摘要：The application of the Non-dominated Sorting genetic Algorithm Ⅱ (NSGA-Ⅱ) in designing microwave absorbers is described in this paper. To obtain high performance coatings,we put forward three cost functions,which represent three objectives of strong-absorption,broad-bandwidth and thin structure,and study the tradeoffs between each other. Numerical calculations on available materials in 2―18 GHz are implemented to construct the Pareto front and Pareto-optimal surface for two and three objectives respectively. Results indicate that the NSGA-Ⅱ can work more efficiently and effectively than traditional Pareto genetic algorithms. Additionally,we present several particular designs from the above Pareto front (surface) for potential applications in different frequency bands. For example,a four-layer absorber with thickness of 2.8071 mm is obtained to provide average reflection coefficient of -11.95 dB and average reflection bandwidth of 0.5780 in 2―18 GHz,considering arbitrary incident angles (0°―89°) and both TE and TM polarizations.

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摘要：This paper presents the design of Optimal Infinite-Impulse Response (IIR) digital filters using genetic Algorithm (GA). IIR filter is essentially a digital filter with Recursive responses. Since the error surface of digital IIR filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. This paper presents heuristic way for the designing IIR filters. GA is a powerful global optimization algorithm introduced in combinatorial optimization problems. The paper finds the optimum Coefficients of IIR digital filter through GA. Design of Lowpass and High pass IIR digital filter is proposed to provide estimate of transition band. It is found that the calculated values are more optimal than fda tool available for the design of filter in MATLAB. The simulation result of the employed examples shows an improvement on transition band and mean-square-error (MSE). The position of pole-zero is also presented to describe stability and results are compared with Simulated Annealing (SA) method.

摘要：Many engineering design problems are characterized by presence of several conflicting objectives. This requires efficient search of the feasible design region for optimal solutions which simultaneously satisfy multiple design objectives. genetic algorithm optimization (GAO) is a powerful search technique with faster convergence rates than traditional evolutionary algorithms. This paper applies two GAO-based approaches to multi-objective engineering design and finds design variables through the feasible space. To demonstrate the utility of the proposed methods, the multi-objective design of an I-beam will be presented.

摘要：This paper presents a comprehensive review of various traditional systems of crude oil distillation column design, modeling, simulation, optimization and control methods. Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column. It was discovered that many past researchers used rigorous simulations which led to convergence problems that were time consuming. The use of dynamic mathematical models was also challenging as these models were also time dependent. The proposed methodologies use back-propagation algorithm to replace the convergence problem using error minimal method.

摘要：This paper proposes a genetic Programming based algorithm that can be used to design optimal controllers. The proposed algorithm will be named a Multiple Basis Function genetic Programming (MBFGP). Herein, the main ideas concerning the initial population, the tree structure, genetic operations, and other proposed non-genetic operations are discussed in details. An optimization algorithm called numeric constant mutation is embedded to strengthen the search for the optimal solutions. The results of solving the optimal control for linear as well as nonlinear systems show the feasibility and effectiveness of the proposed MBFGP as compared to the optimal solutions which are based on numerical methods. Furthermore, this algorithm enriches the set of suboptimal state feedback controllers to include controllers that have product time-state terms.

摘要：The optimizations of constrained layered damped (CLD) laminated structures are discussed in this study. genetic algorithms (GAs) are employed as the search tool for optimization because these algorithms are suitable for solving optimization problems involving multiple discrete variable combinations. The numerical computation packages, ANSYS and MATLAB, have been used to estimate the optimum stacking sequence of CLD laminated structures. MATLAB package is used to achieve GAs process, and ANSYS package is used to proceed the structural analysis. This study successfully developed a numerical simulation mechanism for optimizing CLD adhesion efficiency by implementing GAs and the finite element method. The loss coefficients of the CLD damping layer vary with vibration frequency and failure constraints of CLD laminated plates are considered in objective function. In addition, the modified plasticity analysis (MPA) is used to increase the search efficiency of GAs and simply plastic analysis.

摘要：This paper presents an optimal vehicle and seat suspension design for a half-car vehicle model to reduce human-body vibration (whole-body vibration). A genetic algorithm is applied to search for the optimal parameters of the seat and vehicle suspension. The desired objective is proposed as the minimization of a multi-objective function formed by the combination of seat suspension working space (seat suspension deflection), head acceleration, and seat mass acceleration to achieve the best comfort of the driver. With the aid of Matlab/Simulink software, a simulation model is achieved. In solving this problem, the genetic algorithms have consistently found near-optimal solutions within specified parameters ranges for several independent runs. For validation, the solution obtained by GA was compared to the ones of the passive suspensions through sinusoidal excitation of the seat suspension system for the currently used suspension systems.

摘要：This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.

摘要：In accordance with the enhancement for luminous efficiency improving, LED (Light Emitting Diode) has been gradually developed by combining the characteristics of small volume, impact resistance, good reliability, long life, low power consumption with multiple purposes for energy saving and environmental protection. Therefore, the array LED has been widely applied in human livings nowadays. This study applies the finite element analysis software ANSYS to analyze the thermal behavior of the array power LED work lamp which is modeled by four same-size LED with MCPCB (Metal Core Print Circuit Board) mounted on a base heat-sink. The Flotran heat flow analysis is applied to obtain the natural convection of air coefficient, while the convection value can be confirmed by the iterative method since it is set as the boundary condition for ANSYS thermal analysis to obtain the temperature distribution, accordingly the chip junction temperature and the base heat-sink temperature were followed through experiments in order to check if the simulation results meet the design requirements and coincide with the power LED product design specification. Prior to the optimal design process for chip junction temperature, the most significant parameters were first chosen by the fractional factorial design. The regressive models were respectively setup by the dual response surface method (RSM) and the mixed response surface method. Furthermore, the genetic algorithm combined with response surface method was applied to acquire the optimal design parameters, and the results were obtained from both methods, which are reviewed for comparison. Afterwards, the mixed response surface method is adopted to investigate the effects of interactions among various factors on chip junction temperature. In conclusion, it is found that the thermal conductivity of MCPCB and the height of base heat-sink are the two major significant factors. In addition, the interactive effects between chip size and thermal co