International Nuclear Information System (INIS)
Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao
2014-01-01
Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP. (paper)
Strategy Instruction in Mathematics.
Goldman, Susan R.
1989-01-01
Experiments in strategy instruction for mathematics have been conducted using three models (direct instruction, self-instruction, and guided learning) applied to the tasks of computation and word problem solving. Results have implications for effective strategy instruction for learning disabled students. It is recommended that strategy instruction…
Miller, Steven J
2017-01-01
Optimization Theory is an active area of research with numerous applications; many of the books are designed for engineering classes, and thus have an emphasis on problems from such fields. Covering much of the same material, there is less emphasis on coding and detailed applications as the intended audience is more mathematical. There are still several important problems discussed (especially scheduling problems), but there is more emphasis on theory and less on the nuts and bolts of coding. A constant theme of the text is the "why" and the "how" in the subject. Why are we able to do a calculation efficiently? How should we look at a problem? Extensive effort is made to motivate the mathematics and isolate how one can apply ideas/perspectives to a variety of problems. As many of the key algorithms in the subject require too much time or detail to analyze in a first course (such as the run-time of the Simplex Algorithm), there are numerous comparisons to simpler algorithms which students have either seen or c...
Some topics in mathematical finance: Asian basket option pricing, Optimal investment strategies
Diallo, Ibrahima
2010-01-01
This thesis presents the main results of my research in the field of computational finance and portfolios optimization. We focus on pricing Asian basket options and portfolio problems in the presence of inflation with stochastic interest rates.In Chapter 2, we concentrate upon the derivation of bounds for European-style discrete arithmetic Asian basket options in a Black and Scholes framework.We start from methods used for basket options and Asian options. First, we use the general approach f...
Methods of mathematical optimization
Vanderplaats, G. N.
The fundamental principles of numerical optimization methods are reviewed, with an emphasis on potential engineering applications. The basic optimization process is described; unconstrained and constrained minimization problems are defined; a general approach to the design of optimization software programs is outlined; and drawings and diagrams are shown for examples involving (1) the conceptual design of an aircraft, (2) the aerodynamic optimization of an airfoil, (3) the design of an automotive-engine connecting rod, and (4) the optimization of a 'ski-jump' to assist aircraft in taking off from a very short ship deck.
International Nuclear Information System (INIS)
Chen, C.Y.; Shih, L.H.
1992-01-01
Recently, the main power company in Taiwan has shifted the primary energy resource from oil to coal and tried to diversify the coal supply from various sources. The company wants to have the imported coal meet the environmental standards and operation requirements as well as to have high heating value. In order to achieve these objectives, establishment of a coal blending system for Taiwan is necessary. A mathematical model using mixed integer programming technique is used to model the import strategy and the blending system. 6 refs., 1 tab
Optimal GENCO bidding strategy
Gao, Feng
Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed
Optimal intermittent search strategies
International Nuclear Information System (INIS)
Rojo, F; Budde, C E; Wio, H S
2009-01-01
We study the search kinetics of a single fixed target by a set of searchers performing an intermittent random walk, jumping between different internal states. Exploiting concepts of multi-state and continuous-time random walks we have calculated the survival probability of a target up to time t, and have 'optimized' (minimized) it with regard to the transition probability among internal states. Our model shows that intermittent strategies always improve target detection, even for simple diffusion states of motion
Modelling and Optimizing Mathematics Learning in Children
Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus
2013-01-01
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Stochastic optimization: beyond mathematical programming
CERN. Geneva
2015-01-01
Stochastic optimization, among which bio-inspired algorithms, is gaining momentum in areas where more classical optimization algorithms fail to deliver satisfactory results, or simply cannot be directly applied. This presentation will introduce baseline stochastic optimization algorithms, and illustrate their efficiency in different domains, from continuous non-convex problems to combinatorial optimization problem, to problems for which a non-parametric formulation can help exploring unforeseen possible solution spaces.
Optimal fuel inventory strategies
International Nuclear Information System (INIS)
Caspary, P.J.; Hollibaugh, J.B.; Licklider, P.L.; Patel, K.P.
1990-01-01
In an effort to maintain their competitive edge, most utilities are reevaluating many of their conventional practices and policies in an effort to further minimize customer revenue requirements without sacrificing system reliability. Over the past several years, Illinois Power has been rethinking its traditional fuel inventory strategies, recognizing that coal supplies are competitive and plentiful and that carrying charges on inventory are expensive. To help the Company achieve one of its strategic corporate goals, an optimal fuel inventory study was performed for its five major coal-fired generating stations. The purpose of this paper is to briefly describe Illinois Power's system and past practices concerning coal inventories, highlight the analytical process behind the optimal fuel inventory study, and discuss some of the recent experiences affecting coal deliveries and economic dispatch
Optimal intermittent search strategies
Energy Technology Data Exchange (ETDEWEB)
Rojo, F; Budde, C E [FaMAF, Universidad Nacional de Cordoba, Ciudad Universitaria, X5000HUA Cordoba (Argentina); Wio, H S [Instituto de Fisica de Cantabria, Universidad de Cantabria and CSIC E-39005 Santander (Spain)
2009-03-27
We study the search kinetics of a single fixed target by a set of searchers performing an intermittent random walk, jumping between different internal states. Exploiting concepts of multi-state and continuous-time random walks we have calculated the survival probability of a target up to time t, and have 'optimized' (minimized) it with regard to the transition probability among internal states. Our model shows that intermittent strategies always improve target detection, even for simple diffusion states of motion.
Mathematical modeling and optimization of complex structures
Repin, Sergey; Tuovinen, Tero
2016-01-01
This volume contains selected papers in three closely related areas: mathematical modeling in mechanics, numerical analysis, and optimization methods. The papers are based upon talks presented on the International Conference for Mathematical Modeling and Optimization in Mechanics, held in Jyväskylä, Finland, March 6-7, 2014 dedicated to Prof. N. Banichuk on the occasion of his 70th birthday. The articles are written by well-known scientists working in computational mechanics and in optimization of complicated technical models. Also, the volume contains papers discussing the historical development, the state of the art, new ideas, and open problems arising in modern continuum mechanics and applied optimization problems. Several papers are concerned with mathematical problems in numerical analysis, which are also closely related to important mechanical models. The main topics treated include: * Computer simulation methods in mechanics, physics, and biology; * Variational problems and methods; minimiz...
Practical mathematical optimization basic optimization theory and gradient-based algorithms
Snyman, Jan A
2018-01-01
This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are presented with emphasis on gradient-based numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradient-based methods. This second edition addresses further advancements of gradient-only optimization strategies to handle discontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies and numerical optimization using Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and dir...
Optimization and mathematical modeling in computer architecture
Sankaralingam, Karu; Nowatzki, Tony
2013-01-01
In this book we give an overview of modeling techniques used to describe computer systems to mathematical optimization tools. We give a brief introduction to various classes of mathematical optimization frameworks with special focus on mixed integer linear programming which provides a good balance between solver time and expressiveness. We present four detailed case studies -- instruction set customization, data center resource management, spatial architecture scheduling, and resource allocation in tiled architectures -- showing how MILP can be used and quantifying by how much it outperforms t
Mathematical model of highways network optimization
Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.
2017-12-01
The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.
Implementing optimal thinning strategies
Kurt H. Riitters; J. Douglas Brodie
1984-01-01
Optimal thinning regimes for achieving several management objectives were derived from two stand-growth simulators by dynamic programming. Residual mean tree volumes were then plotted against stand density management diagrams. The results supported the use of density management diagrams for comparing, checking, and implementing the results of optimization analyses....
The mathematics of games of strategy
Dresher, Melvin
1981-01-01
A noted research mathematician explores decision making in the absence of perfect information. His clear presentation of the mathematical theory of games of strategy encompasses applications to many fields, including economics, military, business, and operations research. No advanced algebra or non-elementary calculus occurs in most of the proofs.
Optimizing decommissioning strategies
International Nuclear Information System (INIS)
Passant, F.H.
1993-01-01
Many different approaches can be considered for achieving satisfactory decommissioning of nuclear installations. These can embrace several different engineering actions at several stages, with time variations between the stages. Multi-attribute analysis can be used to help in the decision making process and to establish the optimum strategy. It has been used in the Usa and the UK to help in selecting preferred sites for radioactive waste repositories, and also in UK to help with the choice of preferred sites for locating PWR stations, and in selecting optimum decommissioning strategies
Switching strategies to optimize search
International Nuclear Information System (INIS)
Shlesinger, Michael F
2016-01-01
Search strategies are explored when the search time is fixed, success is probabilistic and the estimate for success can diminish with time if there is not a successful result. Under the time constraint the problem is to find the optimal time to switch a search strategy or search location. Several variables are taken into account, including cost, gain, rate of success if a target is present and the probability that a target is present. (paper: interdisciplinary statistical mechanics)
Optimal Strategy and Business Models
DEFF Research Database (Denmark)
Johnson, Peter; Foss, Nicolai Juul
2016-01-01
This study picks up on earlier suggestions that control theory may further the study of strategy. Strategy can be formally interpreted as an idealized path optimizing heterogeneous resource deployment to produce maximum financial gain. Using standard matrix methods to describe the firm Hamiltonia...... variable of firm path, suggesting in turn that the firm's business model is the codification of the application of investment resources used to control the strategic path of value realization....
Existence and characterization of optimal control in mathematics model of diabetics population
Permatasari, A. H.; Tjahjana, R. H.; Udjiani, T.
2018-03-01
Diabetes is a chronic disease with a huge burden affecting individuals and the whole society. In this paper, we constructed the optimal control mathematical model by applying a strategy to control the development of diabetic population. The constructed mathematical model considers the dynamics of disabled people due to diabetes. Moreover, an optimal control approach is proposed in order to reduce the burden of pre-diabetes. Implementation of control is done by preventing the pre-diabetes develop into diabetics with and without complications. The existence of optimal control and characterization of optimal control is discussed in this paper. Optimal control is characterized by applying the Pontryagin minimum principle. The results indicate that there is an optimal control in optimization problem in mathematics model of diabetic population. The effect of the optimal control variable (prevention) is strongly affected by the number of healthy people.
Rabab'h, Belal; Veloo, Arsaythamby
2015-01-01
Jordanian 8th grade students revealed low achievement in mathematics through four periods (1999, 2003, 2007 & 2011) of Trends in International Mathematics and Science Study (TIMSS). This study aimed to determine whether spatial visualization mediates the affect of Mathematics Learning Strategies (MLS) factors namely mathematics attitude,…
Numerical methods of mathematical optimization with Algol and Fortran programs
Künzi, Hans P; Zehnder, C A; Rheinboldt, Werner
1971-01-01
Numerical Methods of Mathematical Optimization: With ALGOL and FORTRAN Programs reviews the theory and the practical application of the numerical methods of mathematical optimization. An ALGOL and a FORTRAN program was developed for each one of the algorithms described in the theoretical section. This should result in easy access to the application of the different optimization methods.Comprised of four chapters, this volume begins with a discussion on the theory of linear and nonlinear optimization, with the main stress on an easily understood, mathematically precise presentation. In addition
Strategies to Support Students' Mathematical Modeling
Jung, Hyunyi
2015-01-01
An important question for mathematics teachers is this: "How can we help students learn mathematics to solve everyday problems, rather than teaching them only to memorize rules and practice mathematical procedures?" Teaching students using modeling activities can help them learn mathematics in real-world problem-solving situations that…
Lin, Su-Wei; Tai, Wen-Chun
2015-01-01
This study investigated how various mathematics learning strategies affect the mathematical literacy of students. The data for this study were obtained from the 2012 Programme for International Student Assessment (PISA) data of Taiwan. The PISA learning strategy survey contains three types of learning strategies: elaboration, control, and…
Comparison of mathematical problem solving strategies of primary school pupils
Wasilewská, Eliška
2016-01-01
The aim of this dissertation is to describe the role of educational strategy especially in field of the teaching of mathematics and to compare the mathematical problem solving strategies of primary school pupils which are taught by using different educational strategies. In the theoretical part, the main focus is on divergent educational strategies and their characteristics, next on factors affected teaching/learning process and finally on solving the problems. The empirical part of the disse...
Lobato, Fran Sérgio
2017-01-01
This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.
Evolution strategies for robust optimization
Kruisselbrink, Johannes Willem
2012-01-01
Real-world (black-box) optimization problems often involve various types of uncertainties and noise emerging in different parts of the optimization problem. When this is not accounted for, optimization may fail or may yield solutions that are optimal in the classical strict notion of optimality, but
Optlang: An algebraic modeling language for mathematical optimization
DEFF Research Database (Denmark)
Jensen, Kristian; Cardoso, Joao; Sonnenschein, Nikolaus
2016-01-01
Optlang is a Python package implementing a modeling language for solving mathematical optimization problems, i.e., maximizing or minimizing an objective function over a set of variables subject to a number of constraints. It provides a common native Python interface to a series of optimization...
A Mathematical Optimization Problem in Bioinformatics
Heyer, Laurie J.
2008-01-01
This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…
Concept mapping learning strategy to enhance students' mathematical connection ability
Hafiz, M.; Kadir, Fatra, Maifalinda
2017-05-01
The concept mapping learning strategy in teaching and learning mathematics has been investigated by numerous researchers. However, there are still less researchers who have scrutinized about the roles of map concept which is connected to the mathematical connection ability. Being well understood on map concept, it may help students to have ability to correlate one concept to other concept in order that the student can solve mathematical problems faced. The objective of this research was to describe the student's mathematical connection ability and to analyze the effect of using concept mapping learning strategy to the students' mathematical connection ability. This research was conducted at senior high school in Jakarta. The method used a quasi-experimental with randomized control group design with the total number was 72 students as the sample. Data obtained through using test in the post-test after giving the treatment. The results of the research are: 1) Students' mathematical connection ability has reached the good enough level category; 2) Students' mathematical connection ability who had taught with concept mapping learning strategy is higher than who had taught with conventional learning strategy. Based on the results above, it can be concluded that concept mapping learning strategycould enhance the students' mathematical connection ability, especially in trigonometry.
