Parameters Of Objective Function Research Articles

The effect of HZSM-5 catalyst particle size on kinetic models of methanol to gasoline conversion

In chemical reactions, a principal and influential parameter is particle size. The effect of HZSM-5 catalyst particle size on the kinetics of methanol conversion to gasoline has been investigated in this work. Three catalysts of 90nm (Z1), 1μm (Z2) and 4μm (Z3) containing Si/Al ratios of 25, and a 90nm sized with a Si/Al ratio of 50 (Z4) were prepared. The experiments were performed at temperatures of 598, 623 and 648K at different feed rates. Chen and Schipper kinetic models, credible models for MTG process, were chosen to study the catalyst particle size effect on MTG process kinetics. R2 adj. values for each of the models show that the experimental data are in relatively good agreement with Chen and Schipper models. In order to check the results of modeling with experimental data, objective function parameter was applied as a criterion and Z1 catalyst showed the best performance using Chen model, closely followed by Z2.

The Paradox of Policy-Relevant Natural Experiments

Conventional wisdom holds that natural experiments represent especially credible bases for econometric inference facilitating evidence-based policymaking. We illustrate the fragility of policy-relevant evidence generated by first-stage randomizations by way of parable economies. In the first (second) economy, the econometric analysis is relevant (irrelevant) as the government is able (powerless) to alter policy in the future. In the first economy, but not the second, econometric evidence is contaminated by endogeneity after-the-fact, with treatment responses contingent upon (unknown) parameters of the government objective function into which the empirical estimates will be fed. We have the following paradox: The irrelevant natural experiment is bias-free, while the relevant experiment is biased after-the-fact. Extending this argument, we show a perceived-credible natural experiment is biased by Hawthorne Effects while a perceived-non-credible experiment is not. Importantly, since we consider measure zero experimental subjects, the Hawthorne Effects we illustrate must be understood as arising from rational expectations as distinct from behavioral motives posited in the psychology literatures.

Research on data reconciliation based on generalized T distribution with historical data

In the most of previous data reconciliation(DR) studies, process data were conventionally characterized by normal Gaussian distribution, so the optimality/validity of DR estimator is implicitly based on a main assumption that errors follow normal Gaussian distribution. When this assumption is not satisfied, conventional data reconciliation approaches will become unavailable. However, normal distribution usually does not exist in real chemical engineering practice, as it is hard to ensure the normality even for high-quality measurements. So it is necessary to propose a new DR method which can accommodate more variety of measurement error distribution. In this paper, generalized T distribution is applied to accommodate measurement error distribution, meanwhile, historical data is introduced to estimate the objective function parameters by using Particle Swarm Optimization (PSO) algorithm. A novel robust data reconciliation method is proposed based on GT distribution and historical data, at the same time, its robustness characteristics are investigated. The new method is demonstrated on a steam-metering system for a methanol synthesis unit. Based on the comparison with other DR methods, the novel robust DR method can effectively improve the reliability of reconciled data even when errors do not follow normal distribution.

Improvement and prevention of asthma with concomitant treatment of allergic rhinitis and allergen-specific therapy.

Asthma and allergic rhinitis are 2 of the most prevalent chronic medical diseases. Asthma is estimated to affect 8% of adults and 9% of children, with nearly 300 million people affected worldwide. Poorly controlled allergic rhinitis may be associated with worsening asthma symptoms over time. Various treatments have been proposed in the improvement and prevention of asthma in children and adults with allergic symptoms, which have included pharmacotherapy with antihistamines and topical intranasal corticosteroids, as well as allergen-specific immunotherapy. Articles were selected through PubMed and personal knowledge of the authors based on a comprehensive literature review examining whether treatment of allergic rhinitis improves and/or prevents concomitant symptoms of asthma. The largest and highest-quality studies were included in the literature review. The search selection was not standardized. Articles written in a language other than English were excluded. Clinical trials have showed improvement in asthma symptoms with concomitant treatment of allergic rhinitis with antihistamines and topical intranasal corticosteroids, though improvement in objective pulmonary function parameters has not been uniformly demonstrated with antihistamine use alone. There is very strong evidence to suggest that subcutaneous and sublingual immunotherapy may in addition prevent the progression of asthma in high-risk atopic patients by inducing immunological tolerance. Traditional pharmacotherapy with antihistamines and topical intranasal steroids has been shown to improve allergic rhinitis symptoms with concomitant allergic asthma; however, only allergen-specific immunotherapy offers long-term control in improving asthma symptoms, exacerbations, and likely ultimate prevention in developing asthma.

