• 한국시뮬레이션학회:학술대회논문집
• /
• 한국시뮬레이션학회 1999년도 추계학술대회 논문집
• /
• pp.75-80
• /
• 1999

This paper presents a new method to find a optimal solution for stochastic system. This method uses Genetic Algorithm(GA) and simulation. GA is used to search for new alternative and simulation is used to evaluate alternative. The stochastic system has one or more random variables as inputs. Random inputs lead to random outputs. Since the outputs are random, they can be considered only as estimates of the true characteristics of they system. These estimates could greatly differ from the corresponding real characteristics for the system. We need multiple replications to get reliable information on the system. And we have to analyze output data to get a optimal solution. It requires too much computation to be practical. We address the problem of reducing computation. The procedure on this paper use GA character, an iterative process, to reduce the number of replications. The same chromosomes could exit in post and present generation. Computation can be reduced by using the information of the same chromosomes which exist in post and present current generation.

• 한국시뮬레이션학회논문지
• /
• 제13권1호
• /
• pp.11-23
• /
• 2004

The decomposition of a structuring element for a morphological operation reduces the amount of the computation required for executing the operation. In this paper, we present a new technique for the decomposition of convex structuring elements for morphological operations. We formulated the linear constraints for the decomposition of a convex polygon in discrete space, then the constraints are applied to the decomposition of a convex structuring element. Also, a cost function is introduced to represent the optimal criteria for decomposition. We use linear integer programming technique to find the combination of basis structuring elements which minimizes the amount of the computation required for executing the morphological operation. Formulating different cost functions for different implementation methods and computer architectures, we can determine the optimal decompositions which guarantee the minimal amounts of computation on different computing environment.

• 정보처리학회논문지A
• /
• 제12A권1호
• /
• pp.79-86
• /
• 2005

이 논문에서는 계산적으로나 수명적으로 코드를 최적화 하기 위해 절제된 코드 모션 알고리즘을 제안한다. 제한한 알고리즘은 BCM과 LCM 알고리즘을 확장한 SpCM 알고리즘이다. SpCM 알고리즘에서 BCM 알고리즘은 계산적으로 최적의 코드 모션을 수행하며, LCM 알고리즘은 레지스터 압박을 감소시킨다. 일반적으로, 코트 모션 알고리즘은 계산의 최적화와 레지스터 압박에 관련된 실행시간 최적화를 실행한다. 이 논문에서는 계산 비용과 레지스터 압박에 코드의 크기를 고려하는 부분을 추가하였다. 코드의 계산적 최적화와 수명적 최적화에 이어 코드의 크기를 고려하는 SpCM 알고리즘에 의해 코드 모션의 최적화 결과를 얻을 수 있다. 이 논문에서 제안한 알고리즘은 모든 불필요한 코드 모션을 억제시키기 때문에 계산적으로나 수명적으로 최적인 알고리즘이라 할 수 있다.

• ETRI Journal
• /
• 제32권4호
• /
• pp.622-625
• /
• 2010

In this letter, we assess the scalability of a path computation flooding (PCF) approach to compute optimal end-to-end inter-domain paths in a path computation element-based multi-domain network. PCF yields a drastically reduced network blocking probability compared to a blind per-domain path computation but introduces significant network control overhead and path computation complexity. In view of this, we introduce and compare an alternative low overhead PCF (LoPCF) solution. From the obtained results, LoPCF leads to similar blocking probabilities to PCF while exhibiting around 50% path computation complexity and network control overhead reduction.

• Journal of Information Processing Systems
• /
• 제14권2호
• /
• pp.499-509
• /
• 2018

Recently, hybrid transactional memory (HyTM) has gained much interest from researchers because it combines the advantages of hardware transactional memory (HTM) and software transactional memory (STM). To provide the concurrency control of transactions, the existing HyTM-based studies use a bloom filter. However, they fail to overcome the typical false positive errors of a bloom filter. Though the existing studies use a global lock, the efficiency of global lock-based memory allocation is significantly low in multi-core environment. In this paper, we propose an efficient hybrid transactional memory scheme using near-optimal retry computation and sophisticated memory management in order to efficiently process transactions in multi-core environment. First, we propose a near-optimal retry computation algorithm that provides an efficient HTM configuration using machine learning algorithms, according to the characteristic of a given workload. Second, we provide an efficient concurrency control for transactions in different environments by using a sophisticated bloom filter. Third, we propose a memory management scheme being optimized for the CPU cache line, in order to provide a fast transaction processing. Finally, it is shown from our performance evaluation that our HyTM scheme achieves up to 2.5 times better performance by using the Stanford transactional applications for multi-processing (STAMP) benchmarks than the state-of-the-art algorithms.