Comparison of Mathematics and Humanitarian Sciences Students’ Metacognitive Strategies
Directory of Open Access Journals (Sweden)
Gholam Hossein Javanmard
2014-09-01
Full Text Available Abstract The purpose of this study was to compare the differences of using meta-cognitive strategies in high school students who study in the fields of mathematics and humanities. For do this, 140 high school students were selected randomly. The Swanson’s Meta-cognition Strategies Test was administrated for sample groups. The acquired means for two regroups were compared with t-test for two independent groups’ method. Results indicated that two groups were meaningfully differed from each other (sig=0.01 in using meta-cognitive strategies, and mean of students in mathematics field were high. Also there was a meaningful difference in task component between two groups (sig=0.002, and the mean of students in mathematics field was higher than from students in humanities field in this component. The high school students in mathematics field use more metacognitive strategies, especially task component, than the students in humanities field.
Math in plain english literacy strategies for the mathematics classroom
Benjamin, Amy
2013-01-01
Do word problems and math vocabulary confuse students in your mathematics classes? Do simple keywords like ""value"" and ""portion"" seem to mislead them? Many words that students already know can have a different meaning in mathematics. To grasp that difference, students need to connect English literacy skills to math. Successful students speak, read, write, and listen to each other so they can understand, retain, and apply mathematics concepts. This book explains how to use 10 classroom-ready literacy strategies in concert with your mathematics instruction. You'll learn how to develop stude
Active Learning Strategies for the Mathematics Classroom
Kerrigan, John
2018-01-01
Active learning involves students engaging with course content beyond lecture: through writing, applets, simulations, games, and more (Prince, 2004). As mathematics is often viewed as a subject area that is taught using more traditional methods (Goldsmith & Mark, 1999), there are actually many simple ways to make undergraduate mathematics…
Determining an optimal supply chain strategy
Directory of Open Access Journals (Sweden)
Intaher M. Ambe
2012-11-01
Full Text Available In today’s business environment, many companies want to become efficient and flexible, but have struggled, in part, because they have not been able to formulate optimal supply chain strategies. Often this is as a result of insufficient knowledge about the costs involved in maintaining supply chains and the impact of the supply chain on their operations. Hence, these companies find it difficult to manufacture at a competitive cost and respond quickly and reliably to market demand. Mismatched strategies are the root cause of the problems that plague supply chains, and supply-chain strategies based on a one-size-fits-all strategy often fail. The purpose of this article is to suggest instruments to determine an optimal supply chain strategy. This article, which is conceptual in nature, provides a review of current supply chain strategies and suggests a framework for determining an optimal strategy.
Optimal inspection strategies for offshore structural systems
DEFF Research Database (Denmark)
Faber, M. H.; Sorensen, J. D.; Kroon, I. B.
1992-01-01
a mathematical framework for the estimation of the failure and repair costs a.ssociated with systems failure. Further a strategy for selecting the components to inspect based on decision tree analysis is suggested. Methods and analysis schemes are illustrated by a simple example....
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
MODERN OR TRADITIONAL TEACHING STRATEGY IN LEARNING ENGINEERING MATHEMATICS COURSE
Directory of Open Access Journals (Sweden)
N. RAZALI
2016-11-01
Full Text Available First-year engineering students of the Faculty of Engineering and Built Environment, UKM are in the process of transition in the way they learn mathematics from pre-university level to the undergraduate level. It is essential for good engineers to have the ability to unfold mathematical problems in an efficient way. Thus, this research is done to investigate students preference in learning KKKQ1123 Engineering Mathematics I (Vector Calculus (VC course; either individually or in a team; using modern (e-learning or traditional (cooperative-learning teaching strategy. Questionnaires are given to the first year Chemical and Process Engineering students from academic year 2015/2016 and the results were analysed. Based on the finding, the students believed that the physical educators or teachers play an important role and that they have slightest preference in the traditional teaching strategy to learn engineering mathematics course.
Mathematical programming methods for large-scale topology optimization problems
DEFF Research Database (Denmark)
Rojas Labanda, Susana
for mechanical problems, but has rapidly extended to many other disciplines, such as fluid dynamics and biomechanical problems. However, the novelty and improvements of optimization methods has been very limited. It is, indeed, necessary to develop of new optimization methods to improve the final designs......, and at the same time, reduce the number of function evaluations. Nonlinear optimization methods, such as sequential quadratic programming and interior point solvers, have almost not been embraced by the topology optimization community. Thus, this work is focused on the introduction of this kind of second...... for the classical minimum compliance problem. Two of the state-of-the-art optimization algorithms are investigated and implemented for this structural topology optimization problem. A Sequential Quadratic Programming (TopSQP) and an interior point method (TopIP) are developed exploiting the specific mathematical...
An optimal inspection strategy for randomly failing equipment
International Nuclear Information System (INIS)
Chelbi, Anis; Ait-Kadi, Daoud
1999-01-01
This paper addresses the problem of generating optimal inspection strategies for randomly failing equipment where imminent failure is not obvious and can only be detected through inspection. Inspections are carried out following a condition-based procedure. The equipment is replaced if it has failed or if it shows imminent signs of failure. The latter state is indicated by measuring certain predetermined control parameters during inspection. Costs are associated with inspection, idle time and preventive or corrective actions. An optimal inspection strategy is defined as the inspection sequence minimizing the expected total cost per time unit over an infinite span. A mathematical model and a numerical algorithm are developed to generate an optimal inspection sequence. As a practical example, the model is applied to provide a machine tool operator with a time sequence for inspecting the cutting tool. The tool life time distribution and the trend of one control parameter defining its actual condition are supposed to be known
Optimization strategies in complex systems
Bussolari, L.; Contucci, P.; Giardinà, C.; Giberti, C.; Unguendoli, F.; Vernia, C.
2003-01-01
We consider a class of combinatorial optimization problems that emerge in a variety of domains among which: condensed matter physics, theory of financial risks, error correcting codes in information transmissions, molecular and protein conformation, image restoration. We show the performances of two
The Strategies of Mathematics Teachers When Solving Number Sense Problems
Directory of Open Access Journals (Sweden)
Sare Şengül
2014-04-01
Full Text Available Number sense involves efficient strategies and the ability to think flexibly with numbers and number operations and flexible thinking ability and the inclination getting for making sound mathematical judgements. The aim of this study was to investigate the strategies used by mathematics teachers while solving number sense problems. Eleven mathematics teachers from a graduate program in education were the participants. A number sense test which has a total of 12 problems is used as the data gathering tool. Teachers’ responses and strategies were analyzed both qualitatively and quantitatively.First, participants’ responses were evaluated for correctness. Then the strategies teachers used were analyzed. The strategies were categorized as based on the use of number sense or rule based strategies. When the correct and incorrect responses were considered together, in the 46% of the responses number sense strategies were used and in 54% the rule-based strategies were used. The results of this study showed that even though teachers can use number sense strategies at some level, there is still room for development in teachers’ number sense.
Transitions in optimal adaptive strategies for populations in fluctuating environments
Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.
2017-09-01
Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.
Optimal Advance Selling Strategy under Price Commitment
Chenhang Zeng
2012-01-01
This paper considers a two-period model with experienced consumers and inexperienced consumers. The retailer determines both advance selling price and regular selling price at the beginning of the first period. I show that advance selling weekly dominates no advance selling, and the optimal advance selling price may be at a discount, at a premium or at the regular selling price. To help the retailer choose the optimal pricing strategy, conditions for each possible advance selling strategy to ...
Optimal Design of Gravity Pipeline Systems Using Genetic Algorithm and Mathematical Optimization
Directory of Open Access Journals (Sweden)
maryam rohani
2015-03-01
Full Text Available In recent years, the optimal design of pipeline systems has become increasingly important in the water industry. In this study, the two methods of genetic algorithm and mathematical optimization were employed for the optimal design of pipeline systems with the objective of avoiding the water hammer effect caused by valve closure. The problem of optimal design of a pipeline system is a constrained one which should be converted to an unconstrained optimization problem using an external penalty function approach in the mathematical programming method. The quality of the optimal solution greatly depends on the value of the penalty factor that is calculated by the iterative method during the optimization procedure such that the computational effort is simultaneously minimized. The results obtained were used to compare the GA and mathematical optimization methods employed to determine their efficiency and capabilities for the problem under consideration. It was found that the mathematical optimization method exhibited a slightly better performance compared to the GA method.
DEFF Research Database (Denmark)
Fischetti, Martina; Fraccaro, Marco
2018-01-01
In this paper we propose a combination of Mathematical Optimization and Machine Learning to estimate the value of optimized solutions. In particular, we investigate if a machine, trained on a large number of optimized solutions, could accurately estimate the value of the optimized solution for new...... in production between optimized/non optimized solutions, it is not trivial to understand the potential value of a new site without running a complete optimization. This could be too time consuming if a lot of sites need to be evaluated, therefore we propose to use Machine Learning to quickly estimate...... the potential of new sites (i.e., to estimate the optimized production of a site without explicitly running the optimization). To do so, we trained and tested different Machine Learning models on a dataset of 3000+ optimized layouts found by the optimizer. Thanks to the close collaboration with a leading...
Directory of Open Access Journals (Sweden)
Aweke Shishigu
2018-02-01
Full Text Available In the process of reaching a medium income country, science, mathematics and technology have become an emphasis of Ethiopia. But, currently, students' interest to study mathematics and ability in mathematics is declining. This study therefore aimed to investigate the prevalence of mathematics anxiety and its effect on students' current mathematics achievement. Additionally, by grounding on the literature, some strategies supposed to reduce the negative effects of math anxiety were identified for practice. The study was conducted on five randomly selected public secondary schools of East Shoa Zone in Oromia region. Math anxiety was measured using a validated instrument called Math Anxiety Rating Scale (MARS, whereas students' current mathematics achievement was measured using achievement test. Structural model was developed to examine causal relationship of the variables treated in the study. The finding revealed that there was a significant negative relationship between mathematics anxiety and achievement. There was also a statistically significant gender difference in mathematics anxiety and current math achievement, with effect size small and typical respectively. Based on the findings of the study, imperative implication for practice and future research were made.
Determining of the Optimal Device Lifetime using Mathematical Renewal Models
Directory of Open Access Journals (Sweden)
Knežo Dušan
2016-05-01
Full Text Available Paper deals with the operations and equipment of the machine in the process of organizing production. During operation machines require maintenance and repairs, while in case of failure or machine wears it is necessary to replace them with new ones. For the process of replacement of old machines with new ones the term renewal is used. Qualitative aspects of the renewal process observe renewal theory, which is mainly based on the theory of probability and mathematical statistics. Devices lifetimes are closely related to the renewal of the devices. Presented article is focused on mathematical deduction of mathematical renewal models and determining optimal lifetime of the devices from the aspect of expenditures on renewal process.
Tank Waste Remediation System optimized processing strategy
International Nuclear Information System (INIS)
Slaathaug, E.J.; Boldt, A.L.; Boomer, K.D.; Galbraith, J.D.; Leach, C.E.; Waldo, T.L.
1996-03-01
This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.
Optimal Design of Pumped Pipeline Systems Using Genetic Algorithm and Mathematical Optimization
Directory of Open Access Journals (Sweden)
Mohammadhadi Afshar
2007-12-01
Full Text Available In recent years, much attention has been paid to the optimal design of pipeline systems. In this study, the problem of pipeline system optimal design has been solved through genetic algorithm and mathematical optimization. Pipe diameters and their thicknesses are considered as decision variables to be designed in a manner that water column separation and excessive pressures are avoided in the event of pump failure. Capabilities of the genetic algorithm and the mathematical programming method are compared for the problem under consideration. For simulation of transient streams, explicit characteristic method is used in which devices such as pumps are defined as boundary conditions of the equations defining the hydraulic behavior of pipe segments. The problem of optimal design of pipeline systems is a constrained problem which is converted to an unconstrained optimization problem using an external penalty function approach. The efficiency of the proposed approaches is verified in one example and the results are presented.
Optimal Pricing Strategy in Marketing Research Consulting.
Chang, Chun-Hao; Lee, Chi-Wen Jevons
1994-01-01
This paper studies the optimal pricing scheme for a monopolistic marketing research consultant who sells high-cost proprietary marketing information to her oligopolistic clients in the manufacturing industry. In designing an optimal pricing strategy, the consultant needs to fully consider the behavior of her clients, the behavior of the existing and potential competitors to her clients, and the behavior of her clients' customers. The authors show how the environment uncertainty, the capabilit...
Optimal Deterministic Investment Strategies for Insurers
Directory of Open Access Journals (Sweden)
Ulrich Rieder
2013-11-01
Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.
Optimization strategies for complex engineering applications
Energy Technology Data Exchange (ETDEWEB)
Eldred, M.S.
1998-02-01
LDRD research activities have focused on increasing the robustness and efficiency of optimization studies for computationally complex engineering problems. Engineering applications can be characterized by extreme computational expense, lack of gradient information, discrete parameters, non-converging simulations, and nonsmooth, multimodal, and discontinuous response variations. Guided by these challenges, the LDRD research activities have developed application-specific techniques, fundamental optimization algorithms, multilevel hybrid and sequential approximate optimization strategies, parallel processing approaches, and automatic differentiation and adjoint augmentation methods. This report surveys these activities and summarizes the key findings and recommendations.
