• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2357-2375
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• 2013

Message ferry is a controllable mobile node with large capacity and rechargeable energy to collect information from the sensors to the sink in wireless sensor networks. In the existing works, route of the message ferry is often designed from the solutions of the Traveling Salesman Problem (TSP) and its variants. In such solutions, the ferry route is often a simple cycle, which starts from the sink, access all the sensors exactly once and moves back to the sink. In this paper, we consider a different case, where the ferry route is a closed walk that contains more than one simple cycle. This problem is defined as the Closed Walk Ferry Route Design (CWFRD) problem in this paper, which is an optimization problem aiming to minimize the average weighted delay. The CWFRD problem is proved to be NP-hard, and the Integer Linear Programming (ILP) formulation is given. Furthermore, a heuristic scheme, namely the Initialization-Split-Optimization (ISO) scheme is proposed to construct closed walk routes for the ferry. The experimental results show that the ISO algorithm proposed in this paper can effectively reduce the average weighted delay compared to the existing simple cycle based scheme.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.3
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• pp.133-143
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• 2016

The objective in here is to find the density, stiffness, and strength of truss-wall rectangular (TWR) model which is combined with lattice truss (MLT) inside space. The TWR unit-cell model is defined as a unit cell originated from a solid-wall rectangular (SWR) model and it has an empty space inside. Thus, the empty space inside of the TWR is filled with lattice truss model defined as TWR-MLT. The ideal solutions derived of TWR-MLT are based on TWR with MLT model and it has developed by Gibson-Ashby's theory. To validate the ideal solutions of the TWR-MLT, ABAQUS software is applied to predict the density, strength, and stiffness, and then each of them are compared with the Gibson-Ashby's ideal solution as a log-log scale. Applied material property is stainless steel 304 because of cost effectiveness and easy to get around. For the analysis, SWR and TWR-MLT models are 1mm, 2mm, and 3mm truss diameter separately within a fixed 20mm opening width. In conclusion, the relative Young's modulus and relative yield strength of the TWR-MLT unit model is reasonably matched to the ideal expectations of the Gibson-Ashby's theory. In nearby future, TWR-MLT model can be verified by advanced technologies such as 3D printing skills.t.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2524-2528
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• 2003

High-precision position system is widely used in lots of fields such as semiconductor industry, biotechnology, display and other up-to-date industry field. One of the main issues is to have a long traveling range with precision. There are a few solutions. For instance, there are inchworm methods, lever principle. In this study, we use lever principle to amplify output displacement with a new mechanical amplification structure. We designed new type 3DOF stage with PZT actuator and capacitive sensor. Non-monolithic structure is suggested to obtain the convenience of assembly and modification. Driving parts are designed as modules that generate displacement amplification of each axis. Designed motion module consists of 3 flexure hinges and a PZT actuator with double L lever structure.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.199-206
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• 2014

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.328-338
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• 1994

TSP(Traveling Salesman Problem) is a famous problem in Operations Research fields due to its applicability to various problems. It is also well-known that the problem is hard to solve in reasonable time, since it is in the NP-Complete class. Hence it is desired to develop heuristics which have polynominal complexity and also solve the problem to near-optimality. This paper presents a heuristic algorithm for TSP using the concept of dynamic programming. The proposed method has the complexity of O(N$\^$3/), and gives improved solutions than other well-known algorithms in our extensive computational experiments.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.140-147
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• 2012

Vehicle routing problem is one of the traveling salesman problems with various conditions such as vehicle capacity limits, delivery time windows, as well as time dependent speeds in metropolitan area. In this research hourly vehicle moving speeds information in a typical metropolitan area are analyzed to use the results in the design procedure of VRP heuristic. Quality initial vehicle routing solutions can be obtained with adaption of the analysed results of the time periods with no vehicle speed changes. This strategy makes complicated time dependent vehicle speed simple to solve. Time dependent vehicle speeds are too important to ignore to obtain optimum vehicle routing search for real life logistics systems.

• Structural Engineering and Mechanics
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• v.49 no.3
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• pp.329-353
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• 2014

Increasing usage of tank cars and their intrinsic instability due to sloshing of contents have caused growing maintenance costs as well as more frequent hazards and defects like derailment and fatigue of bogies and axels. Therefore, varieties of passive solutions have been represented to improve dynamical parameters. In this task, assuming 22 degrees of freedom, dynamic analysis of partially filled tank car traveling on a curved track is investigated. In order to consider stochastic geometry of track; irregularities have been derived randomly by Mont Carlo method. More over the fluid tank model with 1 degree of freedom is also presented by equivalent mechanical approach in terms of pendulum. An active suspension system for described car is designed by using linear quadratic optimal control theory to decrease destructive effects of fluid sloshing. Eventually, the performance of the active suspension system has been compared with that of the passive one and a study is carried out on how active suspension may affect the dynamical parameters such as displacements and Nadal's derailment index.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.6-12
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• 2001

Evolutionary algorithms(EAs) have been successfully applied to many combinatorial optimization problems of various engineering fields. Recently, some comparative studies of EAs with other stochastic search algorithms have, however, shown that they are similar to, or even are not comparable to other heuristic search. In this paper, a new hybrid evolutionary algorithm utilizing a new local heuristic search, for combinatorial optimization problems, is presented. The new intelligent local heuristic search is described, and the behavior of the hybrid search algorithm is investigated on two well-known problems: traveling salesman problems (TSPs), and quadratic assignment problems(QAPs). The results indicate that the proposed hybrid is able to produce solutions of high quality compared with some of evolutionary and simulated annealing.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1053-1054
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• 2008

This paper presents the mobile robot initial velocity estimation using spatial/temporal information from passive RFID system. A mobile robot is traveling along a sequence of line segments, each at a constant velocity, and the number of passive tags sensed at every sampling instant is at most one. To simplify the problem, a mobile robot is commanded to traverse two passive tags with steering angle unchanged. The 6th order polynomial equation for the mobile robot initial velocity estimation is obtained, along with some discussion on resolving the multiplicity of solutions.