• 제목/요약/키워드: global optimality

검색결과 44건 처리시간 0.025초

Optimal Opportunistic Spectrum Access with Unknown and Heterogeneous Channel Dynamics in Cognitive Radio Networks

  • Zhang, Yuli;Xu, Yuhua;Wu, Qihui;Anpalagan, Alagan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권8호
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    • pp.2675-2690
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    • 2014
  • We study the problem of optimal opportunistic spectrum access with unknown and heterogeneous channel dynamics in cognitive radio networks. There is neither statistic information about the licensed channels nor information exchange among secondary users in the respective systems. We formulate the problem of maximizing network throughput. To achieve the desired optimization, we propose a win-shift lose-stay algorithm based only on rewards. The key point of the algorithm is to make secondary users tend to shift to another channel after receiving rewards from the current channel. The optimality and the convergence of the proposed algorithm are proved. The simulation results show that for both heterogeneous and homogenous systems the proposed win-shift lose-stay algorithm has better performance in terms of throughput and fairness than an existing algorithm.

유전 알고리즘을 활용한 무인기의 다중 임무 계획 최적화 (Multi-mission Scheduling Optimization of UAV Using Genetic Algorithm)

  • 박지훈;민찬오;이대우;장우혁
    • 한국항공운항학회지
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    • 제26권2호
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    • pp.54-60
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    • 2018
  • This paper contains the multi-mission scheduling optimization of UAV within a given operating time. Mission scheduling optimization problem is one of combinatorial optimization, and it has been shown to be NP-hard(non-deterministic polynomial-time hardness). In this problem, as the size of the problem increases, the computation time increases dramatically. So, we applied the genetic algorithm to this problem. For the application, we set the mission scenario, objective function, and constraints, and then, performed simulation with MATLAB. After 1000 case simulation, we evaluate the optimality and computing time in comparison with global optimum from MILP(Mixed Integer Linear Programming).

Robust and Optimal Attitude Control Law Design for Spacecraft with Inertia Uncertainties

  • Park, Yon-Mook;Tahk, Min-Jea
    • International Journal of Aeronautical and Space Sciences
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    • 제3권2호
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    • pp.1-12
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    • 2002
  • This paper considers the robust and optimal three-axis attitude stabilization of rigid spacecraft with inertia uncertainties. The attitude motion of rigid spacecraft described in terms of either the Cayley-Rodrigues parameters or the Modified Rodrigues parameters is considered. A class of robust nonlinear control laws with relaxed feedback gain structures is proposed for attitude stabilization of rigid spacecraft with inertia uncertainties. Global asymptotic stability of the proposed control laws is shown by using the LaSalle Invariance Principle. The optimality properties of the proposed control laws are also investigated by using the Hamilton-Jacobi theory. A numerical example is given to illustrate the theoretical results presented in this paper.

Multi-station Fixture Layout Design Using Simulated Annealing

  • Kim, Pansoo;Seun, Ji Ung
    • Management Science and Financial Engineering
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    • 제10권2호
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    • pp.73-87
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    • 2004
  • Automotive and aircraft assembly process rely on fixtures to support and coordinate parts and subassemblies. Fixture layout in multi-station panel assemblies has a direct dimensional effect on final products and thus presents a quality problem. This paper describes a methodology for fixture layout design in multi -station assembly processes. An optimal fixture layout improves the robustness of a fixture system against environmental noises, reduces product variability, and eventually leads to manufacturing cost reduction. One of the difficulties raised by multi-station fixture layout design is the overwhelmingly large number of design alternatives. This makes it difficult to find a global optimality and, if an inefficient algorithm is used, may require prohibitive computing time. In this paper, simulated annealing is adopted and appropriate parameters are selected to find good fixture layouts. A four-station assembly process for a sport utility vehicle (SUV) side frame is used throughout the paper to illustrate the efficiency and effectiveness of this methodology.