Mathematical model of the metal mould surface temperature optimization
Energy Technology Data Exchange (ETDEWEB)
Mlynek, Jaroslav, E-mail: jaroslav.mlynek@tul.cz; Knobloch, Roman, E-mail: roman.knobloch@tul.cz [Department of Mathematics, FP Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic); Srb, Radek, E-mail: radek.srb@tul.cz [Institute of Mechatronics and Computer Engineering Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic)
2015-11-30
The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article.
Mathematical model of the metal mould surface temperature optimization
International Nuclear Information System (INIS)
Mlynek, Jaroslav; Knobloch, Roman; Srb, Radek
2015-01-01
The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article
An optimization strategy for a biokinetic model of inhaled radionuclides
International Nuclear Information System (INIS)
Shyr, L.J.; Griffith, W.C.; Boecker, B.B.
1991-01-01
Models for material disposition and dosimetry involve predictions of the biokinetics of the material among compartments representing organs and tissues in the body. Because of a lack of human data for most toxicants, many of the basic data are derived by modeling the results obtained from studies using laboratory animals. Such a biomathematical model is usually developed by adjusting the model parameters to make the model predictions match the measured retention and excretion data visually. The fitting process can be very time-consuming for a complicated model, and visual model selections may be subjective and easily biased by the scale or the data used. Due to the development of computerized optimization methods, manual fitting could benefit from an automated process. However, for a complicated model, an automated process without an optimization strategy will not be efficient, and may not produce fruitful results. In this paper, procedures for, and implementation of, an optimization strategy for a complicated mathematical model is demonstrated by optimizing a biokinetic model for 144Ce in fused aluminosilicate particles inhaled by beagle dogs. The optimized results using SimuSolv were compared to manual fitting results obtained previously using the model simulation software GASP. Also, statistical criteria provided by SimuSolv, such as likelihood function values, were used to help or verify visual model selections
Strong profiling is not mathematically optimal for discovering rare malfeasors
Energy Technology Data Exchange (ETDEWEB)
Press, William H [Los Alamos National Laboratory
2008-01-01
In a large population of individuals labeled j = 1,2,...,N, governments attempt to find the rare malfeasor j = j, (terrorist, for example) by making use of priors p{sub j} that estimate the probability of individual j being a malfeasor. Societal resources for secondary random screening such as airport search or police investigation are concentrated against individuals with the largest priors. They may call this 'strong profiling' if the concentration is at least proportional to p{sub j} for the largest values. Strong profiling often results in higher probability, but otherwise innocent, individuals being repeatedly subjected to screening. They show here that, entirely apart from considerations of social policy, strong profiling is not mathematically optimal at finding malfeasors. Even if prior probabilities were accurate, their optimal use would be only as roughly the geometric mean between a strong profiling and a completely uniform sampling of the population.
Integrated testing strategies can be optimal for chemical risk classification.
Raseta, Marko; Pitchford, Jon; Cussens, James; Doe, John
2017-08-01
There is an urgent need to refine strategies for testing the safety of chemical compounds. This need arises both from the financial and ethical costs of animal tests, but also from the opportunities presented by new in-vitro and in-silico alternatives. Here we explore the mathematical theory underpinning the formulation of optimal testing strategies in toxicology. We show how the costs and imprecisions of the various tests, and the variability in exposures and responses of individuals, can be assembled rationally to form a Markov Decision Problem. We compute the corresponding optimal policies using well developed theory based on Dynamic Programming, thereby identifying and overcoming some methodological and logical inconsistencies which may exist in the current toxicological testing. By illustrating our methods for two simple but readily generalisable examples we show how so-called integrated testing strategies, where information of different precisions from different sources is combined and where different initial test outcomes lead to different sets of future tests, can arise naturally as optimal policies. Copyright © 2017 Elsevier Inc. All rights reserved.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
Students Thinking Process in Compiling Mathematical Proof with Semantics Strategy
Directory of Open Access Journals (Sweden)
Abdussakir Abdussakir
2015-03-01
Full Text Available Proses Berpikir Mahasiswa dalam Menyusun Bukti Matematis dengan Strategi Semantik Abstract: This study is aimed to reveal the thinking process in proof construction performed by students with semantic strategy. This study use descriptive-qualitative approach. The thinking process of students will be analyzed using theoretical framework of David Tall about the three worlds of mathematical thinking. The result are three ways of thinking in semantic strategy, namely (1 started from formal world then move into the symbolic or embodied-symbolic world with possibility of more than once and ends within or outside of the formal world, (2 started from symbolic world or embodied-symbolic world then move to the formal world with possibility of more than once and ends within or outside of the formal world, and (3 all thinking processes performed outside of formal world that does not obtain formal proof. Key Words: thinking process, mathematical proof, semantic strategy Abstrak: Penelitian ini bertujuan untuk menjelaskan proses berpikir mahasiswa dalam menyusun bukti matematis dengan strategi semantik. Penelitian ini menggunakan pendekatan deskiptif-kualitatif. Analisis data dilakukan dengan menggunakan kerangka kerja David Tall tentang tiga dunia berpikir matematik. Hasil penelitian menunjukkan bahwa terdapat enam kemungkinan jalur dalam strategi semantik ditinjau dari teori tiga dunia berpikir matematis. Hasil penelitian menunjukkan ada tiga jalur berpikir mahasiswa dalam menyusun bukti matematis dengan strategi semantik, yaitu (1 bermula dari dunia berpikir formal berpindah ke dunia berpikir wujud-simbolik atau dunia berpikir simbolik dengan proses perpindahan dimungkinkan lebih dari satu kali dan berakhir di dalam atau di luar dunia berpikir formal, (2 bermula dari dunia berpikir wujud simbolik atau dunia berpikir simbolik (non RSP lalu pindah ke dunia berpikir formal dengan proses perpindahan dimungkinkan lebih dari satu kali dan berakhir di
Parallel strategy for optimal learning in perceptrons
International Nuclear Information System (INIS)
Neirotti, J P
2010-01-01
We developed a parallel strategy for learning optimally specific realizable rules by perceptrons, in an online learning scenario. Our result is a generalization of the Caticha-Kinouchi (CK) algorithm developed for learning a perceptron with a synaptic vector drawn from a uniform distribution over the N-dimensional sphere, so called the typical case. Our method outperforms the CK algorithm in almost all possible situations, failing only in a denumerable set of cases. The algorithm is optimal in the sense that it saturates Bayesian bounds when it succeeds.
The Optimal Nash Equilibrium Strategies Under Competition
Institute of Scientific and Technical Information of China (English)
孟力; 王崇喜; 汪定伟; 张爱玲
2004-01-01
This paper presented a game theoretic model to study the competition for a single investment oppertunity under uncertainty. It models the hazard rate of investment as a function of competitors' trigger level. Under uncertainty and different information structure, the option and game theory was applied to researching the optimal Nash equilibrium strategies of one or more firm. By means of Matlab software, the paper simulates a real estate developing project example and illustrates how parameter affects investment strategies. The paper's work will contribute to the present investment practice in China.
Optimized Strategies for Detecting Extrasolar Space Weather
Hallinan, Gregg
2018-06-01
Fully understanding the implications of space weather for the young solar system, as well as the wider population of planet-hosting stars, requires remote sensing of space weather in other stellar systems. Solar coronal mass ejections can be accompanied by bright radio bursts at low frequencies (typically measurement of the magnetic field strength of the planet, informing on whether the atmosphere of the planet can survive the intense magnetic activity of its host star. However, both stellar and planetary radio emission are highly variable and optimal strategies for detection of these emissions requires the capability to monitor 1000s of nearby stellar/planetary systems simultaneously. I will discuss optimized strategies for both ground and space-based experiments to take advantage of the highly variable nature of the radio emissions powered by extrasolar space weather to enable detection of stellar CMEs and planetary magnetospheres.
Optimization of pocket machining strategy in HSM
Msaddek, El Bechir; Bouaziz, Zoubeir; Dessein, Gilles; Baili, Maher
2012-01-01
International audience; Our two major concerns, which should be taken into consideration as soon as we start the selecting the machining parameters, are the minimization of the machining time and the maintaining of the high-speed machining machine in good state. The manufacturing strategy is one of the parameters which practically influences the time of the different geometrical forms manufacturing, as well as the machine itself. In this article, we propose an optimization methodology of the ...
Optimal strategies for pricing general insurance
Emms, P.; Haberman, S.; Savoulli, I.
2006-01-01
Optimal premium pricing policies in a competitive insurance environment are investigated using approximation methods and simulation of sample paths. The market average premium is modelled as a diffusion process, with the premium as the control function and the maximization of the expected total utility of wealth, over a finite time horizon, as the objective. In order to simplify the optimisation problem, a linear utility function is considered and two particular premium strategies are adopted...
Mathematical game type optimization of powerful fast reactors
International Nuclear Information System (INIS)
Pavelesku, M.; Dumitresku, Kh.; Adam, S.
1975-01-01
To obtain maximum speed of putting into operation fast breeders it is recommended on the initial stage of putting into operation these reactors to apply lower power which needs less fission materials. That is why there is an attempt to find a configuration of a high-power reactor providing maximum power for minimum mass of fission material. This problem has a structure of the mathematical game with two partners of non-zero-order total and is solved by means of specific aids of theory of games. Optimal distribution of fission and breeding materials in a multizone reactor first is determined by solution of competitive game and then, on its base, by solution of the cooperation game. The second problem the solution for which is searched is developed from remark on the fact that a reactor with minimum coefficient of flux heterogenity has a configuration different from the reactor with power coefficient heterogenity. Maximum burn-up of fuel needs minimum heterogenity of the flux coefficient and the highest power level needs minimum coefficient of power heterogenity. That is why it is possible to put a problem of finding of the reactor configuration having both coefficients with minimum value. This problem has a structure of a mathematical game with two partners of non-zero-order total and is solved analogously giving optimal distribution of fuel from the new point of view. In the report is shown that both these solutions are independent which is a result of the aim put in the problem of optimization. (author)
Didactic strategies through authentic performances in the Mathematics teaching process
Directory of Open Access Journals (Sweden)
Enrique Diaz Chong
2016-09-01
Full Text Available The main objective of this article is gather a set of Mathematic didactic strategies by improving the academic performance and acquiring skills and abilities through authentic performances during the teaching process. The investigation is going to realize with students of the ﬁrst semester E and with a teacher of Commercial Studies career, applying the “learn to learn” method described in the fundaments since the application of the teaching strategy until the evaluation. Through this method, they acquire basic competence of the mentioned subject and the knowledge in order to use them as future professionals in any life circumstance. It will verify the obtained results by having a better motivation of the students and the discipline comprehension. It is important to highlight that those strategies could be applied in any other subject.
Optimization Under Uncertainty for Wake Steering Strategies
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-08-03
Offsetting turbines' yaw orientations from incoming wind is a powerful tool that may be leveraged to reduce undesirable wake effects on downstream turbines. First, we examine a simple two-turbine case to gain intuition as to how inflow direction uncertainty affects the optimal solution. The turbines are modeled with unidirectional inflow such that one turbine directly wakes the other, using ten rotor diameter spacing. We perform optimization under uncertainty (OUU) via a parameter sweep of the front turbine. The OUU solution generally prefers less steering. We then do this optimization for a 60-turbine wind farm with unidirectional inflow, varying the degree of inflow uncertainty and approaching this OUU problem by nesting a polynomial chaos expansion uncertainty quantification routine within an outer optimization. We examined how different levels of uncertainty in the inflow direction effect the ratio of the expected values of deterministic and OUU solutions for steering strategies in the large wind farm, assuming the directional uncertainty used to reach said OUU solution (this ratio is defined as the value of the stochastic solution or VSS).
Optimal and Robust Switching Control Strategies : Theory, and Applications in Traffic Management
Hajiahmadi, M.
2015-01-01
Macroscopic modeling, predictive and robust control and route guidance for large-scale freeway and urban traffic networks are the main focus of this thesis. In order to increase the efficiency of our control strategies, we propose several mathematical and optimization techniques. Moreover, in the
An Overview of Optimizing Strategies for Flotation Banks
Directory of Open Access Journals (Sweden)
Miguel Maldonado
2012-10-01
Full Text Available A flotation bank is a serial arrangement of cells. How to optimally operate a bank remains a challenge. This article reviews three reported strategies: air profiling, mass-pull (froth velocity profiling and Peak Air Recovery (PAR profiling. These are all ways of manipulating the recovery profile down a bank, which may be the property being exploited. Mathematical analysis has shown that a flat cell-by-cell recovery profile maximizes the separation of two floatable minerals for a given target bank recovery when the relative floatability is constant down the bank. Available bank survey data are analyzed with respect to recovery profiling. Possible variations on recovery profile to minimize entrainment are discussed.
Application of evolution strategy algorithm for optimization of a single-layer sound absorber
Directory of Open Access Journals (Sweden)
Morteza Gholamipoor
2014-12-01
Full Text Available Depending on different design parameters and limitations, optimization of sound absorbers has always been a challenge in the field of acoustic engineering. Various methods of optimization have evolved in the past decades with innovative method of evolution strategy gaining more attention in the recent years. Based on their simplicity and straightforward mathematical representations, single-layer absorbers have been widely used in both engineering and industrial applications and an optimized design for these absorbers has become vital. In the present study, the method of evolution strategy algorithm is used for optimization of a single-layer absorber at both a particular frequency and an arbitrary frequency band. Results of the optimization have been compared against different methods of genetic algorithm and penalty functions which are proved to be favorable in both effectiveness and accuracy. Finally, a single-layer absorber is optimized in a desired range of frequencies that is the main goal of an industrial and engineering optimization process.
An, Song A.; Tillman, Daniel A.; Paez, Carlos R.
