• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.77-78
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• 2008

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm and the particle swarm optimization. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the particle swarm optimization method. At first, we produce paths of a mobile robot in the static environment. And then, we find midpoints of each path using the Maklink graph. Finally, the hybrid algorithm is adopted to get a shortest path. We prove the performance of the proposed algorithm is better than that of the path planning algorithm using the ant colony optimization only through simulation.

• Steel and Composite Structures
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• v.21 no.6
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• pp.1389-1410
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• 2016

This paper proposes a hybrid of topological derivative-based level set method (LSM) and isogeometric analysis (IGA) for structural topology optimization. In topology optimization a significant drawback of the conventional LSM is that it cannot create new holes in the design domain. In this study, the topological derivative approach is used to create new holes in appropriate places of the design domain, and alleviate the strong dependency of the optimal topology on the initial design. Furthermore, the values of the gradient vector in Hamilton-Jacobi equation in the conventional LSM are replaced with a Delta function. In the topology optimization procedure IGA based on Non-Uniform Rational B-Spline (NURBS) functions is utilized to overcome the drawbacks in the conventional finite element method (FEM) based topology optimization approaches. Several numerical examples are provided to confirm the computational efficiency and robustness of the proposed method in comparison with derivative-based LSM and FEM.

• Current Optics and Photonics
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• v.1 no.4
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• pp.325-335
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• 2017

Hybrid radio frequency/free space optical (RF/FSO) wireless mesh networks have attracted increasing attention for they can overcome the limitations of RF and FSO communications and significantly increase the throughput of wireless mesh networks (WMNs). In this article, a resource assignment optimization scheme is proposed for hybrid RF/FSO wireless mesh networks. The optimization framework is proposed for the objective of maximizing throughput of overall hybrid networks through joint transmission slot assignment, FSO links allocation and power control with the consideration of the fading nature of RF and FSO links. The scheme is formulated as an instance of mixed integer linear program (MILP) and the optimal solutions are provided using CPLEX and Gurobi optimizers. How to choose the appropriate optimizer is discussed by comparing their performance. Numerous simulations are done to demonstrate that the performance of our optimization scheme is much better than the current case of having the same topology.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.159-166
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• 2014

The study is conducted on the subject of optimization of components sizing for series hybrid electric propulsion systems. The components sizing of series type hybrid system is very important because each component of series type is larger than the corresponding component of the parallel type or series-parallel type. If the components sizing is greater or less than what is required to this system, the performance of the system is getting worse. The methodology for the sizing of a driving motor is introduced based on the foundation of determined system configuration and performance target. And the sizing of an engine/generator and a battery is achieved based on simulation results using Dynamic Programming. It is possible to find the optimal sizing of these components by comparing fuel efficiency of hybrid electric propulsion system for 8 driving cycles.

• Coupled systems mechanics
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• v.9 no.2
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• pp.147-161
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• 2020

Constructive merging of "basic" systems of different behavior creates hybrid systems. In doing so, the structural elements are grouped according to the behavior in carrying the load into a geometric order that provides sufficient load and structure functionality and optimization of the material consumption. Applicable in all materializations and logical geometric forms is a transparent system suitable for the optimization of load-bearing structures. Research by individual authors gave insight into suitable system constellations from the aspect of load capacity and the approximatemethod of estimating the participation of partialstiffnesswithin the rigidity ofthe hybrid system. The obtained terms will continue to be the basisfor our own research of the influence of variable parameters on the behavior of hybrid systemsformed of glued laminated girder and cable of different geometric shapes. Previous research has shown that by applying the strut-type hybrid systems can increase the load capacity and reduce the deformability ofthe free girder.The implemented parametric analysis pointsto the basic parameterin the behavior of these systems-the rigidity ofindividual elements and the overallstiffnessofthe system.The basic idea ofpre-stressing is that, in the load system or individual load-bearing element, prior to application of the exploitation load, artificially challenge the forcesthatshould optimize the finalsystembehaviorin the overall load. Pre-stressing is possible only if the supporting system orsystem's element possesssufficientstrength orstiffness, orreaction to the imposed forces of pre-stressing. In this paper will be presented own research of the relationship of partial stiffness of strut-type hybrid systemsofdifferentgeometric forms.Conducted parametric analysisofhybridsystemswithandwithoutpre-stressing, and on the example of the glulam-steel strut-type hybrid system under realistic conditions of change in the moisture content ofthe wooden girder,resulted in accurate expressions and diagramssuitable for application in practice.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.4
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• pp.407-417
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• 2003