• 대한전기학회논문지:전력기술부문A
• /
• 제48권9호
• /
• pp.1167-1174
• /
• 1999

In this paper, we present a new technique for the local decomposition of convex structuring elements for morphological image processing. Local decomposition of a structuring element consists of local structuring elements, in which each structuring element consists of a subset of origin pixel and its eight neighbors. Generally, local decomposition of a structuring element reduces the amount of computation required for morphological operations with the structuring element. A unique feature of our approach is the use of linear integer programming technique to determine optimal local decomposition that guarantees the minimal amount of computation. We defined a digital convex polygon, which, in turn, is defined as a convex structuring element, and formulated the necessary and sufficient conditions to decompose a digital convex polygon into a set of basis digital convex polygons. We used a set of linear equations to represent the relationships between the edges and the positions of the original convex polygon, and those of the basis convex polygons. Further. a cost function was used represent the total processing time required for computation of dilation/erosion with the structuring elements in a decomposition. Then integer linear programming was used to seek an optimal local decomposition, that satisfies the linear equations and simultaneously minimize the cost function.

• 대한전기학회논문지:전력기술부문A
• /
• 제48권12호
• /
• pp.1498-1506
• /
• 1999

In this paper, a hybridization of Evolutionary Strategy (ES) and a Two-Phase Neural Network(TPNN) is applied to the optimal environmental and economic operation. As the evolutionary computation, ES is to search for the global optimum based on natural selection and genetics but it shows a defect of reducing the convergence rate in the latter part of search, and often does not search the exact solution. Also, neural network theory as a local search technique can be used to search a more exact solution. But it also has the defect that a solution frequently sticks to the local region. So, new algorithm is presented as hybrid methods by combining merits of two methods. The hybrid algorithm has been tested on Emission Constrained Economic Dispatch (ECED) problem and Weighted Emission Economic Dispatch (WEED) problem for optimal environmental and economic operation. The result indicated that the hybrid approach can outperform the other computational efficiency and accuracy.

• 제어로봇시스템학회논문지
• /
• 제17권8호
• /
• pp.790-798
• /
• 2011

An efficient sequential computation algorithm of kinematic optimal control is suggested for redundancy resolution of freefloating manipulators. Utilization of minimum principle usually requires involved and tedious procedure of differentiation of Hamiltonian. Due to the constraints of momentum conservation, it is not easy to get exact differential equations of boundary value problem for even relatively simple free-floating manipulator models. To overcome this difficulty, we developed an effective sequential algorithm for the computation of terms appeared in the differential equations. The usefulness of suggested approach is verified by simulation of a planar 3-joints free-floating manipulator.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
• /
• pp.569-571
• /
• 1995

This paper compares the simulated annealing and the Hopfield neural network method for an optimal routing in a multistage interconnection network(MIN). The MIN provides a multiple number of paths for ATM cells to avoid cell conflict. Exhaustive search always finds the optimal path, but with heavy computation. Although greedy method sets up a path quickly, the path found need not be optimal. The simulated annealing can find an sub optimal path in time comparable with the greedy method.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
• /
• pp.6-8
• /
• 2009

This paper presents the novel implementation of memetic algorithm with GA (Genetic Algorithm) and MADS (Mesh Adaptive Direct Search), which is applied for optimal design methodology of electric machine. This hybrid algorithm has been developed for obtaining the global optimum rapidly, which is effective for optimal design of electric machine with many local optima and much longer computation time. In particular, the proposed memetic algorithm has been forwarded to optimal design of direct-driven PM wind generator for maximizing the Annual Energy Production (AEP), of which design objective should be obtained by FEA (Finite Element Analysis). After all, it is shown that GA combined with MADS has contributed to reducing the computation time effectively for optimal design of PM wind generator when compared with purposely developed GA implemented with the parallel computing method.