A Generalized Interval Fuzzy Chance-Constrained Programming Method for Domestic Wastewater Management Under Uncertainty – A Case Study of Kunming, China

In this study, interval mathematical programming (IMP), m λ -measure, and fuzzy chance-constrained programming are incorporated into a general optimization framework, leading to a generalized interval fuzzy chance-constrained programming (GIFCP) method. GIFCP can be used to address not only interval uncertainties in the objective function, variables and left-hand side parameters but also fuzzy uncertainties on the right-hand side. Also, it can reflect the aspiration preference of optimistic and pessimistic decision makers due to the integration of m λ -measure. The developed method is applied to the long-term planning of a domestic wastewater management system in the city of Kunming, China, with consideration of the eco-environmental protection of downstream water body. The solution results of the GIFCP method can generate a series of optimal wastewater allocation patterns and WTPs capacity expansion schemes under different risk levels, provide in-depth insights into the effects of uncertainties, and consider the proper balance between system cost and risk of constraint violation.

Effect of position of near addition in an asymmetric refractive multifocal intraocular lens on quality of vision

To evaluate the impact of the position of an asymmetric multifocal near segment on visual quality. Cathedral Eye Clinic, Belfast, United Kingdom. Retrospective comparative case series. Data from consecutive patients who had bilateral implantation of the Lentis Mplus LS-312 multifocal intraocular lens were divided into 2 groups. One group received inferonasal near-segment placement and the other, superotemporal near-segment placement. A +3.00 diopter (D) reading addition (add) was used in all eyes. The main outcome measures included uncorrected distance visual acuity (UDVA), uncorrected near visual acuity (UNVA), contrast sensitivity, and quality of vision. Follow-up was 3 months. Patients ranged in age from 43 to 76 years. The inferonasal group comprised 80 eyes (40 patients) and the superotemporal group, 76 eyes (38 patients). The mean 3-month spherical equivalent was -0.11 D ± 0.49 (SD) in the inferonasal group and -0.18 ± 0.46 D in the superotemporal group. The mean postoperative UDVA was 0.14 ± 0.10 logMAR and 0.18 ± 0.15 logMAR, respectively. The mean monocular UNVA was 0.21 ± 0.14 logRAD and 0.24 ± 0.13 logRAD, respectively. No significant differences were observed in the higher-order aberrations, total Strehl ratio (point-spread function), or modulation transfer function between the groups. Dysphotopic symptoms measured with a validated quality-of-vision questionnaire were not significantly different between groups. Positioning of the near add did not significantly affect objective or subjective visual function parameters.

Skin lesion tracking using structured graphical models.

An automatic pigmented skin lesions tracking system, which is important for early skin cancer detection, is proposed in this work. The input to the system is a pair of skin back images of the same subject captured at different times. The output is the correspondence (matching) between the detected lesions and the identification of newly appearing and disappearing ones. First, a set of anatomical landmarks are detected using a pictorial structure algorithm. The lesions that are located within the polygon defined by the landmarks are identified and their anatomical spatial contexts are encoded by the landmarks. Then, these lesions are matched by labeling an association graph using a tensor-based algorithm. A structured support vector machine is employed to learn all free parameters in the aforementioned steps. An adaptive learning approach (on-the-fly vs offline learning) is applied to set the parameters of the matching objective function using the estimated error of the detected landmarks. The effectiveness of the different steps in our framework is validated on 194 skin back images (97 pairs).

