• Computational Structural Engineering
• /
• v.5 no.1
• /
• pp.133-142
• /
• 1992

This paper presents a method to apply the linear goal programming, which has rarely been used to the structural opimization problem due to its unique formulation, to large scale nonlinear structural optimization. The method can be used as a multicriteria optimization tool since goal programming removes the difficulty in defining an objective function and constraints. The method uses the finite element analysis, linear goal programming techniques and successive linearization to obtain the solution for the nonlinear goal optimization problems. The general formulation of the structural optimization problem into a nonlinear goal programming form is presented. The successive linearization method for the nonlinear goal optimization problem is discussed. To demonstrate the validity of the method, as a design tool, the minimum weight structural optimization problems with stress constraints are solved for the cases of 10, 25 and 200 trusses and compared with the results of the other works.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.3
• /
• pp.259-266
• /
• 2011

We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.11A
• /
• pp.1079-1085
• /
• 2007

This Paper Proposes a new optimization algorithm named by GBNSGA-II(Goal-pareto Based Non-dominated Sorting Genetic Algorithm-II) which uses Goal Programming to find non-dominated solutions in NSGA-II. Although the conventional NSGA is very popular to solve multiobjective optimization problem, its high computational complexity, lack of elitism and difficulty of selecting sharing parameter have been considered as problems to be overcome. To overcome these problems, NSGA-II has been introduced as the alternative for multiobjective optimization algorithm preventing aforementioned defects arising in the conventional NSGA. Together with advantageous features of NSGA-II, this paper proposes rather effective optimization algorithm formulated by purposely combining NSGA-II algorithm with GP (Goal Programming) subject to satisfying multiple objectives as possible as it can. By conducting computer simulations, the superiority of the proposed GBNSGA-II algorithm will be verified in the aspects of the effectiveness on optimization process in presence of a priori constrained goals and its fast converging capability.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2005.04a
• /
• pp.309-316
• /
• 2005

In this paper, we develop continuum-based design sensitivity analysis (DSA) methods using both direct differential method (DDM) and adjoint variable method (AVM) for non-shape design problems. The developed DSA method is further utilized for the topology design optimization of 3-dimensional structures. In numerical examples, the analytical DSA results are verified using finite difference ones. The topology optimization method yields very reasonable results in physical point of view.

• Phonetics and Speech Sciences
• /
• v.3 no.2
• /
• pp.65-70
• /
• 2011

Recently, audio-visual speech recognition (AVSR) has been studied to cope with noise problems in speech recognition. In this paper we propose a novel method of deciding weighting factors for audio-visual information fusion. We adopt the particle swarm optimization (PSO) to weighting factor determination. The AVSR experiments show that PSO-based normalized confidence measures (NCM) improve the rejection performance of mis-recognized words by 33%.

• Journal of the Korean Mathematical Society
• /
• v.47 no.4
• /
• pp.767-788
• /
• 2010

In this paper, we propose two limited memory BFGS algorithms with a nonmonotone line search technique for unconstrained optimization problems. The global convergence of the given methods will be established under suitable conditions. Numerical results show that the presented algorithms are more competitive than the normal BFGS method.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2008.10a
• /
• pp.308-311
• /
• 2008

The ant colony optimization (ACO) is a metaheuristic inspired by the behavior of real ants. Recently, ACO has been widely used to solve the difficult combinatorial optimization problems. In this paper, we propose an ACO algorithm to solve the two disjoint paths problem with dual link cost structure (TDPDCP). We propose a dual pheromone structure and a procedure for solution construction which is appropriate for the TDPDCP. Computational comparisons with the state-of-the-arts algorithms are also provided.

• Journal of Mechanical Science and Technology
• /
• v.18 no.2
• /
• pp.246-252
• /
• 2004

The modal characteristics of rotating structures vary with the rotating speed. The material and the geometric properties of the structures as well as the rotating speed influence the variations of their modal characteristics. Very often, the modal characteristics of rotating structures need to be specified at some rotating speeds to meet their design requirements. In this paper, rotating cantilever beam is chosen as a design target structure. Optimization problems are formulated and solved to find the optimal shapes of rotating beams with rectangular cross section.

• Journal of the Chungcheong Mathematical Society
• /
• v.30 no.1
• /
• pp.31-40
• /
• 2017

In this paper, we consider a nonsmooth multiobjective robust optimization problem with more than two locally Lipschitz objective functions and locally Lipschitz constraint functions in the face of data uncertainty. We prove a nonsmooth sufficient optimality theorem for a weakly robust efficient solution of the problem. We formulate a Wolfe type dual problem for the problem, and establish duality theorems which hold between the problem and its Wolfe type dual problem.

• Journal of applied mathematics & informatics
• /
• v.28 no.3_4
• /
• pp.823-835
• /
• 2010

In this paper, A FSQP algorithm for degenerate inequality constraints optimization problems is proposed. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving a quadratic programming subproblem. To overcome the Maratos effect, a higher-order correction direction is obtained by solving another quadratic programming subproblem. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions. Finally, some preliminary numerical results are reported.