok-Hwan;Kang, Hyun-Tae;Kwon, Jung-Uk;Kim, Hyung-Su;Hwang, Gi-Hyun;Park, June-Ho
    • Proceedings of the KIEE Conference
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    • 2001.07a
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    • pp.327-329
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    • 2001
  • This paper presents the application of Parallel genetic algorithm and parallel tabu search to search an optimal solution of a unit commitment problem. The proposed method previously searches the solution globally using the parallel genetic algorithm, and then searches the solution locally using tabu search which has the good local search characteristic to reduce the computation time. This method combines the benefit of both method, and thus improves the performance. To show the usefulness of the proposed method, we simulated for 10 units system. Numerical results show the improvements of cost and computation time compared to previous obtained results.

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The Optimal Controller Design of Buck-Boost Converter by using Adaptive Tabu Search Algorithm Based on State-Space Averaging Model

  • Pakdeeto, Jakkrit;Chanpittayagit, Rangsan;Areerak, Kongpan;Areerak, Kongpol
    • Journal of Electrical Engineering and Technology
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    • v.12 no.3
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    • pp.1146-1155
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    • 2017
  • Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.