A New Method For Solving Fuzzy Linear Programming Problems Based on The Fuzzy Linear Complementary Problem (FLCP)

Linear programming (LP) is one of the most widely used methods in the area of optimization. Dealing with the formulation of LP problems, the parameters of objective function and constraints should be assigned by experts. In most cases, precise data have been used, but in most of the real-life situations, these parameters are imprecise and ambiguous. In order to deal with the problem of ambiguity and imprecision, fuzzy numbers can be appropriate. By replacing precise numbers with fuzzy numbers, LP problems change to fuzzy linear programming (FLP) problems. So FLPs can be considered as a broader category in comparison to LPs. Considering the above-mentioned points, FLP problems play an important rule in operational researches hence there is a need to investigate these problems. In this paper, a new method for solving the FLP problems is presented in which the coefficients of the objective function and the values of the right-hand side are represented by fuzzy numbers, while the elements of the coefficient matrix are represented by real numbers. To this end, we develop the Karush–Kuhn–Tucker (KKT) optimality conditions for FLP problems. Then, every FLP problem is converted to a fuzzy linear complementary problem (FLCP) by considering KKT conditions. In order to solve the FLCP problems, ranking functions and Lemke’s algorithm are used. Consequently, the solution to primal and dual problems of FLP is obtained. In addition to simplicity in calculations and feasibility, this method solves the primal and dual problems of FLP simultaneously. In order to illustrate the proposed method, some numerical examples are considered.

Long-term results of ORIF of condylar head fractures of the mandible: A prospective 5-year follow-up study of small-fragment positional-screw osteosynthesis (SFPSO)

BackgroundOptimum treatment of condylar head fractures (CHF) remains subject to controversy. There are currently a variety of alternative techniques applied, data in literature are often inconsistent and especially systematic long-term data on results after treatment by open reduction and internal fixation (ORIF) have so far not been available. This study in hand is the first long-term prospective study of ORIF after CHF based on osteosynthesis with 1.7 mm small-fragment positional screws (SFPSO)via a retroauricular transmeatal approach (RA). MethodsThe study made use of radiologic, anatomic and objective functional parameters (axiography and MRI) to assess vertical height, disk mobility, protrusive and translatory movement as well as potential physical complaints. Included were surgical long-term sequelae after RA, such as incidence of stenosis of the auditory canal, the facial nerve and resulting disturbance of facial skin sensitivity. Retroauricular scars were evaluated according to the Vancouver Scar Scale. Helkimo and RDC/TMD indices were applied for patient's self-assessment of quality of life aspects after ORIF via RA.The sample in the first follow-up trial (FFT) in the years 2003–2004 comprised 26 patients (36 CHF). 22 patients (31 CHF) were re-evaluated in a second follow-up trial (SFT) between 2006 and 2008. A reference collective (43 patients, 56 CHF) treated with ORIF from 1993 to 2000 mainly by mini- or microplates (MMP) served as a surgical control group. ResultsFive years after ORIF all fractured condyles (FC) continued to show stable anatomic restoration of the pre-trauma vertical height. FC treated with SFPSO exhibited a significantly superior range of motion (p < 0.05) of disk and condyle during mouth opening and protrusion compared to a previous MMP reference collective. Also, no difference was found between condylar mobility of FC five years after surgery and non-fractured condyles (NFC). SFPSO had thus successfully achieved a sustainable, stable physiological restoration of protrusive mobility of the articular disk and condyle. Remarkably, these long-term results were even slightly better in SFT vs. FFT (p < 0.05). Except for sporadically occurring minor complaints, the patients' subjective overall long-term perception of the success of the treatment was equally positive to the surgeons' objective assessment. ConclusionsThis first long-term prospective follow-up study, based on objective assessment tools, demonstrates that in all cases the major goals of ORIF in CHF could be fully achieved. These goals are: restoration of vertical height viz. prevention of occlusal disorders, physiological function of disk and condyle as well as of the lateral pterygoid muscle. Accordingly, ORIF of CHF e.g. with SFPSO and via the RA secures both a long-term functionally and anatomically stable result and as best as possible pain-free result for the patient, a central prerequisite of optimum perceived HRQoL. The paper has been amended by an extensive review part that covers the current knowledge of the major surgical aspects regarding the treatment of condylar head fractures.