2015-01-01
This study investigated the effects upon elementary preservice teachers' mathematics teaching self-efficacy and interdisciplinary lesson design strategies, which resulted from an educational intervention that emphasized integrated music-mathematics instruction. The participating elementary preservice teachers (n = 152) were recruited for this…
Mathematical efficiency calibration with uncertain source geometries using smart optimization
International Nuclear Information System (INIS)
Menaa, N.; Bosko, A.; Bronson, F.; Venkataraman, R.; Russ, W. R.; Mueller, W.; Nizhnik, V.; Mirolo, L.
2011-01-01
The In Situ Object Counting Software (ISOCS), a mathematical method developed by CANBERRA, is a well established technique for computing High Purity Germanium (HPGe) detector efficiencies for a wide variety of source shapes and sizes. In the ISOCS method, the user needs to input the geometry related parameters such as: the source dimensions, matrix composition and density, along with the source-to-detector distance. In many applications, the source dimensions, the matrix material and density may not be well known. Under such circumstances, the efficiencies may not be very accurate since the modeled source geometry may not be very representative of the measured geometry. CANBERRA developed an efficiency optimization software known as 'Advanced ISOCS' that varies the not well known parameters within user specified intervals and determines the optimal efficiency shape and magnitude based on available benchmarks in the measured spectra. The benchmarks could be results from isotopic codes such as MGAU, MGA, IGA, or FRAM, activities from multi-line nuclides, and multiple counts of the same item taken in different geometries (from the side, bottom, top etc). The efficiency optimization is carried out using either a random search based on standard probability distributions, or using numerical techniques that carry out a more directed (referred to as 'smart' in this paper) search. Measurements were carried out using representative source geometries and radionuclide distributions. The radionuclide activities were determined using the optimum efficiency and compared against the true activities. The 'Advanced ISOCS' method has many applications among which are: Safeguards, Decommissioning and Decontamination, Non-Destructive Assay systems and Nuclear reactor outages maintenance. (authors)
Combined optimization model for sustainable energization strategy
Abtew, Mohammed Seid
Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Local Optimization Strategies in Urban Vehicular Mobility.
Directory of Open Access Journals (Sweden)
Pierpaolo Mastroianni
Full Text Available The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.
Assessment of Antimicrobial Treatment Strategies in Pig Production Using Mathematical Models
DEFF Research Database (Denmark)
Ahmad, Amais
strategies. Dosing factors, along with the in vivo epidemiological parameters, govern the relation between resistance and antimicrobial use. Mathematical modeling and simulation techniques have been used over the past two decades to evaluate the effect of these factors on the development of resistance......, and are considered to be powerful tools in designing treatment strategies. The overall aim of the thesis was to develop an in vivo bacterial growth model to predict and assess the effect of dosing factor on resistance growth in order to optimize treatment strategies. Specific aims were to a) estimate pharmacodynamic...... concentration (MIC). These parameters along with MIC should be taken into account when studying the effect of antimicrobials on the bacterial growth. These parameters were used as an input to the in vivo growth model of multiple bacterial strains. For almost all treatments, high resistance levels were found...
Web malware spread modelling and optimal control strategies
Liu, Wanping; Zhong, Shouming
2017-02-01
The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.
Optimal allocation of trend following strategies
Grebenkov, Denis S.; Serror, Jeremy
2015-09-01
We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.
Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted
2017-01-01
Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.
Asymptotic estimation of reactor fueling optimal strategy
International Nuclear Information System (INIS)
Simonov, V.D.
1985-01-01
The problem of improving the technical-economic factors of operating. and designed nuclear power plant blocks by developino. internal fuel cycle strategy (reactor fueling regime optimization), taking into account energy system structural peculiarities altogether, is considered. It is shown, that in search of asymptotic solutions of reactor fueling planning tasks the model of fuel energy potential (FEP) is the most ssuitable and effective. FEP represents energy which may be produced from the fuel in a reactor with real dimensions and power, but with hypothetical fresh fuel supply, regime, providing smilar burnup of all the fuel, passing through the reactor, and continuous overloading of infinitely small fuel portion under fule power, and infinitely rapid mixing of fuel in the reactor core volume. Reactor fuel run with such a standard fuel cycle may serve as FEP quantitative measure. Assessment results of optimal WWER-440 reactor fresh fuel supply periodicity are given as an example. The conclusion is drawn that with fuel enrichment x=3.3% the run which is 300 days, is economically justified, taking into account that the cost of one energy unit production is > 3 cop/KW/h
Stability Analysis and Optimal Control Strategy for Prevention of Pine Wilt Disease
Directory of Open Access Journals (Sweden)
Kwang Sung Lee
2014-01-01
Full Text Available We propose a mathematical model of pine wilt disease (PWD which is caused by pine sawyer beetles carrying the pinewood nematode (PWN. We calculate the basic reproduction number R0 and investigate the stability of a disease-free and endemic equilibrium in a given mathematical model. We show that the stability of the equilibrium in the proposed model can be controlled through the basic reproduction number R0. We then discuss effective optimal control strategies for the proposed PWD mathematical model. We demonstrate the existence of a control problem, and then we apply both analytical and numerical techniques to demonstrate effective control methods to prevent the transmission of the PWD. In order to do this, we apply two control strategies: tree-injection of nematicide and the eradication of adult beetles through aerial pesticide spraying. Optimal prevention strategies can be determined by solving the corresponding optimality system. Numerical simulations of the optimal control problem using a set of reasonable parameter values suggest that reducing the number of pine sawyer beetles is more effective than the tree-injection strategy for controlling the spread of PWD.
Teaching Preschoolers to Count: Effective Strategies for Achieving Early Mathematics Milestones
Jacobi-Vessels, Jill L.; Brown, E. Todd; Molfese, Victoria J.; Do, Ahn
2016-01-01
Attention to early childhood mathematics instructional strategies has sharpened due to the relatively poor mathematics performance of U.S. students in comparison to students from other countries and research evidence that early mathematics skills impact later achievement. Early Childhood counting skills form the foundation for subsequent…
Andriani, Ade; Dewi, Izwita; Halomoan, Budi
2018-03-01
In general, this research is conducted to improve the quality of lectures on mathematics learning strategy in Mathematics Department. The specific objective of this research is to develop learning instrument of mathematics learning strategy based on Higher Order Thinking Skill (HOTS) that can be used to improve mathematical communication and self efficacy of mathematics education students. The type of research is development research (Research & Development), where this research aims to develop a new product or improve the product that has been made. This development research refers to the four-D Model, which consists of four stages: defining, designing, developing, and disseminating. The instrument of this research is the validation sheet and the student response sheet of the instrument.
Mathematical Teaching Strategies: Pathways to Critical Thinking and Metacognition
Su, Hui Fang Huang; Ricci, Frederick A.; Mnatsakanian, Mamikon
2016-01-01
A teacher that emphasizes reasoning, logic and validity gives their students access to mathematics as an effective way of practicing critical thinking. All students have the ability to enhance and expand their critical thinking when learning mathematics. Students can develop this ability when confronting mathematical problems, identifying possible…
Optimal control for mathematical models of cancer therapies an application of geometric methods
Schättler, Heinz
2015-01-01
This book presents applications of geometric optimal control to real life biomedical problems with an emphasis on cancer treatments. A number of mathematical models for both classical and novel cancer treatments are presented as optimal control problems with the goal of constructing optimal protocols. The power of geometric methods is illustrated with fully worked out complete global solutions to these mathematically challenging problems. Elaborate constructions of optimal controls and corresponding system responses provide great examples of applications of the tools of geometric optimal control and the outcomes aid the design of simpler, practically realizable suboptimal protocols. The book blends mathematical rigor with practically important topics in an easily readable tutorial style. Graduate students and researchers in science and engineering, particularly biomathematics and more mathematical aspects of biomedical engineering, would find this book particularly useful.
Mathematical optimization for planning and design of cycle paths
Energy Technology Data Exchange (ETDEWEB)
LiÑan Ruiz, R.J.; Perez Aracil, J.; Cabrera Cañizares, V.
2016-07-01
The daily need for citizens to move for different activities, whatever its nature, has been greatly affected by the changes. The advantages resulting from the inclusion of the bicycle as a mode of transport and the proliferation of its use among citizens are numerous and extend both in the field of urban mobility and sustainable development.Currently, there are a number of programs for the implementation, promotion or increased public participation related to cycling in cities. But ultimately, each and every one of these initiatives have the same goal, to create a mesh of effective, useful and cycling trails that allow the use of bicycles in preferred routes with high guarantees of security, incorporating bicycle model intermodal urban transport.With the gradual implementation of bike lanes, many people have begun to use them to get around the city. But everything again needs a period of adaptation, and the reality is that the road network for these vehicles is full of obstacles to the rider. The current situation has led to the proposal that many kilometers of cycle paths needed to supply the demand of this mode of transport and, if implemented and planned are correct and sufficient.This paper presents a mathematical programming model for optimal design of a network for cyclists is presented. Specifically, the model determines a network of bicycle infrastructure, appropriate to the characteristics of a network of existing roads.As an application of the proposed model, the result of these experiments give a number of useful conclusions for planning and designing networks of cycle paths from a social perspective, applied to the case in the city of Malaga. (Author)
Optimal Claiming Strategies in Bonus Malus Systems and Implied Markov Chains
Directory of Open Access Journals (Sweden)
Arthur Charpentier
2017-11-01
Full Text Available In this paper, we investigate the impact of the accident reporting strategy of drivers, within a Bonus-Malus system. We exhibit the induced modification of the corresponding class level transition matrix and derive the optimal reporting strategy for rational drivers. The hunger for bonuses induces optimal thresholds under which, drivers do not claim their losses. Mathematical properties of the induced level class process are studied. A convergent numerical algorithm is provided for computing such thresholds and realistic numerical applications are discussed.
International Nuclear Information System (INIS)
Pankov, V.V.; Chernyshev, G.G.; Kozlov, N.E.
1987-01-01
A mathematical model for optimization of multilayer submerged arc welding of frame equipment of power units is constructed. The variation-energy method permits to construct the universal mathematical model for strengthening formation of a single bead; the method is reasonable for simulation of a multilayer welded joint. Minimization of the distance between maximum and minimum layer height of a built-up metal is the necessary condition for qualitative formation of the multilayer joint. One can calculate in real time scale the optimal vector of maximally ten parameters under the multilayer welding condition immediately after change in the grooving width using the developed mathematical model of optimization
Optimal energy management strategy for self-reconfigurable batteries
International Nuclear Information System (INIS)
Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter
2017-01-01
This paper proposes a novel energy management strategy for multi-cell high voltage batteries where the current through each cell can be controlled, called self-reconfigurable batteries. An optimized control strategy further enhances the energy efficiency gained by the hardware architecture of those batteries. Currently, achieving cell equalization by using the active balancing circuits is considered as the best way to optimize the energy efficiency of the battery pack. This study demonstrates that optimizing the energy efficiency of self-reconfigurable batteries is no more strongly correlated to the cell balancing. According to the features of this novel battery architecture, the energy management strategy is formulated as nonlinear dynamic optimization problem. To solve this optimal control, an optimization algorithm that generates the optimal discharge policy for a given driving cycle is developed based on dynamic programming and code vectorization. The simulation results show that the designed energy management strategy maximizes the system efficiency across the battery lifetime over conventional approaches. Furthermore, the present energy management strategy can be implemented online due to the reduced complexity of the optimization algorithm. - Highlights: • The energy efficiency of self-reconfigurable batteries is maximized. • The energy management strategy for the battery is formulated as optimal control problem. • Developing an optimization algorithm using dynamic programming techniques and code vectorization. • Simulation studies are conducted to validate the proposed optimal strategy.
Mathematical Teaching Strategies: Pathways to Critical Thinking and Metacognition
Su, Hui Fang Huang " Ricci, Frederick A; Mnatsakanian, Mamikon
2015-01-01
A teacher that emphasizes reasoning, logic and validity gives their students access to mathematics as an effective way of practicing critical thinking. All students have the ability to enhance and expand their critical thinking when learning mathematics. Students can develop this ability when confronting mathematical problems, identifying possible solutions and evaluating and justifying their reasons for the results, thereby allowing students to become confident critical thinkers. Critical th...
Optimum investment strategy in the power industry mathematical models
Bartnik, Ryszard; Hnydiuk-Stefan, Anna
2016-01-01
This book presents an innovative methodology for identifying optimum investment strategies in the power industry. To do so, it examines results including, among others, the impact of oxy-fuel technology on CO2 emissions prices, and the specific cost of electricity production. The technical and economic analysis presented here extend the available knowledge in the field of investment optimization in energy engineering, while also enabling investors to make decisions involving its application. Individual chapters explore the potential impacts of different factors like environmental charges on costs connected with investments in the power sector, as well as discussing the available technologies for heat and power generation. The book offers a valuable resource for researchers, market analysts, decision makers, power engineers and students alike.
Optimization strategies for ultrasound volume registration
International Nuclear Information System (INIS)
Ijaz, Umer Zeeshan; Prager, Richard W; Gee, Andrew H; Treece, Graham M
2010-01-01
This paper considers registration of 3D ultrasound volumes acquired in multiple views for display in a single image volume. One way to acquire 3D data is to use a mechanically swept 3D probe. However, the usefulness of these probes is restricted by their limited field of view. This problem can be overcome by attaching a six-degree-of-freedom (DOF) position sensor to the probe, and displaying the information from multiple sweeps in their proper positions. However, an external six-DOF position sensor can be an inconvenience in a clinical setting. The objective of this paper is to propose a hybrid strategy that replaces the sensor with a combination of three-DOF image registration and an unobtrusive inertial sensor for measuring orientation. We examine a range of optimization algorithms and similarity measures for registration and compare them in in vitro and in vivo experiments. We register based on multiple reslice images rather than a whole voxel array. In this paper, we use a large number of reslices for improved reliability at the expense of computational speed. We have found that the Levenberg–Marquardt method is very fast but is not guaranteed to give the correct solution all the time. We conclude that normalized mutual information used in the Nelder–Mead simplex algorithm is potentially suitable for the registration task with an average execution time of around 5 min, in the majority of cases, with two restarts in a C++ implementation on a 3.0 GHz Intel Core 2 Duo CPU machine
Optimizing metapopulation sustainability through a checkerboard strategy.
