• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.747-752
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• 2004

Researches about scheduling of the distributed real-time systems have been proposed. However, they have some weak points, not scheduling both sporadic and periodic tasks and messages or being unable to guaranteeing the end-to-end constraints due to omitting precedence relations between sporadic tasks. So this paper proposes a new scheduling method for distributed real-time systems consisting of sporadic and periodic tasks with precedence relations and sporadic and periodic messages, guaranteeing end-to-end constraints. The proposed method is based on a binary search-based period assignment algorithm, an end-to-end laxity-based priority assignment algorithm, and three kinds of schedulability analysis, node, network, and end-to-end schedulability analysis. In addition, this paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system, shows that existing scheduling methods such as Rate Monotonic (RM) scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints, and proposes an end-to-end laxity-based priority assignment algorithm.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1162-1172
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• 2000

The research was conducted to quantify farm and household characteristics of sheep farmers, evaluate farmer access to and the effectiveness of livestock services in sheep farming areas, and examine regional constraints to improving sheep productivity and profitability in Nepal. A rapid diagnostic socioeconomic survey of 200 sheep farmers was carried out in 1996 and all four ecological regions (Trans-Himalayan, Mountains, Hills and Terai), each with a distinct local sheep breed, were represented in the survey. Six major constraints were identified: (a) poor performance of local sheep breeds, (b) a serious seasonal deficit of pasture and other feed, (c) the lack of an organized market for wool and meat, (d) poor access to agricultural credit, (e) primitive shearing equipment, and (f) an inadequate supply of drinking water for sheep. Strategies to assist farmers develop their sheep management skills, improve access and quality of support services, improved technology adaptable to local conditions and effective linkages with local carpet and meat industry are likely to overcome the constraints and alleviate persistent poverty faced by sheep farmers in Nepal.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.6 s.237
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• pp.842-851
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• 2005

In this paper, a new method for constrained optimization of noisy functions is proposed. In approximate optimization using response surface methods, if constraints have severe noise, the approximate feasible region defined by approximate constraints is apt to include some of the infeasible region defined by actual constraints. This can cause the approximate optimum to converge into the infeasible region. In the proposed method, the approximate optimization is performed with the approximate constraints shifted by their deviations, which are calculated using a diagonal quadratic response surface method. This can prevent the approximate optimum from converging into the infeasible region. To fit the objective and constraints into diagonal quadratic models, we select the center and 4 additional points along each axis of design variables as experimental points. The deviation of each function is calculated using the differences between the real and approximate function values at the experimental points. A sequential approximate optimization technique based on the trust region algorithm is adopted to manage approximate models. The proposed approach is validated by solving some design problems. The results of the problems show the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.793-796
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• 1996

This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

• Structural Engineering and Mechanics
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• v.65 no.6
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• pp.707-719
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• 2018

In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.391-393
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• 2000

This paper presents an new algorithm for the economic load dispatch considering the reliability level constraints of composite power system under deregulated electricity market. It is the traditional ELD problem that generation powers have been dispatched In order to minimize total fuel cost subjected to constraints which sum of powers generated must equal the received load and no violating lower and upper limit constraints on generation. Under deregulated electricity market, however, generation powers of a pool have to be reallocated newly in order to satisfy the reliability differentiated level required at a load point because of a reliability differentiated electricity service which is a part of the priority service. In this study, new economic load dispatch algorithm for reallocating the generation powers of a pool in order to satisfy the reliability differentiated level under deregulated competitive electricity market is proposed. The uncertainties of not only generators but also transmission lines are considered fer the reliability evaluation. The characteristics and effectiveness of this methodology are illustrated by the case studies on MRBTS and IEEE-RTS.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.215-218
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• 1996

In work scheduling problems, scheduling constraints are not absolutely rigid; they may be changed depending on the scheduling aspect effected. In order to cope with changes in scheduling constraints and assignment strategies and to optimize scheduling results quickly, this paper will propose a new scheduling method which combines knowledge engineering and mathematical programming techniques.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.1019-1031
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• 2004

This paper describes a new modeling method for the prediction of transmembrane protein topology. The structural regions of the transmembrane protein have been modeled by means of a multiple state hidden Markov model that has provided for the detailed modeling of the heterogeneous amino acid distributions of each structural region. Grammatical constraints have been incorporated to the prediction method in order to capture the biological order of membrane protein topology. The proposed method correctly predicted 76% of all membrane spanning regions and 92% sidedness of the integration when all membrane spanning regions were found correctly.

• Language and Information
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• v.5 no.1
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• pp.73-85
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• 2001

The purpose of this paper is to explore the relationship between nominal markers and scrambling in Korean by providing proper LP constraints based on Cho &Chai (2000) anc Cho & Choe(2001). In doing so, we introduce a new type marker which includes case, postpositions and delimiters and propose the Adjunct LP Constraint and the Argument LP Constraint. Our LP constraints presents a solution to the problems of the previous analyses such as Kuno's (1980) Crossing-Over Constraint. The newly postulated type marker enables us to account for the scrambling possibilities of the NPs containing cases as well as postpositions and delimiters.