• Title/Summary/Keyword: flexible search algorithm

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Tabu Search Heuristics for Solving a Class of Clustering Problems (타부 탐색에 근거한 집락문제의 발견적 해법)

  • Jung, Joo-Sung;Yum, Bong-Jin
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.3
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    • pp.451-467
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    • 1997
  • Tabu search (TS) is a useful strategy that has been successfully applied to a number of complex combinatorial optimization problems. By guiding the search using flexible memory processes and accepting disimproved solutions at some iterations, TS helps alleviate the risk of being trapped at a local optimum. In this article, we propose TS-based heuristics for solving a class of clustering problems, and compare the relative performances of the TS-based heuristic and the simulated annealing (SA) algorithm. Computational experiments show that the TS-based heuristic with a long-term memory offers a higher possibility of finding a better solution, while the TS-based heuristic without a long-term memory performs better than the others in terms of the combined measure of solution quality and computing effort required.

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The Integration of FMS Process Planning and Scheduling Using an Asymmetric Multileveled Symbiotic Evolutionary Algorithm (비대칭형 다계층 공생 진화알고리듬을 이용한 FMS 공정계획과 일정계획의 통합)

  • Kim, Yeo Keun;Kim, Jae Yun;Shin, Kyoung Seok
    • Journal of Korean Institute of Industrial Engineers
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    • v.30 no.2
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    • pp.130-145
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    • 2004
  • This paper addresses the integrated problem of process planning and scheduling in FMS (Flexible Manufacturing System). The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called asymmetric multileveled symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. Efficient genetic representations and operator schemes are considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and existing evolutionary algorithms. The experimental results show that the proposed algorithm outperforms the compared algorithms.

Optimal Design of a Squeeze Film Damper Using an Enhanced Genetic Algorithm

  • Ahn, Young-Kong;Kim, Young-Chan;Yang, Bo-Suk
    • Journal of Mechanical Science and Technology
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    • v.17 no.12
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    • pp.1938-1948
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    • 2003
  • This paper represents that an enhanced genetic algorithm (EGA) is applied to optimal design of a squeeze film damper (SFD) to minimize the maximum transmitted load between the bearing and foundation in the operational speed range. A general genetic algorithm (GA) is well known as a useful global optimization technique for complex and nonlinear optimization problems. The EGA consists of the GA to optimize multi-modal functions and the simplex method to search intensively the candidate solutions by the GA for optimal solutions. The performance of the EGA with a benchmark function is compared to them by the IGA (Immune-Genetic Algorithm) and SQP (Sequential Quadratic Programming). The radius, length and radial clearance of the SFD are defined as the design parameters. The objective function is the minimization of a maximum transmitted load of a flexible rotor system with the nonlinear SFDs in the operating speed range. The effectiveness of the EGA for the optimal design of the SFD is discussed from a numerical example.

A Heterogeneous VRP to Minimize the Transportation Costs Using Genetic Algorithm (유전자 알고리듬을 이용한 운행비용 최소화 다용량 차량경로문제)

  • Ym, Mu-Kyun;Jeon, Geon-Wook
    • IE interfaces
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    • v.20 no.2
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    • pp.103-111
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    • 2007
  • A heterogeneous VRP which considers various capacities, fixed and variable costs was suggested in this study. The transportation cost for vehicle is composed of its fixed and variable costs incurred proportionately to the travel distance. The main objective is to minimize the total sum of transportation costs. A mathematical programming model was suggested for this purpose and it gives an optimal solution by using OPL-STUDIO (ILOG CPLEX). A genetic algorithm which considers improvement of an initial solution, new fitness function with weighted cost and distance rates, and flexible mutation rate for escaping local solution was also suggested. The suggested algorithm was compared with the results of a tabu search and sweeping method by Taillard and Lee, respectively. The suggested algorithm gives better solutions rather than existing algorithms.

A Combined Heuristic Algorithm for Preference-based Shortest Path Search (선호도 기반 최단경로 탐색을 위한 휴리스틱 융합 알고리즘)

  • Ok, Seung-Ho;Ahn, Jin-Ho;Kang, Sung-Ho;Moon, Byung-In
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.47 no.8
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    • pp.74-84
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    • 2010
  • In this paper, we propose a preference-based shortest path algorithm which is combined with Ant Colony Optimization (ACO) and A* heuristic algorithm. In recent years, with the development of ITS (Intelligent Transportation Systems), there has been a resurgence of interest in a shortest path search algorithm for use in car navigation systems. Most of the shortest path search algorithms such as Dijkstra and A* aim at finding the distance or time shortest paths. However, the shortest path is not always an optimum path for the drivers who prefer choosing a less short, but more reliable or flexible path. For this reason, we propose a preference-based shortest path search algorithm which uses the properties of the links of the map. The preferences of the links are specified by the user of the car navigation system. The proposed algorithm was implemented in C and experiments were performed upon the map that includes 64 nodes with 118 links. The experimental results show that the proposed algorithm is suitable to find preference-based shortest paths as well as distance shortest paths.