Directory of Open Access Journals (Sweden)
Yossi Ben Zion
2010-01-01
Full Text Available The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent of stable solutions and the structure of their basin of attraction (dependence on initial population size. Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.
Effective Strategies for Teaching Mathematics to African American Students
White, La Donna
2012-01-01
As of 2001 with the mandates issued under No Child Left Behind, the National Council of Teachers of Mathematics (NCTM) revised its standards to ensure that all students receive a quality mathematics education (NCTM, 2008). The 2009 report from U.S. Department of Education revealed that there is an increase in the number of minority students…
Developing an Integrated Design Strategy for Chip Layout Optimization
Wits, Wessel Willems; Jauregui Becker, Juan Manuel; van Vliet, Frank Edward; te Riele, G.J.
2011-01-01
This paper presents an integrated design strategy for chip layout optimization. The strategy couples both electric and thermal aspects during the conceptual design phase to improve chip performances; thermal management being one of the major topics. The layout of the chip circuitry is optimized
Optimal Spatial Harvesting Strategy and Symmetry-Breaking
International Nuclear Information System (INIS)
Kurata, Kazuhiro; Shi Junping
2008-01-01
A reaction-diffusion model with logistic growth and constant effort harvesting is considered. By minimizing an intrinsic biological energy function, we obtain an optimal spatial harvesting strategy which will benefit the population the most. The symmetry properties of the optimal strategy are also discussed, and related symmetry preserving and symmetry breaking phenomena are shown with several typical examples of habitats
Optimal Investment-Consumption Strategy under Inflation in a Markovian Regime-Switching Market
Directory of Open Access Journals (Sweden)
Huiling Wu
2016-01-01
Full Text Available This paper studies an investment-consumption problem under inflation. The consumption price level, the prices of the available assets, and the coefficient of the power utility are assumed to be sensitive to the states of underlying economy modulated by a continuous-time Markovian chain. The definition of admissible strategies and the verification theory corresponding to this stochastic control problem are presented. The analytical expression of the optimal investment strategy is derived. The existence, boundedness, and feasibility of the optimal consumption are proven. Finally, we analyze in detail by mathematical and numerical analysis how the risk aversion, the correlation coefficient between the inflation and the stock price, the inflation parameters, and the coefficient of utility affect the optimal investment and consumption strategy.
Mathematical Modelling, Simulation, and Optimal Control of the 2014 Ebola Outbreak in West Africa
Directory of Open Access Journals (Sweden)
Amira Rachah
2015-01-01
it is crucial to modelize the virus and simulate it. In this paper, we begin by studying a simple mathematical model that describes the 2014 Ebola outbreak in Liberia. Then, we use numerical simulations and available data provided by the World Health Organization to validate the obtained mathematical model. Moreover, we develop a new mathematical model including vaccination of individuals. We discuss different cases of vaccination in order to predict the effect of vaccination on the infected individuals over time. Finally, we apply optimal control to study the impact of vaccination on the spread of the Ebola virus. The optimal control problem is solved numerically by using a direct multiple shooting method.
Synthesis of Optimal Strategies Using HyTech
DEFF Research Database (Denmark)
Bouyer, Patricia; Cassez, Franck; Larsen, Kim Guldstrand
2005-01-01
Priced timed (game) automata extend timed (game) automata with costs on both locations and transitions. The problem of synthesizing an optimal winning strategy for a priced timed game under some hypotheses has been shown decidable in [P. Bouyer, F. Cassez, E. Fleury, and K.G. Larsen. Optimal...... strategies in priced timed game automata. Research Report BRICS RS-04-4, Denmark, Feb. 2004. Available at http://www.brics.dk/RS/04/4/]. In this paper, we present an algorithm for computing the optimal cost and for synthesizing an optimal strategy in case there exists one. We also describe the implementation...
Optimization Strategies for Hardware-Based Cofactorization
Loebenberger, Daniel; Putzka, Jens
We use the specific structure of the inputs to the cofactorization step in the general number field sieve (GNFS) in order to optimize the runtime for the cofactorization step on a hardware cluster. An optimal distribution of bitlength-specific ECM modules is proposed and compared to existing ones. With our optimizations we obtain a speedup between 17% and 33% of the cofactorization step of the GNFS when compared to the runtime of an unoptimized cluster.
Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.
Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V
2016-01-01
Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
In an electricity market generating companies and large consumers need suitable bidding models to maximize their profits. Therefore, each supplier and large consumer will bid strategically for choosing the bidding coefficients to counter the competitors bidding strategy. In this paper, bidding strategy problem modeled as an ...
Optimization strategies for discrete multi-material stiffness optimization
DEFF Research Database (Denmark)
Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias
2011-01-01
Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... which numerically confirm the sought properties of the new scheme in terms of convergence to a discrete solution....
Fetal DNA: strategies for optimal recovery
Legler, Tobias J.; Heermann, Klaus-Hinrich; Liu, Zhong; Soussan, Aicha Ait; van der Schoot, C. Ellen
2008-01-01
For fetal DNA extraction, in principle each DNA extraction method can be used; however, because most methods have been optimized for genomic DNA from leucocytes, we describe here the methods that have been optimized for the extraction of fetal DNA from maternal plasma and validated for this purpose
Strategies for Optimal Design of Structural Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...
An optimal tuning strategy for tidal turbines.
Vennell, Ross
2016-11-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This 'impatient-tuning strategy' results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing 'patient-tuning strategy' which maximizes the power output averaged over the tidal cycle. This paper presents a 'smart patient tuning strategy', which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine's average power output.
Mathematical foundation of the optimization-based fluid animation method
DEFF Research Database (Denmark)
Erleben, Kenny; Misztal, Marek Krzysztof; Bærentzen, Jakob Andreas
2011-01-01
We present the mathematical foundation of a fluid animation method for unstructured meshes. Key contributions not previously treated are the extension to include diffusion forces and higher order terms of non-linear force approximations. In our discretization we apply a fractional step method to ...
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
user
A considerable amount of work has also been reported on the game theory applications ... probability distribution function (Song et al, 1999) and as a continuous ..... compared with GA and Monte Carlo method, therefore the bidding strategies.
Verification and synthesis of optimal decision strategies for complex systems
Energy Technology Data Exchange (ETDEWEB)
Summers, S. J.
2013-07-01
Complex systems make a habit of disagreeing with the mathematical models strategically designed to capture their behavior. A recursive process ensues where data is used to gain insight into the disagreement. A simple model may give way to a model with hybrid dynamics. A deterministic model may give way to a model with stochastic dynamics. In many cases, the modeling framework that sufficiently characterises the system is both hybrid and stochastic; these systems are referred to as stochastic hybrid systems. This dissertation considers the stochastic hybrid system framework for modeling complex systems and provides mathematical methods for analysing, and synthesizing decision laws for, such systems. We first propose a stochastic reach-avoid problem for discrete time stochastic hybrid systems. In particular, we present a dynamic programming based solution to a probabilistic reach-avoid problem for a controlled discrete time stochastic hybrid system. We address two distinct interpretations of the reach-avoid problem via stochastic optimal control. In the first case, a sum-multiplicative cost function is introduced along with a corresponding dynamic recursion that quantifies the probability of hitting a target set at some point during a finite time horizon, while avoiding an unsafe set at all preceding time steps. In the second case, we introduce a multiplicative cost function and a dynamic recursion that quantifies the probability of hitting a target set at the terminal time, while avoiding an unsafe set at all preceding time steps. In each case, optimal reach-avoid control policies are derived as the solution to an optimal control problem via dynamic programming. We next introduce an extension of the reach-avoid problem where we consider the verification of discrete time stochastic hybrid systems when there exists uncertainty in the reachability specifications themselves. A sum multiplicative cost function is introduced along with a corresponding dynamic recursion
Verification and synthesis of optimal decision strategies for complex systems
International Nuclear Information System (INIS)
Summers, S. J.
2013-01-01
Complex systems make a habit of disagreeing with the mathematical models strategically designed to capture their behavior. A recursive process ensues where data is used to gain insight into the disagreement. A simple model may give way to a model with hybrid dynamics. A deterministic model may give way to a model with stochastic dynamics. In many cases, the modeling framework that sufficiently characterises the system is both hybrid and stochastic; these systems are referred to as stochastic hybrid systems. This dissertation considers the stochastic hybrid system framework for modeling complex systems and provides mathematical methods for analysing, and synthesizing decision laws for, such systems. We first propose a stochastic reach-avoid problem for discrete time stochastic hybrid systems. In particular, we present a dynamic programming based solution to a probabilistic reach-avoid problem for a controlled discrete time stochastic hybrid system. We address two distinct interpretations of the reach-avoid problem via stochastic optimal control. In the first case, a sum-multiplicative cost function is introduced along with a corresponding dynamic recursion that quantifies the probability of hitting a target set at some point during a finite time horizon, while avoiding an unsafe set at all preceding time steps. In the second case, we introduce a multiplicative cost function and a dynamic recursion that quantifies the probability of hitting a target set at the terminal time, while avoiding an unsafe set at all preceding time steps. In each case, optimal reach-avoid control policies are derived as the solution to an optimal control problem via dynamic programming. We next introduce an extension of the reach-avoid problem where we consider the verification of discrete time stochastic hybrid systems when there exists uncertainty in the reachability specifications themselves. A sum multiplicative cost function is introduced along with a corresponding dynamic recursion
Optimal portfolio strategies under a shortfall constraint
African Journals Online (AJOL)
we make precise the optimal control problem to be solved. .... is closely related to the concept of Value-at-Risk, but overcomes some of the conceptual .... We adapt a dynamic programming approach to solve the HJB equation associated with.
Optimal Pricing Strategy for New Products
Trichy V. Krishnan; Frank M. Bass; Dipak C. Jain
1999-01-01
Robinson and Lakhani (1975) initiated a long research stream in marketing when they used the Bass model (1969) to develop optimal pricing path for a new product. A careful analysis of the extant literature reveals that the research predominantly suggests that the optimal price path should be largely based on the sales growth pattern. However, in the real world we rarely find new products that have such pricing pattern. We observe either a monotonically declining pricing pattern or an increase...
Ramnarain, Umesh
2014-01-01
A major impediment to problem solving in mathematics in the great majority of South African schools is that disadvantaged students from seriously impoverished learning environments are lacking in the necessary informal mathematical knowledge to develop their own strategies for solving non-routine problems. A randomized pretest-posttest control…
What Mathematics Teachers Say about the Teaching Strategies in the Implementation of Tasks
Enríquez, Jakeline Amparo Villota; de Oliveira, Andréia María Pereira; Valencia, Heriberto González
2018-01-01
In this article we will discuss, through the explanations given by teachers who teach Mathematics, the importance of using teaching strategies in the implementation of tasks. Teachers who participated in it belong to the group "Observatory Mathematics Education" (OME-Bahia). This study was framed in a qualitative approach and data were…
Effects of Teaching Strategies on Student Motivation to Learn in High School Mathematics Classes
Toles, Ann
2010-01-01
To succeed in an increasing technological and global society, students need to develop strong mathematical and problem-solving skills. This qualitative grounded theory study examined student perceptions of the ways in which teaching strategies in high school mathematics classes affect student motivation to learn the subject. Study participants…
Ünlü, Melihan
2017-01-01
The aim of the study was to determine mathematics teacher candidates' knowledge about problem solving strategies through problem posing. This qualitative research was conducted with 95 mathematics teacher candidates studying at education faculty of a public university during the first term of the 2015-2016 academic year in Turkey. Problem Posing…
Jitendra, Asha K.; Petersen-Brown, Shawna; Lein, Amy E.; Zaslofsky, Anne F.; Kunkel, Amy K.; Jung, Pyung-Gang; Egan, Andrea M.
2015-01-01
This study examined the quality of the research base related to strategy instruction priming the underlying mathematical problem structure for students with learning disabilities and those at risk for mathematics difficulties. We evaluated the quality of methodological rigor of 18 group research studies using the criteria proposed by Gersten et…
Strategies Used to Teach Mathematics to Special Education Students from the Teachers' Perspective
Brown, Desline A.
2016-01-01
The perspectives of special education teachers on the strategies used to teach mathematics to special education students were examined in this dissertation. Three central research questions that guided the study are: (a) What were New York special education teachers' opinions about the methods they use to teach mathematics to special education…
van 't Noordende, Jaccoline E|info:eu-repo/dai/nl/369862422; van Hoogmoed, Anne H|info:eu-repo/dai/nl/314839496; Schot, Willemijn D; Kroesbergen, Evelyn H|info:eu-repo/dai/nl/241607949
INTRODUCTION: Number line estimation is one of the skills related to mathematical performance. Previous research has shown that eye tracking can be used to identify differences in the estimation strategies children with dyscalculia and children with typical mathematical development use on number
van’t Noordende, Jaccoline E.; van Hoogmoed, Anne H.; Schot, Willemijn D.; Kroesbergen, Evelyn H.
2016-01-01
Introduction: Number line estimation is one of the skills related to mathematical performance. Previous research has shown that eye tracking can be used to identify differences in the estimation strategies children with dyscalculia and children with typical mathematical development use on number
Jeanmarie-Gardner, Charmaine
2013-01-01
A quasi-experimental research study was conducted that investigated the academic impact of utilizing Marzano's summarizing and note taking strategies on mathematic achievement. A sample of seventh graders from a middle school located on Long Island's North Shore was tested to determine whether significant differences existed in mathematic test…
Stochastic Robust Mathematical Programming Model for Power System Optimization
Energy Technology Data Exchange (ETDEWEB)
Liu, Cong; Changhyeok, Lee; Haoyong, Chen; Mehrotra, Sanjay
2016-01-01
This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.
