• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1998.10a
• /
• pp.3-10
• /
• 1998

Optimization problems may be devided into geometry optimization problems and topology optimization problems. In this paper, a method using tile equivalent material properties prediction techniques of a particulate-reinforced composites is proposed for the topology optimization. This method makes use of penalty factor in order that regions with intermediate value of design variables can be penalized. The computational results being obtained from PLBA algorithm of some values of penalty factor are presented.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.14 no.2
• /
• pp.73-83
• /
• 2014

Many recent theoretical developments in the field of machine learning and control have rapidly expanded its relevance to a wide variety of applications. In particular, a variety of portfolio optimization problems have recently been considered as a promising application domain for machine learning and control methods. In highly uncertain and stochastic environments, portfolio optimization can be formulated as optimal decision-making problems, and for these types of problems, approaches based on probabilistic machine learning and control methods are particularly pertinent. In this paper, we consider probabilistic machine learning and control based solutions to a couple of portfolio optimization problems. Simulation results show that these solutions work well when applied to real financial market data.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.3
• /
• pp.129-136
• /
• 2009

The estimation of muscle force is important to understand the roles of the muscles. The static optimization method can be used to figure out the individual muscle forces. However, muscle forces during the movement including muscle co-contraction cannot be considered by the static optimization. In this study, a hybrid static optimization method was introduced to find the well-matched muscle forces with EMG signals under muscle co-contraction conditions. To validate the developed algorithm, the 3D motion analysis and its corresponding inverse dynamics using the musculoskeletal modeling software (SIMM) were performed on heel-rise movements. Results showed that the developed algorithm could estimate the acceptable muscle forces during heel-rise movement. These results imply that a hybrid numerical approach is very useful to obtain the reasonable muscle forces under muscle co-contraction conditions.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.425-436
• /
• 2016

In this paper, a parameter optimization based iterative learning control strategy is presented for permanent magnet synchronous motor control. This paper analyzes the mechanism of iterative learning control suppressing PMSM torque ripple and discusses the impact of controller parameters on steady-state and dynamic performance of the system. Based on the analysis, an optimization problem is constructed, and the expression of the optimal controller parameter is obtained to adjust the controller parameter online. Experimental research is carried out on a 5.2kW PMSM. The results show that the parameter optimization based iterative learning control proposed in this paper achieves lower torque ripple during steady-state operation and short regulating time of dynamic response, thus satisfying the demands for both steady state and dynamic performance of the speed regulating system.

• Industrial Engineering and Management Systems
• /
• v.10 no.1
• /
• pp.7-14
• /
• 2011

In solving the Job Shop Scheduling Problem, the best solution rarely is completely random; it follows one or more rules (heuristics). The Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing, and Tabu search, which belong to the Evolutionary Computations Algorithms (ECs), are not efficient enough in solving this problem as they neglect all conventional heuristics and hence they need to be hybridized with different heuristics. In this paper a new algorithm titled "Shaking Optimization Algorithm" is proposed that follows the common methodology of the Evolutionary Computations while utilizing different heuristics during the evolution process of the solution. The results show that the proposed algorithm outperforms the GA, PSO, SA, and TS algorithms, while being a good competitor to some other hybridized techniques in solving a selected number of benchmark Job Shop Scheduling problems.

• Structural Engineering and Mechanics
• /
• v.37 no.5
• /
• pp.543-560
• /
• 2011

In structural engineering there are randomness inherently exist on determination of the loads, strength, geometry, and so on, and the manufacturing of the structural members, workmanship etc. Thus, objective and constraint functions of the optimization problem are functions that depend on those randomly natured components. The constraints being the function of the random variables are evaluated by using reliability index or performance measure approaches in the optimization process. In this study, the minimum weight of a space truss is obtained under the uncertainties on the load, material and cross-section areas with harmony search using reliability index and performance measure approaches. Consequently, optimization algorithm produces the same result when both the approaches converge. Performance measure approach, however, is more efficient compare to reliability index approach in terms of the convergence rate and iterations needed.

• Journal of Power Electronics
• /
• v.12 no.2
• /
• pp.368-376
• /
• 2012

This paper deals with an optimization approach of 3D space placement of power components under volume and thermal constraints. It consists in optimizing semiconductors positions on a heat sink by respecting the components junction temperatures and minimizing the heat sink size. The aim is to remove risks on the 3D converter components placement and ensure their effective integration before carrying out the first physical prototype. This approach is based on coupling an optimization environment with a thermal finite element simulation tool. A pre-sizing step using analytical models is performed to set the optimization computations coupled to numerical simulation.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.12
• /
• pp.102-109
• /
• 2009

This study proposes the structural optimization of a manifold valve. FE analysis is performed to evaluate the strength of a manifold valve. In addition, the structural optimization technique is applied to reduce its weight. In this study, the optimization method using the kriging interpolation method is adopted to obtain the minimum weight satisfying the strength constraint. The maximum stress and the weight are replaced by the metamodels. In this process, tile sample points are generated by latin-hypercube design. Optimum designs are obtained by ANSYS Workbench and the in-house program.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.1
• /
• pp.17-22
• /
• 2012

Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.

• Structural Engineering and Mechanics
• /
• v.6 no.1
• /
• pp.31-40
• /
• 1998

The research and applications of numerical methods of design optimization on structural dynamic behaviors are presented in this paper. The emphasis is focused on the dynamic design optimization of aerospace structures, particularly those composed of composite laminate and sandwich plates. The methods of design modeling, sensitivity analysis on structural dynamic responses, and the optimization solution approaches are presented. The numerical examples of sensitivity analysis and dynamic structural design optimization are given to demonstrate the effectiveness of the numerical methods.