A robust method to adapt the working team commensurate with the distribution of limited resources in project-based organisations

Team building and tasks assignment according to restrictions of each project is one of the most important parts of each project. Project-orientated organisations usually face the problem of adapting team members commensurate with the works bulk, structure and other involved factors. This problem is usually resolved by project managers based upon their experience. Considering great dimensions of the problem, it is not feasible to appraise the probable distribution modes and selection of the best working team as a result. In this paper, a conforming coordinate method is suggested to adapt the members of the working team commensurate with the distribution of confined resources in the project. The proposed algorithms create a feedback loop in a way that the decision-maker has the feasibility to adapt his/her parameters of objective functions constantly. A case study is presented and analysed with the method. Results show the feasibility and proper function of the method.

Fluctuation-Model-Based Discrete Probability Estimation for Small Samples

A robust method is proposed for estimating discrete probability functions for small samples. The proposed approach introduces and minimizes a parameterized objective function that is analogous to free energy functions in statistical physics. A key feature of the method is a model of the parameter that controls the trade-off between likelihood and robustness in response to the degree of fluctuation. The method thus does not require the value of the parameter to be manually selected. It is proved that the estimator approaches the maximum likelihood estimator at the asymptotic limit. The effectiveness of the method in terms of robustness is demonstrated by experimental studies on point estimation for probability distributions with various entropies.

A review of foundational methods for checking the structural identifiability of models: Results for rainfall-runoff

Checking for model identifiability has several advantages as outlined in the paper. We illustrate the use of several screening methods for assessing structural identifiability that should serve as a valuable precursor to model redesign and more sophisticated uncertainty analyses. These are: global evolutionary optimisation algorithms (EAs) that are being used increasingly to estimate parameters of models because of their flexibility; one and two-dimensional discrete model response plots with the latter showing trajectories of convergence/non-convergence; quadratic response surface approximations; and sensitivity analysis of combinations of parameters using Polynomial Chaos Expansion model emulation. Each method has a role to play in understanding the nature of non-identifiability. We illustrate the utility and complementary value of these methods for conceptual rainfall-runoff processes with real and ‘exact’ daily flow data, hydrological models of increasing complexity, and different objective functions. We conclude that errors in data are not primarily the cause of the parameter identification problem and objective function selection gives only a partial solution. Model structure reveals itself to be a major problem for the two more complex models examined, as characterised by the dotty/1D, 2D projection and eigen plots. The Polynomial Chaos Expansion method helps reveal which interactions between parameters could affect the model identifiability. Structural non-identifiability is seen to pervade even at modest levels of model complexity.

Optimal strategies for carbon capture, utilization and storage based on an inexact mλ-measure fuzzy chance-constrained programming

In this study, IMP (interval mathematical programming), mλ-measure, and fuzzy chance-constrained programming are incorporated into a general optimization framework, leading to an IMFCP (interval-parameter mλ-measure based fuzzy chance-constrained programming) method. The IMFCP method can be used to deal with not only interval uncertainties in the objective function, variables and left-hand side parameters, but also fuzzy uncertainties in the right-hand side. mλ-measure, which has the advantage of self-dual and can reflect the aspiration preference of decision makers, is used to describe the failure risk of fuzzy chance constrains. As a more generalized approach compared with credibility constrained programming, IMFCP can reflect the balance between optimism and pessimism. The developed method is applied to the long-term planning of CCUS (carbon capture, utilization and storage) management system. The results of IMFCP method can generate a series of CCUS management patterns under different risk levels, gain in-depth insights into the effects of uncertainties, and consider a proper balance between system costs and risks of constraint violation.