An optimal tuning strategy for tidal turbines
2016-01-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This ‘impatient-tuning strategy’ results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing ‘patient-tuning strategy’ which maximizes the power output averaged over the tidal cycle. This paper presents a ‘smart patient tuning strategy’, which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine’s average power output. PMID:27956870
Pinto Mariano, Adriano; Bastos Borba Costa, Caliane; de Franceschi de Angelis, Dejanira; Maugeri Filho, Francisco; Pires Atala, Daniel Ibraim; Wolf Maciel, Maria Regina; Maciel Filho, Rubens
2009-11-01
In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.
Strategies That Help Learning-Disabled Students Solve Verbal Mathematical Problems.
Giordano, Gerard
1990-01-01
Strategies are presented for dealing with factors that can be responsible for failure in mathematical problem solving. The suggestions include personalization of verbal problems, thematic strands based on student interests, visual representation, a laboratory approach, and paraphrasing. (JDD)
Directory of Open Access Journals (Sweden)
Iván Machín
2015-03-01
Full Text Available This paper presents a set of procedures based on mathematical optimization methods to establish optimal active sulphide phases with higher HDS activity. This paper proposes a list of active phases as a guide for orienting the experimental work in the search of new catalysts that permit optimize the HDS process. Studies in this paper establish Co-S, Cr-S, Nb-S and Ni-S systems have the greatest potential to improve HDS activity.
Directory of Open Access Journals (Sweden)
Annabelle Ballesta
2011-09-01
Full Text Available Circadian timing largely modifies efficacy and toxicity of many anticancer drugs. Recent findings suggest that optimal circadian delivery patterns depend on the patient genetic background. We present here a combined experimental and mathematical approach for the design of chronomodulated administration schedules tailored to the patient molecular profile. As a proof of concept we optimized exposure of Caco-2 colon cancer cells to irinotecan (CPT11, a cytotoxic drug approved for the treatment of colorectal cancer. CPT11 was bioactivated into SN38 and its efflux was mediated by ATP-Binding-Cassette (ABC transporters in Caco-2 cells. After cell synchronization with a serum shock defining Circadian Time (CT 0, circadian rhythms with a period of 26 h 50 (SD 63 min were observed in the mRNA expression of clock genes REV-ERBα, PER2, BMAL1, the drug target topoisomerase 1 (TOP1, the activation enzyme carboxylesterase 2 (CES2, the deactivation enzyme UDP-glucuronosyltransferase 1, polypeptide A1 (UGT1A1, and efflux transporters ABCB1, ABCC1, ABCC2 and ABCG2. DNA-bound TOP1 protein amount in presence of CPT11, a marker of the drug PD, also displayed circadian variations. A mathematical model of CPT11 molecular pharmacokinetics-pharmacodynamics (PK-PD was designed and fitted to experimental data. It predicted that CPT11 bioactivation was the main determinant of CPT11 PD circadian rhythm. We then adopted the therapeutics strategy of maximizing efficacy in non-synchronized cells, considered as cancer cells, under a constraint of maximum toxicity in synchronized cells, representing healthy ones. We considered exposure schemes in the form of an initial concentration of CPT11 given at a particular CT, over a duration ranging from 1 to 27 h. For any dose of CPT11, optimal exposure durations varied from 3h40 to 7h10. Optimal schemes started between CT2h10 and CT2h30, a time interval corresponding to 1h30 to 1h50 before the nadir of CPT11 bioactivation rhythm in
Tas, Maarten; Forsythe, Sue
2010-01-01
The main aim of this study was to analyse and evaluate the effectiveness of support strategies being put into place for students who need to write assignments at Masters Level. In preparation for writing a 5000 word assignment on an aspect of teaching Mathematics or Science, 57 Science and Mathematics PGCE students were asked to write a 500 word synopsis which included an introduction, description of the main focus, questions that the assignment would address and possible strategies for teach...
Power consumption optimization strategy for wireless networks
DEFF Research Database (Denmark)
Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola
2011-01-01
in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...
Intelligent fault recognition strategy based on adaptive optimized multiple centers
Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong
2018-06-01
For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.
Long-run savings and investment strategy optimization.
Gerrard, Russell; Guillén, Montserrat; Nielsen, Jens Perch; Pérez-Marín, Ana M
2014-01-01
We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor's risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.
Long-Run Savings and Investment Strategy Optimization
Directory of Open Access Journals (Sweden)
Russell Gerrard
2014-01-01
Full Text Available We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor’s risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.
Rahayu, D. V.; Kusumah, Y. S.; Darhim
2018-05-01
This study examined to see the improvement of prospective teachers’ basic skills of teaching mathematics through search-solve-create-share learning strategy based on overall and Mathematical Prior Knowledge (MPK) and interaction of both. Quasi experiments with the design of this experimental-non-equivalent control group design involved 67 students at the mathematics program of STKIP Garut. The instrument used in this study included pre-test and post-test. The result of this study showed that: (1) The improvement and achievement of the basic skills of teaching mathematics of the prospective teachers who get the learning of search-solve-create-share strategy is better than the improvement and achievement of the prospective teachers who get the conventional learning as a whole and based on MPK; (2) There is no interaction between the learning used and MPK on improving and achieving basic skills of teaching mathematics.
[Multi-mathematical modelings for compatibility optimization of Jiangzhi granules].
Yang, Ming; Zhang, Li; Ge, Yingli; Lu, Yanliu; Ji, Guang
2011-12-01
To investigate into the method of "multi activity index evaluation and combination optimized of mult-component" for Chinese herbal formulas. According to the scheme of uniform experimental design, efficacy experiment, multi index evaluation, least absolute shrinkage, selection operator (LASSO) modeling, evolutionary optimization algorithm, validation experiment, we optimized the combination of Jiangzhi granules based on the activity indexes of blood serum ALT, ALT, AST, TG, TC, HDL, LDL and TG level of liver tissues, ratio of liver tissue to body. Analytic hierarchy process (AHP) combining with criteria importance through intercriteria correlation (CRITIC) for multi activity index evaluation was more reasonable and objective, it reflected the information of activity index's order and objective sample data. LASSO algorithm modeling could accurately reflect the relationship between different combination of Jiangzhi granule and the activity comprehensive indexes. The optimized combination of Jiangzhi granule showed better values of the activity comprehensive indexed than the original formula after the validation experiment. AHP combining with CRITIC can be used for multi activity index evaluation and LASSO algorithm, it is suitable for combination optimized of Chinese herbal formulas.
Mathematical programming model for the optimization of nutritional ...
African Journals Online (AJOL)
optimum level of production and the corresponding feed that should be offered to the cow, under a particular production system. The model showed that the nutritional strategy applied is dependent upon the ..... Effects of business and dairy.
Control strategy optimization of HVAC plants
Energy Technology Data Exchange (ETDEWEB)
Facci, Andrea Luigi; Zanfardino, Antonella [Department of Engineering, University of Napoli “Parthenope” (Italy); Martini, Fabrizio [Green Energy Plus srl (Italy); Pirozzi, Salvatore [SIAT Installazioni spa (Italy); Ubertini, Stefano [School of Engineering (DEIM) University of Tuscia (Italy)
2015-03-10
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting.
Control strategy optimization of HVAC plants
International Nuclear Information System (INIS)
Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio; Pirozzi, Salvatore; Ubertini, Stefano
2015-01-01
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting
Optimal Licensing Strategy: Royalty or Fixed Fee?
Andrea Fosfuri; Esther Roca
2004-01-01
Licensing a cost-reducing innovation through a royalty has been shown to be superior to licensing by means of a fixed fee for an incumbent licensor. This note shows that this result relies crucially on the assumption that the incumbent licensor can sell its cost-reducing inno-vation to all industry players. If, for any reason, only some competitors could be reached through a licensing contract, then a fixed fee might be optimally chosen.
Optimized Power Dispatch Strategy for Offshore Wind Farms
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Zhang, Baohua
2016-01-01
which are related to electrical system topology. This paper proposed an optimized power dispatch strategy (OPD) for minimizing the levelized production cost (LPC) of a wind farm. Particle swarm optimization (PSO) is employed to obtain final solution for the optimization problem. Both regular shape......Maximizing the power production of offshore wind farms using proper control strategy has become an important issue for wind farm operators. However, the power transmitted to the onshore substation (OS) is not only related to the power production of each wind turbine (WT) but also the power losses...... and irregular shape wind farm are chosen for the case study. The proposed dispatch strategy is compared with two other control strategies. The simulation results show the effectiveness of the proposed strategy....
Sleep As A Strategy For Optimizing Performance.
Yarnell, Angela M; Deuster, Patricia
2016-01-01
Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance. 2016.
Peers Influence Mathematics Strategy Use in Early Elementary School
Carr, Martha; Barned, Nicole; Otumfuor, Beryl
2016-01-01
This study examined the impact of performance goals on arithmetic strategy use, and how same-sex peer groups contributed to the selection of strategies used by first-graders. It was hypothesized that gender differences in strategy use are a function of performance goals and the influence of same-sex peers. Using a sample of 75 first grade…
Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation
Krastev, Vladimir
2011-12-01
We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to optimal control sub problems we find the optimal advertising strategy and goodwill.
A strategy for optimizing item-pool management
Ariel, A.; van der Linden, Willem J.; Veldkamp, Bernard P.
2006-01-01
Item-pool management requires a balancing act between the input of new items into the pool and the output of tests assembled from it. A strategy for optimizing item-pool management is presented that is based on the idea of a periodic update of an optimal blueprint for the item pool to tune item
Framing discourse for optimal learning in science and mathematics
Megowan, Mary Colleen
2007-12-01
This study explored the collaborative thinking and learning that occurred in physics and mathematics classes where teachers practiced Modeling Instruction. Four different classes were videotaped---a middle school mathematics resource class, a 9th grade physical science class, a high school honors physics class and a community college engineering physics course. Videotapes and transcripts were analyzed to discover connections between the conceptual structures and spatial representations that shaped students' conversations about space and time. Along the way, it became apparent that students' and teachers' cultural models of schooling were a significant influence, sometimes positive and sometimes negative, in students' engagement and metaphor selection. A growing number of researchers are exploring the importance of semiotics in physics and mathematics, but typically their unit of analysis is the individual student. To examine the distributed cognition that occurred in this unique learning setting, not just among students but also in connection with their tools, artifacts and representations, I extended the unit of analysis for my research to include small groups and their collaborative work with whiteboarded representations of contextual problems and laboratory exercises. My data revealed a number of interesting insights. Students who constructed spatial representations and used them to assist their reasoning, were more apt to demonstrate a coherent grasp of the elements, operations, relations and rules that govern the model under investigation than those who relied on propositional algebraic representations of the model. In classrooms where teachers permitted and encouraged students to take and hold the floor during whole-group discussions, students learned to probe one another more deeply and conceptually. Shared representations (whether spatial or propositional/algebraic), such as those that naturally occurred when students worked together in small groups to
Blackjack in Holland Casino's : Basic, optimal and winning strategies
van der Genugten, B.B.
1995-01-01
This paper considers the cardgame Blackjack according to the rules of Holland Casino's in the Netherlands. Expected gains of strategies are derived with simulation and also with analytic tools. New effiency concepts based on the gains of the basic and the optimal strategy are introduced. A general
A new inertia weight control strategy for particle swarm optimization
Zhu, Xianming; Wang, Hongbo
2018-04-01
Particle Swarm Optimization is a member of swarm intelligence algorithms, which is inspired by the behavior of bird flocks. The inertia weight, one of the most important parameters of PSO, is crucial for PSO, for it balances the performance of exploration and exploitation of the algorithm. This paper proposes a new inertia weight control strategy and PSO with this new strategy is tested by four benchmark functions. The results shows that the new strategy provides the PSO with better performance.
Noise-dependent optimal strategies for quantum metrology
Huang, Zixin; Macchiavello, Chiara; Maccone, Lorenzo
2018-03-01
For phase estimation using qubits, we show that for some noise channels, the optimal entanglement-assisted strategy depends on the noise level. We note that there is a nontrivial crossover between the parallel-entangled strategy and the ancilla-assisted strategy: in the former the probes are all entangled; in the latter the probes are entangled with a noiseless ancilla but not among themselves. The transition can be explained by the fact that separable states are more robust against noise and therefore are optimal in the high-noise limit, but they are in turn outperformed by ancilla-assisted ones.
Optimal intermittent search strategies: smelling the prey
International Nuclear Information System (INIS)
Revelli, J A; Wio, H S; Rojo, F; Budde, C E
2010-01-01
We study the kinetics of the search of a single fixed target by a searcher/walker that performs an intermittent random walk, characterized by different states of motion. In addition, we assume that the walker has the ability to detect the scent left by the prey/target in its surroundings. Our results, in agreement with intuition, indicate that the prey's survival probability could be strongly reduced (increased) if the predator is attracted (or repelled) by the trace left by the prey. We have also found that, for a positive trace (the predator is guided towards the prey), increasing the inhomogeneity's size reduces the prey's survival probability, while the optimal value of α (the parameter that regulates intermittency) ceases to exist. The agreement between theory and numerical simulations is excellent.