Optimal reinforcement design of structures under the buckling load using the homogenization design method

  • Min, Seungjae;Kikuchi, Noboru
    • Structural Engineering and Mechanics
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    • 제5권5호
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    • pp.565-576
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    • 1997
  • The material-based homogenization design method generates arbitrary topologies of initial structural design as well as reinforcement structural design by controlling the amount of material available. However, if a small volume constraint is specified in the design of Lightweight structures, thin and slender structures are usually obtained. For these structures stability becomes one of the most important requirements. Thus, to prevent overall buckling (that is, to increase stability), the objective of the design is to maximize the buckling load of a structure. In this paper, the buckling analysis is restricted to the linear buckling behavior of a structure. The global stability requirement is defined as a stiffness constraint, and determined by solving the eigenvalue problem. The optimality conditions to update the design variables are derived based on the sequential convex approximation method and the dual method. Illustrated examples are presented to validate the feasibility of this method in the design of structures.

방사상 배전계통의 커패시터 설치를 위한 카오스 탐색알고리즘 (Capacitor Placement in Radial Distribution Systems Using Chaotic Search Algorithm)

  • 이상봉;김규호;유석구
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 하계학술대회 논문집 A
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    • pp.124-126
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    • 2002
  • The general capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. In this paper, the method employing the chaos search algorithm is proposed to solve optimal capacitor placement problem with reducing computational effort and enhancing optimality of the solution. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 9 buses and 69 buses system to illustrate the effectiveness of the proposed method.

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RRT와 SPP 경로 평활화를 이용한 자동주행 로봇의 경로 계획 및 장애물 회피 알고리즘 (Path Planning and Obstacle Avoidance Algorithm of an Autonomous Traveling Robot Using the RRT and the SPP Path Smoothing)

  • 박영상;이영삼
    • 제어로봇시스템학회논문지
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    • 제22권3호
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    • pp.217-225
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    • 2016
  • In this paper, we propose an improved path planning method and obstacle avoidance algorithm for two-wheel mobile robots, which can be effectively applied in an environment where obstacles can be represented by circles. Firstly, we briefly introduce the rapidly exploring random tree (RRT) and single polar polynomial (SPP) algorithm. Secondly, we present additional two methods for applying our proposed method. Thirdly, we propose a global path planning, smoothing and obstacle avoidance method that combines the RRT and SPP algorithms. Finally, we present a simulation using our proposed method and check the feasibility. This shows that proposed method is better than existing methods in terms of the optimality of the trajectory and the satisfaction of the kinematic constraints.

여유자유도 로봇에 있어서 성능지수 제한궤적을 이용한 부작업의 성능에 관한 연구 (A Study on the Subtask Performance Using Measure Constraint Locus for a Redundant Robot)

  • 최병욱;원종화;정명진
    • 전자공학회논문지B
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    • 제28B권10호
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    • pp.761-770
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    • 1991
  • This paper suggests a measure constraint locus for characterization of the performance of a subtask for a redundant robot. The measure constraint locus are the loci of points satisfying the necessary constraint for optimality of measure in the joint configuration space. To uniquely obtain an inverse kinematic solution, one must consider both measure constraint locus and self-motion manifolds which are set of homogeneous solutions. Using measure constraint locus for maniqulability measure, the invertible workspace without singularities and the topological property of the configuration space for linding equilibrium configurations are analyzed. We discuss some limitations based on the topological arguments of measure constraint locus, of the inverse kinematic algorithm for a cyclic task. And the inverse kinematic algorithm using global maxima on self-motion manifolds is proposed and its property is studied.

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혼합 정수 선형 계획법을 이용한 수송 계획 모델 설계 (Design of Mixed Integer Linear Programming Model for Transportation Planning)

  • 박용국;이민구;정경권;원영진
    • 전자공학회논문지
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    • 제53권11호
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    • pp.166-174
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    • 2016
  • 본 논문에서는 스포츠 이벤트에서 선수단 수송 계획을 위한 혼합 정수 선형 계획법 모델을 제안하였다. 선수단 수송 계획은 선수단을 다수의 숙소에서 경기장까지 최소의 비용과 빠른 시간 계획을 찾는 것이다. 운행 회수를 의사결정 변수로 하고, 전체 수송비용은 최소가 되어야 하는 목적함수가 된다. 제안한 방법은 혼합 정수 선형 계획법을 이용하여 전역 최적점을 찾을 수 있는 장점이 있다. 제안한 방식의 유용성을 확인하기 위해서 시뮬레이션을 수행하고 스포츠 이벤트 관리 서비스 플랫폼(SEMSP)에서 수송 계획을 구축하였다.

Path coordinator by the modified genetic algorithm

  • Chung, C.H.;Lee, K.S.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1939-1943
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    • 1991
  • Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the shortest collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Neural Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

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