Shilling attack detection algorithm based on Genetic optimization

Aiming at the low limitation of shilling attack detection technology unsupervised degree, this paper takes the group effect attack profile as the breakthrough point to construct the attack profile groups and the corresponding genetic optimization objective function of quantitative measure of the effects, and prove that the maximum value of the objective function in the ideal state marks the optimum detection effects in ideal situation. On this basis, the combination of genetic optimization process will be adaptive parameter posterior inference and objective function, and proposes the Iterative Bayesian Inference Genetic Detection Algorithm (IBIGDA).Experimental results show that IBIGDA can effectively detect shilling attacks of typical types even in lack of the system or attack-related prior parameters. IBIGDA algorithm can detect common shilling attack, unsupervised degree is high, with the actual application requirements.

Computational finite element model updating tool for modal testing of structures

In this paper, the development of a new optimization software for finite element model updating of engineering structures titled as FemUP is described. The program is used for computational FEM model updating of structures depending on modal testing results. This paper deals with the FE model updating procedure carried out in FemUP. The theoretical exposition on FE model updating and optimization techniques is presented. The related issues including the objective function, constraint function, different residuals and possible parameters for FE model updating are investigated. The issues of updating process adopted in FemUP are discussed. The ideas of optimization to be used in FE model updating application are explained. The algorithm of Sequential Quadratic Programming (SQP) is explored which will be used to solve the optimization problem. The possibilities of the program are demonstrated with a three dimensional steel frame model. As a result of this study, it can be said that SQP algorithm is very effective in model updating procedure.

Optimization in the Interval Uncertainty by Determination Method

Existing approaches to system optimization (optimal design) under uncertainty are considered. The exact formulation of constrained optimization problem with interval uncertainty of the objective function and constraints parameters is given. The mathematical theory of intervals comparison including the precise definition of minimum and maximum ranges is stated. On the basis of this theory, the determination method is formulated and justified which allows solving problems by reducing to a two fully certain constrained optimization problems of the same type. KeywordsOptimization; Uncertainty; Optimization with Interval Uncertainty; Determination Method

Постановка задачи оптимального проектирования стальных конструкций

The presented article considers the following complex of tasks. The main stages of the life cycle of a building construction with the indication of process entrance and process exit are described. Requirements imposed on steel constructions are considered. The optimum range of application for steel designs is specified, as well as merits and demerits of a design material. The nomenclature of metal designs is listed the block diagram is constructed. Possible optimality criteria of steel designs, offered by various authors for various types of constructions are considered. It is established that most often the criterion of a minimum of design mass is accepted as criterion of optimality; more rarely a minimum of the given expenses, a minimum of a design cost in business. In the present article special attention is paid to a type of objective function of optimization problem. It is also established that depending on the accepted optimality criterion, the use of different types of functions is possible. This complexity of objective function depends on completeness of optimality criterion application. In the work the authors consider the following objective functions: the mass of the main element of a design; objective function by criterion of factory cost; objective function by criterion of cost in business. According to these examples it can be seen that objective functions by the criteria of labor expenses for production of designs are generally non-linear, which complicates solving the optimization problem. Another important factor influencing the problem of optimal design solution for steel designs, which is analyzed, is account for operating restrictions. In the article 8 groups of restrictions are analyzed. Attempts to completely account for the parameters of objective function optimized by particular optimality criteria, taking into account all the operating restrictions, considerably complicates the problem of designing. For solving this task it can be offered to use informational technologies and opportunities of automated systems. For this purpose it is necessary to develop the automated system of steel designs, allowing to consider some criteria of optimality and a wide range of the restrictions for steel structural designs. This will allow to accelerate projection process, to reduce labor input of a designer and essentially increase the quality of design solutions for steel designs.