Optimal intermittent search strategies: smelling the prey
Energy Technology Data Exchange (ETDEWEB)
Revelli, J A; Wio, H S [Instituto de Fisica de Cantabria, Universidad de Cantabria and CSIC, E-39005 Santander (Spain); Rojo, F; Budde, C E [Fa.M.A.F., Universidad Nacional de Cordoba, Ciudad Universitaria, X5000HUA Cordoba (Argentina)
2010-05-14
We study the kinetics of the search of a single fixed target by a searcher/walker that performs an intermittent random walk, characterized by different states of motion. In addition, we assume that the walker has the ability to detect the scent left by the prey/target in its surroundings. Our results, in agreement with intuition, indicate that the prey's survival probability could be strongly reduced (increased) if the predator is attracted (or repelled) by the trace left by the prey. We have also found that, for a positive trace (the predator is guided towards the prey), increasing the inhomogeneity's size reduces the prey's survival probability, while the optimal value of {alpha} (the parameter that regulates intermittency) ceases to exist. The agreement between theory and numerical simulations is excellent.
Optimal Inspection and Maintenance Strategies for Structural Systems
DEFF Research Database (Denmark)
Sommer, A. M.
The aim of this thesis is to give an overview of conventional and optimal reliability-based inspection and maintenance strategies and to examine for specific structures how the cost can be reduced and/or the safety can be improved by using optimal reliability-based inspection strategies....... For structures with several almost similar components it is suggested that individual inspection strategies should be determined for each component or a group of components based on the reliability of the actual component. The benefit of this procedure is assessed in connection with the structures considered....... Furthermore, in relation to the calculations performed the intention is to modify an existing program for determination of optimal inspection strategies. The main purpose of inspection and maintenance of structural systems is to prevent or delay damage or deterioration to protect people, environment...
Optimization of mathematical models for soil structure interaction
International Nuclear Information System (INIS)
Vallenas, J.M.; Wong, C.K.; Wong, D.L.
1993-01-01
Accounting for soil-structure interaction in the design and analysis of major structures for DOE facilities can involve significant costs in terms of modeling and computer time. Using computer programs like SASSI for modeling major structures, especially buried structures, requires the use of models with a large number of soil-structure interaction nodes. The computer time requirements (and costs) increase as a function of the number of interaction nodes to the third power. The added computer and labor cost for data manipulation and post-processing can further increase the total cost. This paper provides a methodology to significantly reduce the number of interaction nodes. This is achieved by selectively increasing the thickness of soil layers modeled based on the need for the mathematical model to capture as input only those frequencies that can actually be transmitted by the soil media. The authors have rarely found that a model needs to capture frequencies as high as 33 Hz. Typically coarser meshes (and a lesser number of interaction nodes) are adequate
Mathematical Modelling of Optimization of Structures of Monolithic Coverings Based on Liquid Rubbers
Turgumbayeva, R. Kh; Abdikarimov, M. N.; Mussabekov, R.; Sartayev, D. T.
2018-05-01
The paper considers optimization of monolithic coatings compositions using a computer and MPE methods. The goal of the paper was to construct a mathematical model of the complete factorial experiment taking into account its plan and conditions. Several regression equations were received. Dependence between content components and parameters of rubber, as well as the quantity of a rubber crumb, was considered. An optimal composition for manufacturing the material of monolithic coatings compositions was recommended based on experimental data.
International Nuclear Information System (INIS)
Severin, V.P.
2007-01-01
The mathematical modeling of automatic control systems of reactor facility WWER-1000 with various regulator types is considered. The linear and nonlinear models of neutron power control systems of nuclear reactor WWER-1000 with various group numbers of delayed neutrons are designed. The results of optimization of direct quality indexes of neutron power control systems of nuclear reactor WWER-1000 are designed. The identification and optimization of level control systems with various regulator types of steam generator are executed
Areepattamannil, Shaljan; Caleon, Imelda S
2013-01-01
The authors examined the relationships of cognitive (i.e., memorization and elaboration) and metacognitive learning strategies (i.e., control strategies) to mathematics achievement among 15-year-old students in 4 high-performing East Asian education systems: Shanghai-China, Hong Kong-China, Korea, and Singapore. In all 4 East Asian education systems, memorization strategies were negatively associated with mathematics achievement, whereas control strategies were positively associated with mathematics achievement. However, the association between elaboration strategies and mathematics achievement was a mixed bag. In Shanghai-China and Korea, elaboration strategies were not associated with mathematics achievement. In Hong Kong-China and Singapore, on the other hand, elaboration strategies were negatively associated with mathematics achievement. Implications of these findings are briefly discussed.
A proposal of optimal sampling design using a modularity strategy
Simone, A.; Giustolisi, O.; Laucelli, D. B.
2016-08-01
In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.
Directory of Open Access Journals (Sweden)
Delsika Pramata Sari
2017-06-01
Full Text Available The purpose of this study was to investigate the errors experienced by students learning with REACT strategy and traditional learning in solving problems of mathematical representation ability. This study used quasi experimental pattern with static-group comparison design. The subjects of this study were 47 eighth grade students of junior high school in Bandung consisting of two samples. The instrument used was a test to measure students' mathematical representation ability. The reliability coefficient about the mathematical representation ability was 0.56. The most prominent errors of mathematical representation ability of students learning with REACT strategy and traditional learning, was on indicator that solving problem involving arithmetic symbols (symbolic representation. In addition, errors were also experienced by many students with traditional learning on the indicator of making the image of a real world situation to clarify the problem and facilitate its completion (visual representation.
Directory of Open Access Journals (Sweden)
Mehmet Polat Saka
2013-01-01
Full Text Available The type of mathematical modeling selected for the optimum design problems of steel skeletal frames affects the size and mathematical complexity of the programming problem obtained. Survey on the structural optimization literature reveals that there are basically two types of design optimization formulation. In the first type only cross sectional properties of frame members are taken as design variables. In such formulation when the values of design variables change during design cycles, it becomes necessary to analyze the structure and update the response of steel frame to the external loading. Structural analysis in this type is a complementary part of the design process. In the second type joint coordinates are also treated as design variables in addition to the cross sectional properties of members. Such formulation eliminates the necessity of carrying out structural analysis in every design cycle. The values of the joint displacements are determined by the optimization techniques in addition to cross sectional properties. The structural optimization literature contains structural design algorithms that make use of both type of formulation. In this study a review is carried out on mathematical and metaheuristic algorithms where the effect of the mathematical modeling on the efficiency of these algorithms is discussed.
Finding optimal vaccination strategies for pandemic influenza using genetic algorithms.
Patel, Rajan; Longini, Ira M; Halloran, M Elizabeth
2005-05-21
In the event of pandemic influenza, only limited supplies of vaccine may be available. We use stochastic epidemic simulations, genetic algorithms (GA), and random mutation hill climbing (RMHC) to find optimal vaccine distributions to minimize the number of illnesses or deaths in the population, given limited quantities of vaccine. Due to the non-linearity, complexity and stochasticity of the epidemic process, it is not possible to solve for optimal vaccine distributions mathematically. However, we use GA and RMHC to find near optimal vaccine distributions. We model an influenza pandemic that has age-specific illness attack rates similar to the Asian pandemic in 1957-1958 caused by influenza A(H2N2), as well as a distribution similar to the Hong Kong pandemic in 1968-1969 caused by influenza A(H3N2). We find the optimal vaccine distributions given that the number of doses is limited over the range of 10-90% of the population. While GA and RMHC work well in finding optimal vaccine distributions, GA is significantly more efficient than RMHC. We show that the optimal vaccine distribution found by GA and RMHC is up to 84% more effective than random mass vaccination in the mid range of vaccine availability. GA is generalizable to the optimization of stochastic model parameters for other infectious diseases and population structures.
Optimal reactor strategy for commercializing fast breeder reactors
International Nuclear Information System (INIS)
Yamaji, Kenji; Nagano, Koji
1988-01-01
In this paper, a fuel cycle optimization model developed for analyzing the condition of selecting fast breeder reactors in the optimal reactor strategy is described. By dividing the period of planning, 1966-2055, into nine ten-year periods, the model was formulated as a compact linear programming model. With the model, the best mix of reactor types as well as the optimal timing of reprocessing spent fuel from LWRs to minimize the total cost were found. The results of the analysis are summarized as follows. Fast breeder reactors could be introduced in the optimal strategy when they can economically compete with LWRs with 30 year storage of spent fuel. In order that fast breeder reactors monopolize the new reactor market after the achievement of their technical availability, their capital cost should be less than 0.9 times as much as that of LWRs. When a certain amount of reprocessing commitment is assumed, the condition of employing fast breeder reactors in the optimal strategy is mitigated. In the optimal strategy, reprocessing is done just to meet plutonium demand, and the storage of spent fuel is selected to adjust the mismatch of plutonium production and utilization. The price hike of uranium ore facilitates the commercial adoption of fast breeder reactors. (Kako, I.)
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints
Directory of Open Access Journals (Sweden)
Xiaojian Yu
2014-01-01
Full Text Available This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP strategy can ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that the REDP strategy successfully controls the maximum drawdown within the given limit and performs best in both return and risk.
Alabdulaziz, M.; Higgins, S.
2017-01-01
This paper will investigate the relationship between technology use and the use of constructivist strategies when addressing Saudi primary students' mathematics difficulties. Semi-structured interviews and observations were used for the purpose of this research, which were undertaken with three mathematics teachers from school A which used technology, and the other three from school B, which did not use technology. We found that technology can support constructivist approach when teaching and...
Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.
Tilahun, Getachew Teshome; Makinde, Oluwole Daniel; Malonza, David
2017-01-01
We propose and analyze a compartmental nonlinear deterministic mathematical model for the typhoid fever outbreak and optimal control strategies in a community with varying population. The model is studied qualitatively using stability theory of differential equations and the basic reproductive number that represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The model exhibits a forward transcritical bifurcation and the sensitivity analysis is performed. The optimal control problem is designed by applying Pontryagin maximum principle with three control strategies, namely, the prevention strategy through sanitation, proper hygiene, and vaccination; the treatment strategy through application of appropriate medicine; and the screening of the carriers. The cost functional accounts for the cost involved in prevention, screening, and treatment together with the total number of the infected persons averted. Numerical results for the typhoid outbreak dynamics and its optimal control revealed that a combination of prevention and treatment is the best cost-effective strategy to eradicate the disease.
Integrating packing and distribution problems and optimization through mathematical programming
Directory of Open Access Journals (Sweden)
Fabio Miguel
2016-06-01
Full Text Available This paper analyzes the integration of two combinatorial problems that frequently arise in production and distribution systems. One is the Bin Packing Problem (BPP problem, which involves finding an ordering of some objects of different volumes to be packed into the minimal number of containers of the same or different size. An optimal solution to this NP-Hard problem can be approximated by means of meta-heuristic methods. On the other hand, we consider the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW, which is a variant of the Travelling Salesman Problem (again a NP-Hard problem with extra constraints. Here we model those two problems in a single framework and use an evolutionary meta-heuristics to solve them jointly. Furthermore, we use data from a real world company as a test-bed for the method introduced here.
Directory of Open Access Journals (Sweden)
Yuriy Michaylovich Chinyuchin
2017-01-01
Full Text Available The consistency of the potential increase of fuel efficiency, based on aircraft maintenance optimization, is mathe- matically proved. The mathematical apparatus and a set mathematical model of aircraft spatial motion allow to analyze aircraft behavior on the stage before landing and to draw optimal flight path for minimum fuel consumption with fixed time.For effective problem solving the choice and realization of optimal flight paths are made. The algorithm for the problem of optimal civil aircraft flight control aimed at the most accurate realization of chosen soft path under limited time conditions is proposed. The optimization of the given process is made by solving a point-to-point boundary canonical sys- tem based on the Pontryagin maximum principle.The necessary initial data and conditions for the statement of problem are given. The mathematical model for the simplification of calculations is created and its equivalent representation is given by uniting problems of controls by thrust channels and the angle of attack as the thrust control function. The boundary-value problem is mathematically composed and the analytical apparatus of its solution is presented. Optimal aircraft landing paths reflecting the behavior of the angle of attack and thrust are constructed. The potential of this method is proved by the economic justifiability and its effectiveness, in particular the compar- ison of total aircraft fuel consumption on obtained optimal path to the classic path on which there are rectilinear sections what allowed to confirm the conclusion about the economical expedience and effectiveness of the method of aircraft con- stant landing while making flights.
Freeman-Green, Shaqwana M.; O'Brien, Chris; Wood, Charles L.; Hitt, Sara Beth
2015-01-01
This study examined the effects of explicit instruction in the SOLVE Strategy on the mathematical problem solving skills of six Grade 8 students with specific learning disabilities. The SOLVE Strategy is an explicit instruction, mnemonic-based learning strategy designed to help students in solving mathematical word problems. Using a multiple probe…
Enhancing students’ mathematical problem posing skill through writing in performance tasks strategy
Kadir; Adelina, R.; Fatma, M.
2018-01-01
Many researchers have studied the Writing in Performance Task (WiPT) strategy in learning, but only a few paid attention on its relation to the problem-posing skill in mathematics. The problem-posing skill in mathematics covers problem reformulation, reconstruction, and imitation. The purpose of the present study was to examine the effect of WiPT strategy on students’ mathematical problem-posing skill. The research was conducted at a Public Junior Secondary School in Tangerang Selatan. It used a quasi-experimental method with randomized control group post-test. The samples were 64 students consists of 32 students of the experiment group and 32 students of the control. A cluster random sampling technique was used for sampling. The research data were obtained by testing. The research shows that the problem-posing skill of students taught by WiPT strategy is higher than students taught by a conventional strategy. The research concludes that the WiPT strategy is more effective in enhancing the students’ mathematical problem-posing skill compared to the conventional strategy.
Optimal generator bidding strategies for power and ancillary services
Morinec, Allen G.
