• The Journal of Information Technology
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• v.3 no.2
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• pp.73-85
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• 2000

The efficient algorithms are suggested in this study for solving the multicommodity network flow problems applied to Communications Systems. These problems are typical NP-complete optimization problems that require integer solution and in which the computational complexity increases numerically in appropriate with the problem size. Although the suggested algorithms are not absolutely optimal, they are developed for computationally efficient and produce near-optimal and primal integral solutions. We supplement the traditional Lagrangian method with a price-directive decomposition. It proceeded as follows. First, A primal heuristic from which good initial feasible solutions can be obtained is developed. Second, the dual is initialized using marginal values from the primal heuristic. Generally, the Lagrangian optimization is conducted from a naive dual solution which is set as ${\lambda}=0$. The dual optimization converged very slowly because these values have sort of gaps from the optimum. Better dual solutions improve the primal solution, and better primal bounds improve the step size used by the dual optimization. Third, a limitation that the Lagrangian decomposition approach has Is dealt with. Because this method is dual based, the solution need not converge to the optimal solution in the multicommodity network problem. So as to adjust relaxed solution to a feasible one, we made efficient re-allocation heuristic. In addition, the computational performances of various versions of the developed algorithms are compared and evaluated. First, commercial LP software, LINGO 4.0 extended version for LINDO system is utilized for the purpose of implementation that is robust and efficient. Tested problem sets are generated randomly Numerical results on randomly generated examples demonstrate that our algorithm is near-optimal (< 2% from the optimum) and has a quite computational efficiency.

• Korean Journal of Construction Engineering and Management
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• v.12 no.4
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• pp.50-58
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• 2011

Lean concept is management philosophy that defines a customer's value and eliminates wasteful and impeditive factors. Management philosophy of Lean in the construction industry is referred to as "Lean Construction". Now this concept has expanded to achieve effective productivity during the design phase. Currently the norm of the domestic design process has been Point-based Design(PBD). It involves selecting a single structurally-feasible design option early and then refining that single design as more information becomes available throughout the design process. This single design is then re-worked until a solution is found that is feasible for all parties. On the contrary, Set-based Design(SBD) is based on lean processes to eliminate waste and improve project productivity. It focuses on keeping the design space as open as long as possible, to allow "subdesign" to advance and not labeling them as secondary in importance. Preserving the maximum number of feasible designs as long as possible reduces the likelihood that rework will be necessary and allows all project participants to utilize their unique expertise to make the project successful. This study proposes that the design methodology of minimizing waste and increasing productivity through SBD of AHP, one of the decision making process so as to compare PBD with SBD and tries to find decision making process and then suggest that application methodology through performs case study of SBD process.

• IE interfaces
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• v.18 no.4
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• pp.370-381
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• 2005

This study is concerned with seeking the optimal allocation(disposition) for maximizing utility of consolidating old fashioned and new air defense weapon system like SAM-X(Patriot missile) and developing efficient solution algorithm based on simulated annealing(SA) algorithm. The SED(selection by effectiveness degree) procedure is implemented with an enhanced SA algorithm in which neighboring solutions could be generated only within the optimal feasible region by using a specially designed PERTURB function. Computational results conducted on the problem sets with a variety of size and parameters shows the significant efficiency of our SED algorithm over existing methods in terms of both the computation time and the solution quality.

• Journal of applied mathematics & informatics
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• v.32 no.3_4
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• pp.359-375
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• 2014

In this paper, a multiobjective nondifferentiable fractional programming problem (MFP) is considered where the objective function contains a term involving the support function of a compact convex set. A vector valued (generalized) ${\alpha}$-univex function is defined to extend the concept of a real valued (generalized) ${\alpha}$-univex function. Using these functions, sufficient optimality criteria are obtained for a feasible solution of (MFP) to be an efficient or weakly efficient solution of (MFP). Duality results are obtained for a Mond-Weir type dual under (generalized) ${\alpha}$-univexity assumptions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.193-196
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• 2002

