Multiple Criterion Optimization Research Articles

Multiple criterion optimization in milling of AISI H11 mold steel under MQL condition

In this investigation, the method of minimum quantity lubrication (MQL) is utilized in the procedure of finishing milling of AISI H11 steel instead of the conventional lubrication method. The variants are three three-level experimental cutting parameters, including [Formula: see text]-cutting speed, [Formula: see text]-feed per tooth, and [Formula: see text]-depth of cut. The responses are production rate (MRR, in mm3/min), cutting force ([Formula: see text], in N), and surface roughness ([Formula: see text], in [Formula: see text]m). The purpose of this study is to generate the mathematical regression models for the responses ([Formula: see text], [Formula: see text], and MRR), and solve the multi-objective optimization problem to estimate the appropriate input parameters respecting the defined criteria for [Formula: see text], [Formula: see text], and MRR. Experimental research was conducted with an experimental matrix designed by Box–Behnken Design (BBD). The experimental runs were executed on a 5-axis CNC machine tool, model DMU50. The desirability function (DF) method is used to resolve the problem of multi-attribute optimization. The results show that the optimum process variables include [Formula: see text] m/min, [Formula: see text] mm/tooth, [Formula: see text] mm, corresponding to [Formula: see text]m, [Formula: see text] N, and [Formula: see text] mm3/min.

The Multi-Objective Optimization of Headlamp Lighting System

When designing headlights using optical software LightTools, we found that the maximum illuminance and facula diameter of the initial headlamp lighting system design were less than 20000 lux (maximum illuminance) and 40mm (facula diameter), which did not meet the minimum performance requirements. However, if we increase the maximum illuminance value, the facula diameter value will become smaller and may not meet the minimum performance requirements. In order to obtain the best value of maximum illuminance and facula diameter at the same time, we used a multi-objective optimization method (combination of Taguchi method and robust multiple criterion optimization approach (RMCO)) to solve maximum illuminance and facula diameter optimization problem. It is effective and helpful increase the maximum illuminance and facula diameter of the headlamp lighting system (The maximum illuminance increased from 9580 lux to 22900 lux, the facula diameter increased from 40mm to 50mm). In this method, the concept of statistical analysis is used to obtain a set of diversified Pareto-optimal solutions. The set of diversified Pareto-optimal solutions can obtain for energy optimized design of headlamp lighting system. This study is the first attempt to use the RMCO method to optimize the multi-objective problem in a headlamp lighting system.

Taguchi-based grey relational study for multiple criterion optimization on process variables for micro Electro-chemical Machining of Inconel Super-alloy

The findings of Inconel 718 super-alloy on material extracting potential, including surface finish, were examined in this research. The investigation was conducted out using micro electrochemical metalworking with different factors and a titanium rod material as a tool. Utilizing Minitab 19 software, the optimizing approach has been predicated on Taguchi's related gray relational procedure. The Taguchi's approach was used to create significant attributes for the L9 orthogonalstring, utilizing three inputfactors: voltage (VT), electrolyteconcentration (EC), and current (CT). Taguchi's design assessment was used to evaluate the influence of input factors on the process of dissolving and machined surface qualityof the material. Regression techniques were established for forecasting. Finally, the best test arrayfor material removal rate was 16 V, 0.40 mol/lit, and 0.8 amp. The superior surface roughness test arraywas 9 V, 0.41 mol/lit, and 1 amps. According to the grey relational analysis, array number three produced the best results.

Mathematical modeling and modification of an activated sludge benchmark process evaluated by multiple performance criteria

Optimal modification of an activated sludge process (ASP) evaluated by multiple performance criteria was studied. A benchmark process in BSM1 was taken as a target process. Four indexes of percentage of effluent violation (PEV), energy consumption (OCI), total volume of tanks (TV) and total suspended solid in tank5 (TSSa5), were criteria and eleven process parameters were decision variables, making up the multiple criteria optimization model, which was solved by non-dominated sorting genetic algorithm II (NSGA-II) in MATLAB. Pareto solutions were obtained; one solution (opt1) was selected based on the authors’ decision for a further analysis. Results show that the process with opt1 strategy exhibits much better performance of PEV and OCI than with the default, being improved by 74.17% and 9.97% specifically under dry influent and without control. These results indicated that the multiple criterion optimization method is very useful for modification of an ASP.

Study of extended optimization for U-type 2× zoom optics with free-form surface

Abstract In this paper a U-type 2× zoom miniature lens design with two prisms will have less overall length than a general optical design; however, with the zigzag path of light, aberrations like: spherical aberration, coma aberration, distortion, and Image Plan Offset will result. In such a design, a free-form surface prism with aspherical coefficients may significantly improve the system's performance if the coefficients of the free-form surface prisms are well optimized. A combination of the Taguchi Method and the robust multiple criterion optimization (RMCO) approach is employed in this study to achieve success in minimizing axial aberrations such as spherical and coma aberrations. In the RMCO approach, a Pareto-optimal robust design solution is set with the aid of experimental set-ups that use ANOVA results to quantify the relative dominance and significance of the design factors. It is concluded that the Taguchi Method and RMCO approach can successfully reduce the spherical aberration (43.93%) and coma (29.89%) of the U-type 2× zoom lens system.

