• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.453-463
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• 2013

The probabilistic nature of renewable energy, especially wind energy, increases the needs for new forms of planning and operating with electrical power. This paper presents a novel approach for determining the short-term generation schedule for optimal operations of wind energy-integrated power systems. The proposed probabilistic security-constrained optimal power flow (P-SCOPF) considers dispatch, network, and security constraints in pre- and post-contingency states. The method considers two sources of uncertainty: power demand and wind speed. The power demand is assumed to follow a normal distribution, while the correlated wind speed is modeled by the Weibull distribution. A Monte Carlo simulation is used to choose input variables of power demand and wind speed from their probability distribution functions. Then, P-SCOPF can be applied to the input variables. This approach was tested on a modified IEEE 30-bus system with two wind farms. The results show that the proposed approach provides information on power system economics, security, and environmental parameters to enable better decision-making by system operators.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.3
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• pp.20-33
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• 2006

Because of rapid expansion of third party logistics, fierce competition in the transportation industry, and the diversification and globalization of transportation channels, an effective transportation planning by means of multimodal transport is badly needed. Accordingly, this study aims to suggest an optimal transport algorithm for the multimodal transport in the international logistics. As a solution for this problem, first of all, we have applied a pruning algorithm to simplify it, suggesting a heuristic algorithm for constrained shortest path problem to find out a feasible area with an effective time range, which has been applied to the Label Setting Algorithm, consequently leading to multiple Pareto optimal solutions. Also, in order to test the efficiency of the algorithm for constrained shortest path problem, this paper has applied it to the actual transportation path from Busan port of Korea to Rotterdam port of Netherlands.

• Journal of Distribution Science
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• v.13 no.3
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• pp.69-77
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• 2015

Purpose - The purpose of this study is to examine whether the cash policies of retail firms listed on Korean stock markets are consistent with the evidence provided in the study of Almeida et al. (2004). Liquidity management is an important issue for financially constrained firms relative to financially unconstrained firms. Because there are few sources of external funding, the optimal liquidity policies of financially constrained firms should reflect their own earnings or cash inflows to create opportunities for current and future real investments. According to this simple idea, we estimate the sensitivity of cash to cash flows and simply check whether the estimated sensitivity to cash flows of the cash retained by constrained retail firms is greater than that of the cash retained by unconstrained retail firms. Through this work, we aim to explain why the cash policies of the retail firms listed on the Korean stock markets differ from those of listed manufacturing enterprises. Research design, data, and methodology - To explain a firm's cash holdings, we use only three explanatory variables: earnings before interest and taxes (EBIT), Tobin's q, and size. All the variables are defined as the value of the numerator divided by aggregate assets. Thanks to this definition, it is possible to treat all the sample firms as a single large firm. The sample financial data for this study are collected from the retail enterprises listed on the KOSPI and KOSDAQ markets from 1991 to 2013. We can obtain these data from WISEfn, the financial information company. This study's methodology has its origin in Keynes's simple idea of precautionary liquidity demand: When a firm faces financial constraints, cash savings from earnings or cash inflows become important from the corporate finance perspective. Following this simple idea, Almeida et al. (2004) developed their theoretical model and found empirical evidence that the sensitivity of cash to cash flows varies systematically according to different types of financing frictions. To find more empirical evidence for this idea, we examined the cash flow sensitivity of the cash held by Korean retail firms. Results - Through several robustness tests, we empirically showed that financially constrained Korean retail firms display significant positive propensity to save cash from earnings before interest and taxes, while the estimated cash flow sensitivity of the cash held by unconstrained retail firms is not significant. Despite the relatively low earnings of retail firms, their sensitivity is three times greater than that of manufacturing enterprises. This implies that Korean retail firms have greater intentions of facilitating future investments rather than current investments. Conclusions - The characteristics of the cash policies of Korean retail firms differ from those of manufacturing firms. This contrast may be attributable to industry-oriented policy planning, regulations, and institutional differences. However, the industrial policymakers should observe signals of the long-term growth options of retail firms based on their high propensity to save from their cash inflows.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.31-40
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done. Informations from various sensors can find obstacles and make path. In spite of many solutions of finding optimal path, each can be applied to only a constrained condition. This means that it is difficult to find a universal algorithm. A optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose the algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers. It has an advantage of fast planning and simple operation. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in any direction. When a robot meets moving obstacles, it avoids obstacles in a random direction. RAS method using obstacle information from variable sensors is useful to get minimum path length to goal.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.120-131
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• 2004

In this paper, we propose the method of a motion planning generation in which the movement of the 3-link leg subsystem is constrained to a slider-link and a singular posture can be easily avoided. The proposed method is the jumping control moving in vertical direction which mimics a cat's behavior. That is, it is jumping toward wall and kicking it to get a higher-place. Considering the movement from the point of constraint mechanical system, the robotic system which realizes the motion changes its configuration according to the position and it has several phases such as; ⅰ) an one-leg phase, ⅱ) in an air-phase. In other words, the system is under nonholonomic constraint due to the reservation of its momentum. Especially, in an air-phase, we will use a control method using state transformation and linearization in order to control the landing posture. Also, an iterative learning control algorithm is applied in order to improve the robustness of the control. The simulation results for jumping control will illustrate the effectiveness of the proposed control method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.267-276
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• 1993

This paper discusses the neural network application in the study on the obstacle avoidance of robot manipulator during the trajectory planning. The collision problem of two robot manipulators which are simultaneously moving in the same workspace is investigated. Instead of the traditional modeling method, this paper processing based on the calculation of joint angle in the cartesian coordinate with constrained condition shows the possibility of real time control. The problem of the falling into the local minima is cleared by the adaptive weight factor control using the temperature adding method. Computer simulations are shown for the verification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3270-3294
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• 2020

Some things come easily to humans, one of them is the ability to navigate around. This capability of navigation suffers significantly in case of partial or complete blindness, restricting life activity. Advances in the technological landscape have given way to new solutions aiding navigation for the visually impaired. In this paper, we analyze the existing works and identify the challenges of path selection, context awareness, obstacle detection/identification and integration of visual and nonvisual information associated with real-time assisted mobility. In the process, we explore machine learning approaches for robotic path planning, multi constrained optimal path computation and sensor based wearable assistive devices for the visually impaired. It is observed that the solution to problem is complex and computationally intensive and significant effort is required towards the development of richer and comfortable paths for safe and smooth navigation of visually impaired people. We cannot overlook to explore more effective strategies of acquiring surrounding information towards autonomous mobility.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.390-391
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• 2006

The economic dispatch problem is important in both power system planning and operation, although there have been major advances in defining and solving more complete Optimal Power Flow(OPF) problems, there exists a need for constrained economic dispatch techniques which, though not as rigorous or as exact an OPF, are fast enough to be used on desktop computers. This paper presents a DC-OPF algorithm that is based upon Relative-Contribution Index in Generators. The transmission constraints are modeled as linear constraint based on a DC-Power-Flow model. An detailed illustrative example is presented.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.530-533
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• 1995

This paper deals with the problem of motion planning for a unicycle-like robot. We present a simple local planner for unicycle model, based on an approximation of the desired configuration generated by local holonomic planner that ignores motion constraints. To guarantee a collision avoidance, we propose an inequality constraint, based on the motion analysis with the constant control input and time interval. Consequently, we formulate our problem as the constrained optimization problem and a feedback scheme based on local sensor information is established by simply solving this problem. Through simulations, we confirm the validity and effectiveness of our algorithm.