Vehicle routing problem is known to be a NP-hard problem, and is traditionally solved by some heuristic approaches. This paper investigates the application of the computer method COMSOAL to the optimal vehicle routing selection problem. The COMSOAL (Computer Method of Sequencing Operations for Assembly Lines) is a computer heuristic originally developed to solve an assembly line balancing problem a few decades ago. The solution methodology of repeatedly running COMSOAL will result in many feasible solutions from which the best is chosen. This solution approach now becomes viable thanks to the significantly increased speed of recent computer technology. This paper discusses the adaptation of the COMSOAL approach to the known set of simple vehicle routing example problem. The results show that the COMSOAL can be a good possible approach to solve the vehicle routing problem.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.131-132
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• 2007

This paper presents a numerical solution of PID controller design. The complete set of PID controllers stabilizing an LTI plant that solely determined from the knowledge of the frequency response and the number of unstable poles of the plant. An illustrative example is given to describe implementation of the design algorithm and exhibit graphical displays of the feasible regions of the design parameters.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.57-58
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• 2007

This paper presents a numerical solution of first order controller design. The complete set of first order controllers that stabilizes for a LTI plant solely determined from the knowledge of the frequency response and the number of unstable poles of the plant. An illustrative example is given to describe the design procedure and exhibit graphical displays of the feasible regions of the design parameters.

• Smart Structures and Systems
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• v.20 no.5
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• pp.607-618
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• 2017

In this research, a newly developed nature-inspired optimization method, the Lion Pride Optimization algorithm (LPOA), is utilized for optimal design of composite steel box girder bridges. A composite box girder bridge is one of the common types of bridges used for medium spans due to their economic, aesthetic, and structural benefits. The aim of the present optimization procedure is to provide a feasible set of design variables in order to minimize the weight of the steel trapezoidal box girders. The solution space is delimited by different types of design constraints specified by the American Association of State Highway and Transportation Officials. Additionally, the optimal solution obtained by LPOA is compared to the results of other well-established meta-heuristic algorithms, namely Gray Wolf Optimization (GWO), Ant Lion Optimizer (ALO) and the results of former researches. By this comparison the capability of the LPOA in optimal design of composite steel box girder bridges is demonstrated.

• Journal of Power Electronics
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• v.19 no.4
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• pp.989-999
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• 2019

This paper proposes a fault-tolerant control strategy with finite control set model predictive control (FCS-MPC) based on hierarchical optimization for five-level H-bridge neutral-point-clamped (5L-HNPC) inverter-fed induction motor drives. Fault-tolerant operation is analyzed, and the fault-tolerant control algorithm is improved. Adopting FCS-MPC based on hierarchical optimization, where the voltage is used as the controlled objective, called model predictive voltage control (MPVC), the postfault controller is simplified as a two layer control. The first layer is the voltage jump limit, and the second layer is the voltage following control, which adopts the optimal control strategy to ensure the current following performance and uniqueness of the optimal solution. Finally, simulation and experimental results verify that 5L-HNPC inverter-fed induction motor drives have strong fault tolerant capability and that the FCS-MPVC based on hierarchical optimization is feasible.

• Water for future
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• v.28 no.2
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• pp.169-180
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• 1995

The cost of a looped pipe network is affected by a set of loop flows. The mathematical model for optimizing the looped pipe network is expressed in the optimal set of loop flows to apply to a stochastic optimization method. Because the feasible region of the looped pipe network problem is nonconvex with multiple local optima, the Modified Stochastic Probing Method is suggested to efficiently search the feasible region. The method consists of two phase: i) a global search phase(the stochastic probing method) and ii) a local search phase(the nearest neighbor method). While the global search sequentially improves a local minimum, the local search escapes out of a local minimum trapped in the global search phase and also refines a final solution. In order to test the method, a standard test problem from the literature is considered for the optimal design of the paralled expansion of an existing network. The optimal solutions thus found have significantly smaller costs than the ones reported previously by other researchers.