Optical design and multiobjective optimization of miniature zoom optics with liquid lens element

We propose an optical design for miniature 2.5x zoom fold optics with liquid elements. First, we reduce the volumetric size of the system. Second, this newly developed design significantly reduces the number of moving groups for this 2.5x miniature zoom optics (with only two moving groups compared with the four or five groups of the traditional zoom lens system), thanks to the assistance of liquid lens elements in particular. With regard to the extended optimization of this zoom optics, relative illuminance (RI) and the modulation transfer function (MTF) are considered because the more rays passing through the edge of the image, the lower will be the MTF, at high spatial frequencies in particular. Extended optimization employs the integration of the Taguchi method and the robust multiple criterion optimization (RMCO) approach. In this approach, a Pareto optimal robust design solution is set with the aid of a certain design of the experimental set, which uses analysis of variance results to quantify the relative dominance and significance of the design factors. It is concluded that the Taguchi method and RMCO approach is successful in optimizing the RI and MTF values of the fold 2.5x zoom lens system and yields better and more balanced performance, which is very difficult for the traditional least damping square method to achieve.

A technique for multiple criterion approximation of FIR filters in magnitude and group delay

In spite of the attention received by nonlinear phase (NLP) FIR filter design, the best way to solve this problem is still open to debate. The formulation of nonlinear phase FIR filter design in terms of simultaneous magnitude and group-delay approximation addresses the two parameters of ultimate interest for applications. The simultaneous minimization of these two functions (one of which, the group delay, rational) is approached on the basis of an original extension of the differential correction algorithm. The proposed design tool enjoys interesting theoretical properties and works very effectively. The filters obtained according to the multiple criterion optimization (MCO). Formulation are compared against filters that are optimal in the complex Chebychev norm. Then, the flexibility characteristic of MCO formulations of trading off between magnitude and group-delay performance is exemplified. >

The use of multiple criterion optimization for frequency domain design of noncausal IIR filters

Noncausal recursive filters have recently been proposed because of their increased efficiency versus linear phase FIR filters and causal IIR filters [2]. A general frequency domain design technique capable of exploiting the characteristics of noncausal filters is not yet available. This paper proposes the use of multiple criterion optimization for the frequency domain design of noncausal IIR filters. A new family of filters is generated and their efficiency versus causal FIR filters and IIR filters is discussed.

Simultaneous design in both magnitude and group-delay of IIR and FIR filters based on multiple criterion optimization

This work considers the simultaneous design in both magnitude and group-delay of digital transfer functions on the basis of multiple criterion optimization. Both causal IIR filters and nonlinear phase FIR filters are studied. Examples of the optimal tradeoff filters, both FIR filters and IIR filters, are presented and their characteristics are analyzed.

Multiple criterion optimization with yield maximization

A number of recent papers have described circuit optimization methods in which maximizing yield was the sole design criterion. However, in actual practice there are many competing design criteria such as minimizing power and area, maximizing speed, etc., as well as maximizing yield. In this paper the techniques of Multiple Criterion Optimization (MCO) are used to provide a framework within which to consider all of these objectives simultaneously. Towards this end a theoretical foundation for the analysis of geometrically based yield algorithms is introduced. This framework can be used to investigate the yield estimation algorithms of Director, Hachtel and Brayton, and Bandler and Abdel-Malek. By combining features from both of these methods, a new yield estimation scheme is developed which is better suited to the needs of the MCO problem. The ideas of MCO and the new yield estimation procedure are applied to the design of a two-input MOSFET NAND gate.

Multiple criterion optimization for the design of electronic circuits

Tbe basis of most engineering design Is making tradeoffs among competing factors. This Is especially true in the design of electronic circuits. In this paper we examine multiple criterion optimization (MCO), one aspect of the multiple criterion decision making (MCDM) problem. Because the Ideas and methods of MCO may not be familiar to circuit designers a tutorial review of the area is included. We then develop a weighted oo-norm method for generating noninferior solutions to the MCO problem. User oriented weight selection heuristics are developed and we apply this technique to the MCO design of an MOSFET hand gate. Next we extend this technique to generate a family of weighted p-norm methods for solving the MCO problem. We also develop a canonic weight associated with the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\rho</tex> -norm method that contains the weight selection technique of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\alpha</tex> -norm. This family of MCO methods allows a new and useful interpretation to be given to many of the optimization methods that have been applied to the design of electronic circuits.