Enen though several GA-based optimization algorithms have been successfully applied to complex optimization problems in various engineering fields, GA-based optimization methods are computationally too expensive for practical use in the field of structural optimization, particularly for large- scale problems. Furthermore, a successful implementation of GA-based optimization algorithm requires a cumbersome and trial-and-error routine related to setting of parameters dependent on a optimization problem. Therefore, to overcome these disadvantages, a high-performance GA is developed in the form of distributed hybrid genetic algorithm for structural optimization on a cluster of personal computers. The distributed hybrid genetic algorithm proposed in this paper consist of a simple GA running on a master computer and multiple μ-GAs running on slave computers. The algorithm is implemented on a PC cluster and applied to the minimum weight design of steel structures. The results show that the computational time required for structural optimization process can be drastically reduced and the dependency on the parameters can be avoided.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.57-65
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• 2015

Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.591-600
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• 2015

The efficiency of a powertrain system of hybrid vehicle is highly dependent on the design and control of the hybrid powertrain system. In other words, the optimal design of the powertrain systems is coupled with optimal control of the powertrain system. Therefore, the solution of an optimal design problem for hybrid vehicles is computationally and timely very expensive. For example, dynamic programming, which is a recursive optimization method, is usually used to evaluate the best fuel economy of certain hybrid vehicle design, and, thus, the evaluation takes tens of minutes to several hours. This research aims to accelerate the speed of efficiency evaluation of hybrid vehicles. We suggest a mathematical treat and a methodological treat to reduce the computational load. The mathematical treat is that the dynamics of system is discretized with sparse sampling time without loss of energy balance. The methodological treat is that the efficiency of the hybrid vehicle is inferred by characteristic loss evaluation that is computationally inexpensive. With the suggested methodology, evaluating a design candidate of hybrid powertrain system is taken few minutes, which was taken several hours when dynamic programming is used.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1805-1818
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• 2018

This paper proposes a novel hybrid maximum power point tracking (MPPT) algorithm combining a Whale Optimization Algorithm (WOA) and the conventional Perturb & Observation (P&O) to track/extract the highest amount of power from a solar photovoltaic (SPV) system working under partial shading conditions (PSCs). The proposed hybrid algorithm is based on a WOA which predicts the initial global peak (GP) and is followed by P&O in the final stage to achieve a quicker convergence to a GP. Thus, this hybrid algorithm overcomes the computational burden encountered in a standalone WOA, grey wolf optimization (GWO) and hybrid GWO reported in the literature. The conventional algorithm searches for the maximum power point (MPP) in the predicted region by the WOA. The proposed MPPT technique is modelled and simulated using MATLAB/Simulink for simulating an environment to check its effectiveness in accurately tracking the MPP during the GP region. This hybrid algorithm is compared with a standalone WOA, GWO and hybrid GWO. From the simulating results, it is shown that the proposed algorithm offers high tracking performance and that it increases the output power level of a SPV system under partial shading. The algorithm also verified experimentally on various PSCs.

• Korean Chemical Engineering Research
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• v.56 no.1
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• pp.29-41
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• 2018

Separating a mixture having an azeotrope or low relative volatility with single distillation column is difficult. Separating water-acetic acid mixture and water-ethanol mixture with a distillation column consumes a lot of energy. Pervaporation membrane can be used to separate the mixture in the concentration region where separation is difficult with distillation. We simulated a distillation-membrane hybrid process where membrane is located on the head of the distillation column for efficient separation of water-acetic acid and water-ethanol mixture. Permeability data were obtained from experiments and literature. We formulated an optimization problem for the process with total annual cost (TAC) as an objective function and major design variables as optimization variables. Major optimization variable affecting TAC of the hybrid process was shown to be distillate concentration. We also suggested a simplified optimization procedure to get a close-to-optimal solution.