Segmentation Algorithm for Wafer ID using Active Multiple Templates Model

  • Ahn, In-Mo;Kang, Dong-Joong;Chung, Yoon-Tack
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.839-844
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    • 2003
  • This paper presents a method to segment wafer ID marks on poor quality images under uncontrolled lighting conditions of the semiconductor process. The active multiple templates matching method is suggested to search ID areas on wafers and segment them into meaningful regions and it would have been impossible to recognize characters using general OCR algorithms. This active template model is designed by applying a snake model that is used for active contour tracking. Active multiple template model searches character areas and segments them into single characters optimally, tracking each character that can vary in a flexible manner according to string configurations. Applying active multiple templates, the optimization of the snake energy is done using Greedy algorithm, to maximize its efficiency by automatically controlling each template gap. These vary according to the configuration of character string. Experimental results using wafer images from real FA environment are presented.

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Optimum Design of a Helicopter Tailrotor Driveshaft Using Flexible Matrix Composite (유연복합재를 이용한 헬리콥터 꼬리날개 구동축의 최적 설계)

  • Shin, Eung-Soo;Hong, Eul-Pyo;Lee, Kee-Nyeong;Kim, Ock-Hyun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.12
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    • pp.1914-1922
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    • 2004
  • This paper provides a comprehensive study of optimum design of a helicopter tailrotor driveshaft made of the flexible matrix composites (FMCs). Since the driveshaft transmits power while subjected to large bending deformation due to aerodynamic loadings, the FMCs can be ideal for enhancing the drivetrain performance by absorbing the lateral deformation without shaft segmentation. However, the increased lateral flexibility and high internal damping of the FMCs may induce whirling instability at supercritical operating conditions. Thus, the purpose of optimization in this paper is to find a set of tailored FMC parameters that compromise between the lateral flexibility and the whirling stability while satisfying several criteria such as torsional buckling safety and the maximum shaft temperature at steadystate conditions. At first, the drivetrain was modeled based on the finite element method and the classical laminate theory with complex modulus approach. Then, an objective function was defined as a combination of an allowable bending deformation and external damping and a genetic algorithm was applied to search for an optimum set with respect to ply angles and stack sequences. Results show that an optimum laminate consists of two groups of layers: (i) one has ply angles well below 45$^{\circ}$ and the other far above 45$^{\circ}$ and (ii) the number of layers with low ply angles is much bigger than that with high ply angles. It is also found that a thick FMC shaft is desirable for both lateral flexibility and whirling stability. The genetic algorithm was effective in converging to several local optimums, whose laminates exhibit similar patterns as mentioned above.

An Analysis on the Influential Factors to Set the Path Planning Algorithm for Unmanned Ground Vehicle in Combat Environment (전장환경에서 무인전투차량의 경로계획 알고리즘설정 영향요인 분석)

  • Baek, Jong-Sung;Lee, Choon-Joo
    • The Journal of Korea Robotics Society
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    • v.4 no.3
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    • pp.233-242
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    • 2009
  • This paper briefly reviews the path planning methods that are applicable to the autonomous mobile robots for the military. Two distinct path search algorithms, $A^*$ and $D^*$ that are most popular and flexible in public applications, among those reviewed are coded and analyzed in terms of combat environment assessment factors called METT+TC for the area of operations. The results imply that it is important to consider the characteristics of defense acquisition process and the specific requirements of defense operation so that the successful technology development of the Robot products is directly linked to the defense procurement of Robot products.

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Development of a Stress Path Search Model of Evolutionary Structural Optimization Using TIN (점진적 최적화 기법에서 불규칙 삼각망을 이용한 평면구조의 응력경로 탐색모델의 개발)

  • Kim, Nam-Su;Lee, Jeong-Jae;Yoon, Seong-Soo;Kim, Yoon-Soon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.46 no.4
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    • pp.65-71
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    • 2004
  • Stress Path Search Model of Evolutionary Structural Successive Optimization (SPSMESO) using Triangular Irregular Network(TIN) was developed for improving over burden at initial design of ESO and strict stress direction of strut-and-tie model and truss model. TIN was applied for discretizing structures in flexible stress path and segments of TIN was analyzed as one-dimensional line element for calculating stress. Finally, stress path was searched using ESO algorithm. SPSMESO was efficient to express the direction of stress for 2D structure and time saving.

DYNAMIC ROUTE PLANNING BY Q-LEARNING -Cellular Automation Based Simulator and Control

  • Sano, Masaki;Jung, Si
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.24.2-24
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    • 2001
  • In this paper, the authors present a row dynamic route planning by Q-learning. The proposed algorithm is executed in a cellular automation based traffic simulator, which is also newly created. In Vehicle Information and Communication System(VICS), which is an active field of Intelligent Transport System(ITS), information of traffic congestion is sent to each vehicle at real time. However, a centralized navigation system is not realistic to guide millions of vehicles in a megalopolis. Autonomous distributed systems should be more flexible and scalable, and also have a chance to focus on each vehicles demand. In such systems, each vehicle can search an own optimal route. We employ Q-learning of the reinforcement learning method to search an optimal or sub-optimal route, in which route drivers can avoid traffic congestions. We find some applications of the reinforcement learning in the "static" environment, but there are ...

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