Energy-Efficient Power Allocation Using Probabilistic Interference Model for OFDM-Based Green Cognitive Radio Networks

We study the energy-efficient power allocation techniques for OFDM-based cognitive radio (CR) networks, where a CR transmitter is communicating with CR receivers on a channel borrowed from licensed primary users (PUs). Due to non-orthogonality of the transmitted signals in the adjacent bands, both the PU and the cognitive secondary user (SU) cause mutual-interference. We assume that the statistical channel state information between the cognitive transmitter and the primary receiver is known. The secondary transmitter maintains a specified statistical mutual-interference limits for all the PUs communicating in the adjacent channels. Our goal is to allocate subcarrier power for the SU so that the energy efficiency metric is optimized as well as the mutual-interference on all the active PU bands are below specified bounds. We show that the green power loading problem is a fractional programming problem. We use Charnes-Cooper transformation technique to obtain an equivalent concave optimization problem for what the solution can be readily obtained. We also propose iterative Dinkelbach method using parametric objective function for the fractional program. Numerical results are given to show the effect of different interference parameters, rate and power thresholds, and number of PUs.

Assessment of investment risk in implementing enterprise procurement plan

The problem of assessing the risk, arising from implementing the enterprise procurement plan is considered in the paper. The task of forming the procurement plan is reduced to solving a non-trivial problem of rational allocation of total investment between private investment projects, which together determine the selected procurement strategy.This problem is formulated as an optimization problem of mathematical programming with nonlinear separable objective function and linear constraints. The allocation efficiency criterion is profit, expected from implementing the procurement plan.The real difficulty in solving this problem is that the parameters of the objective function are random variables. Therefore, for any allocation of investment funds, which satisfies the constraints, the allocation efficiency criterion value also becomes random. In this connection, there is a specific problem of estimating the uncertainty level of the result of funds allocation between investment projects and the risk of possible solutions.The problem is solved as follows. First, statistical estimation of probability-theoretic characteristics of the objective function parameters is performed. Furthermore, by expanding the target function in a series, its linearization is made. After that, the calculation of the mathematical expectation and variance of a random value of the criterion is conducted that allows to determine interval estimates of the expected value of the profit, expected from implementing the selected procurement plan.It is clear that the obtained plan efficiency estimates are more informative than point and can be used when selecting the rational investment plan

A robust optimization approach to diet problem with overall glycemic load as objective function

The main purpose of the paper is to introduce a mixed-integer programming model for the diet problem with glycemic load (GL) values of foods as objective function parameters. It is assumed that the glycemic load values are subject to uncertainty. The diet problem with minimum cost function is well-known in the literature. However, the diet problem with minimum total daily GL values of foods that satisfies the daily nutritional and serving size requirements has not been proposed. Robust optimization approach is used to account for uncertainty in the GL values of foods. The decision maker is flexible to tune the degree of uncertainty rather than assuming a worst-case scenario. An experimental analysis with a total of 177 foods is performed based on the nutritional and serving size requirements and the basic food groups recommended by the U.S. Department of Health and Human Services & U.S. Department of Agriculture (USDA). The results of the experimental analysis with different scenarios give different solutions for different degrees of uncertainty. However, some foods are frequently found to be in the optimum solutions. These foods are in good agreement with the literature advising them as a part of a daily diet for attaining low level of blood glucose levels. Although we believe that the proposed diet problem with minimum total GL has contributions for satisfying the daily nutritional and serving size requirements with a minimum level of effect on blood glucose levels, it has several limitations. It is a basic diet problem, and assumes that the overall GL is a linear combination of number of serving sizes with the GL values of foods. It also does not consider any other factors such as several combinations of foods and their varying effects on blood glucose levels. These factors should be considered for the next research.