As the electric power industry transitions to a deregulated market, power transactions are made upon price rather than cost. Generator companies are interested in maximizing their profits rather than overall system efficiency. A method to equitably compensate generation providers for real power, and ancillary services such as reactive power and spinning reserve, will ensure a competitive market with an adequate number of suppliers. Optimizing the generation product mix during bidding is necessary to maximize a generator company's profits. The objective of this research work is to determine and formulate appropriate optimal bidding strategies for a generation company in both the energy and ancillary services markets. These strategies should incorporate the capability curves of their generators as constraints to define the optimal product mix and price offered in the day-ahead and real time spot markets. In order to achieve such a goal, a two-player model was composed to simulate market auctions for power generation. A dynamic game methodology was developed to identify Nash Equilibria and Mixed-Strategy Nash Equilibria solutions as optimal generation bidding strategies for two-player non-cooperative variable-sum matrix games with incomplete information. These games integrated the generation product mix of real power, reactive power, and spinning reserve with the generators's capability curves as constraints. The research includes simulations of market auctions, where strategies were tested for generators with different unit constraints, costs, types of competitors, strategies, and demand levels. Studies on the capability of large hydrogen cooled synchronous generators were utilized to derive useful equations that define the exact shape of the capability curve from the intersections of the arcs defined by the centers and radial vectors of the rotor, stator, and steady-state stability limits. The available reactive reserve and spinning reserve were calculated given a
Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.
Directory of Open Access Journals (Sweden)
Nadia Said
Full Text Available Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.
Application of optimal interation strategies to diffusion theory calculations
International Nuclear Information System (INIS)
Jones, R.B.
1978-01-01
The geometric interpretation of optimal (minimum computational time) iteration strategies is applied to one- and two-group, two-dimensional diffusion-theory calculations. The method is a ''spectral/time balance'' technique which weighs the convergence enhancement of the inner iteration procedure with that of the outer iteration loop and the time required to reconstruct the source. The diffusion-theory option of the discrete-ordinates transport code DOT3.5 was altered to incorporate the theoretical inner/outer decision logic. For the two-dimensional configuration considered, the optimal strategies reduced the total number of iterations performed for a given error criterion
Reliability optimization of series–parallel systems with mixed redundancy strategy in subsystems
International Nuclear Information System (INIS)
Abouei Ardakan, Mostafa; Zeinal Hamadani, Ali
2014-01-01
Traditionally in redundancy allocation problem (RAP), it is assumed that the redundant components are used based on a predefined active or standby strategies. Recently, some studies consider the situation that both active and standby strategies can be used in a specific system. However, these researches assume that the redundancy strategy for each subsystem can be either active or standby and determine the best strategy for these subsystems by using a proper mathematical model. As an extension to this assumption, a novel strategy, that is a combination of traditional active and standby strategies, is introduced. The new strategy is called mixed strategy which uses both active and cold-standby strategies in one subsystem simultaneously. Therefore, the problem is to determine the component type, redundancy level, number of active and cold-standby units for each subsystem in order to maximize the system reliability. To have a more practical model, the problem is formulated with imperfect switching of cold-standby redundant components and k-Erlang time-to-failure (TTF) distribution. As the optimization of RAP belongs to NP-hard class of problems, a genetic algorithm (GA) is developed. The new strategy and proposed GA are implemented on a well-known test problem in the literature which leads to interesting results. - Highlights: • In this paper the redundancy allocation problem (RAP) for a series–parallel system is considered. • Traditionally there are two main strategies for redundant component namely active and standby. • In this paper a new redundancy strategy which is called “Mixed” redundancy strategy is introduced. • Computational experiments demonstrate that implementing the new strategy lead to interesting results
Optimization Under Uncertainty for Wake Steering Strategies: Preprint
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-05-01
Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.
Elementary Teachers' Perspectives of Mathematics Problem Solving Strategies
Bruun, Faye
2013-01-01
Participants in this study were asked to report what strategies were most often used in their attempts to foster their students' problem solving abilities. Participants included 70 second through fifth-grade elementary teachers from 42 schools in a large state of the south central region in the U.S. Data analyses of the interviews revealed that…
House, J Daniel
2007-04-01
Recent findings concerning mathematics assessment indicate that students in Japan consistently score above international averages. Researchers have examined specific mathematics beliefs and instructional strategies associated with mathematics achievement for students in Japan. This study examined relationships among self-beliefs, classroom instructional strategies, and mathematics achievement for a large national sample of students (N=4,207) from the TIMSS 2003 international sample of fourth graders in Japan. Several significant relationships between mathematics beliefs and test scores were found; a number of classroom teaching strategies were also significantly associated with test scores. However, multiple regression using the complete set of five mathematics beliefs and five instructional strategies explained only 25.1% of the variance in mathematics achievement test scores.
Directory of Open Access Journals (Sweden)
Neisy Rodríguez Morales
2014-03-01
Full Text Available The article shows the theoretical elements related with the conception of the curricular strategies and its instrumentation in the process of the student's of the Mathematical career formation - Physics. Examples are presented that demonstrate how to deal with the computer science's curricular strategy from the teaching process - learning of the subject Algebra I in the third year of the career. They give the possibility that the formation process be more effective, they facilitate the systematizing knowledge and abilities as well as the development of the integral general culture in the future professors of Mathematics - Physics.
Optimal football strategies: AC Milan versus FC Barcelona
Papahristodoulou, Christos
2012-01-01
In a recent UEFA Champions League game between AC Milan and FC Barcelona, played in Italy (final score 2-3), the collected match statistics, classified into four offensive and two defensive strategies, were in favour of FC Barcelona (by 13 versus 8 points). The aim of this paper is to examine to what extent the optimal game strategies derived from some deterministic, possibilistic, stochastic and fuzzy LP models would improve the payoff of AC Milan at the cost of FC Barcelona.
PROBLEM SOLVING IN SCHOOL MATHEMATICS BASED ON HEURISTIC STRATEGIES
Directory of Open Access Journals (Sweden)
NOVOTNÁ, Jarmila
2014-03-01
Full Text Available The paper describes one of the ways of developing pupils’ creative approach to problem solving. The described experiment is a part of a longitudinal research focusing on improvement of culture of problem solving by pupils. It deals with solving of problems using the following heuristic strategies: Analogy, Guess – check – revise, Systematic experimentation, Problem reformulation, Solution drawing, Way back and Use of graphs of functions. Most attention is paid to the question whether short-term work, in this case only over the period of three months, can result in improvement of pupils’ abilities to solve problems whose solving algorithms are easily accessible. It also answers the question which strategies pupils will prefer and with what results. The experiment shows that even short-term work can bear positive results as far as pupils’ approach to problem solving is concerned.
Optimal decentralized valley-filling charging strategy for electric vehicles
International Nuclear Information System (INIS)
Zhang, Kangkang; Xu, Liangfei; Ouyang, Minggao; Wang, Hewu; Lu, Languang; Li, Jianqiu; Li, Zhe
2014-01-01
Highlights: • An implementable charging strategy is developed for electric vehicles connected to a grid. • A two-dimensional pricing scheme is proposed to coordinate charging behaviors. • The strategy effectively works in decentralized way but achieves the systematic valley filling. • The strategy allows device-level charging autonomy, and does not require a bidirectional communication/control network. • The strategy can self-correct when confronted with adverse factors. - Abstract: Uncoordinated charging load of electric vehicles (EVs) increases the peak load of the power grid, thereby increasing the cost of electricity generation. The valley-filling charging scenario offers a cheaper alternative. This study proposes a novel decentralized valley-filling charging strategy, in which a day-ahead pricing scheme is designed by solving a minimum-cost optimization problem. The pricing scheme can be broadcasted to EV owners, and the individual charging behaviors can be indirectly coordinated. EV owners respond to the pricing scheme by autonomously optimizing their individual charge patterns. This device-level response induces a valley-filling effect in the grid at the system level. The proposed strategy offers three advantages: coordination (by the valley-filling effect), practicality (no requirement for a bidirectional communication/control network between the grid and EV owners), and autonomy (user control of EV charge patterns). The proposed strategy is validated in simulations of typical scenarios in Beijing, China. According to the results, the strategy (1) effectively achieves the valley-filling charging effect at 28% less generation cost than the uncoordinated charging strategy, (2) is robust to several potential affecters of the valley-filling effect, such as (system-level) inaccurate parameter estimation and (device-level) response capability and willingness (which cause less than 2% deviation in the minimal generation cost), and (3) is compatible with
International Nuclear Information System (INIS)
Safari, Jalal
2012-01-01
This paper proposes a variant of the Non-dominated Sorting Genetic Algorithm (NSGA-II) to solve a novel mathematical model for multi-objective redundancy allocation problems (MORAP). Most researchers about redundancy allocation problem (RAP) have focused on single objective optimization, while there has been some limited research which addresses multi-objective optimization. Also all mathematical multi-objective models of general RAP assume that the type of redundancy strategy for each subsystem is predetermined and known a priori. In general, active redundancy has traditionally received greater attention; however, in practice both active and cold-standby redundancies may be used within a particular system design. The choice of redundancy strategy then becomes an additional decision variable. Thus, the proposed model and solution method are to select the best redundancy strategy, type of components, and levels of redundancy for each subsystem that maximizes the system reliability and minimize total system cost under system-level constraints. This problem belongs to the NP-hard class. This paper presents a second-generation Multiple-Objective Evolutionary Algorithm (MOEA), named NSGA-II to find the best solution for the given problem. The proposed algorithm demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker (DM) with a complete picture of the optimal solution space. After finding the Pareto front, a procedure is used to select the best solution from the Pareto front. Finally, the advantages of the presented multi-objective model and of the proposed algorithm are illustrated by solving test problems taken from the literature and the robustness of the proposed NSGA-II is discussed.
International Nuclear Information System (INIS)
Dikij, N.P.; Rudychev, Y.V.; Fedorchenko, D.V.; Khazhmuradov, M.A.
2014-01-01
This paper considers a method for 67 Cu isotope production using electron bremsstrahlung by the 68 Zn(gamma, p) 67 Cu reaction. The facility for 67 Cu isotope production contains an electron accelerator, electron-gamma converter and zinc target. To optimize this facility we developed three-dimensional model of the converter and the target. Using this model, we performed the mathematical modeling of zinc target irradiation and thermal-hydraulic processes inside the target for various parameters of the electron beam and converter configurations. For mathematical modeling of radiation processes we used the MCNPX software. Thermal-hydraulic simulation utilized the commercial SolidWorks software with Flow Simulation module. Mathematical modeling revealed that efficient 67 Cu isotope production needs smaller beam diameter and higher electron energy. Under these conditions target heat power also increases, thus additional cooling is necessary. If the beam diameter and the electron energy are fixed the most effective method to satisfy the operating parameters and retain an efficient isotope yield is to optimize photonuclear spectra of the target by variation of converter thickness. We developed an algorithm for multicriterion optimization and performed the optimization of the facility with account to coupled radiation and heat transfer processes.
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be new…
Optimal portfolio strategies under a shortfall constraint | Akume ...
African Journals Online (AJOL)
We impose dynamically, a shortfall constraint in terms of Tail Conditional Expectation on the portfolio selection problem in continuous time, in order to obtain optimal strategies. The nancial market is assumed to comprise n risky assets driven by geometric Brownian motion and one risk-free asset. The method of Lagrange ...
Optimal energy management strategy for battery powered electric vehicles
International Nuclear Information System (INIS)
Xi, Jiaqi; Li, Mian; Xu, Min
2014-01-01
Highlights: • The power usage for battery-powered electrical vehicles with in-wheel motors is maximized. • The battery and motor dynamics are examined emphasized on the power conversion and utilization. • The optimal control strategy is derived and verified by simulations. • An analytic expression of the optimal operating point is obtained. - Abstract: Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios
Validation of optimization strategies using the linear structured production chains
Kusiak, Jan; Morkisz, Paweł; Oprocha, Piotr; Pietrucha, Wojciech; Sztangret, Łukasz
2017-06-01
Different optimization strategies applied to sequence of several stages of production chains were validated in this paper. Two benchmark problems described by ordinary differential equations (ODEs) were considered. A water tank and a passive CR-RC filter were used as the exemplary objects described by the first and the second order differential equations, respectively. Considered in the work optimization problems serve as the validators of strategies elaborated by the Authors. However, the main goal of research is selection of the best strategy for optimization of two real metallurgical processes which will be investigated in an on-going projects. The first problem will be the oxidizing roasting process of zinc sulphide concentrate where the sulphur from the input concentrate should be eliminated and the minimal concentration of sulphide sulphur in the roasted products has to be achieved. Second problem will be the lead refining process consisting of three stages: roasting to the oxide, oxide reduction to metal and the oxidizing refining. Strategies, which appear the most effective in considered benchmark problems will be candidates for optimization of the mentioned above industrial processes.
Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Yuan Zou
2013-01-01
Full Text Available A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.
Growth or reproduction: emergence of an evolutionary optimal strategy
International Nuclear Information System (INIS)
Grilli, J; Suweis, S; Maritan, A
2013-01-01
Modern ecology has re-emphasized the need for a quantitative understanding of the original ‘survival of the fittest theme’ based on analysis of the intricate trade-offs between competing evolutionary strategies that characterize the evolution of life. This is key to the understanding of species coexistence and ecosystem diversity under the omnipresent constraint of limited resources. In this work we propose an agent-based model replicating a community of interacting individuals, e.g. plants in a forest, where all are competing for the same finite amount of resources and each competitor is characterized by a specific growth–reproduction strategy. We show that such an evolution dynamics drives the system towards a stationary state characterized by an emergent optimal strategy, which in turn depends on the amount of available resources the ecosystem can rely on. We find that the share of resources used by individuals is power-law distributed with an exponent directly related to the optimal strategy. The model can be further generalized to devise optimal strategies in social and economical interacting systems dynamics. (paper)
Contributions of Neuroscience to Develop Teaching Strategies and Learning of Mathematics
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Eddy Mogollón
2010-12-01
Full Text Available The goal of the present work is to develop some strategies based on research in neurosciences that contribute to the teaching and learning of mathematics. The interrelationship of education with the brain, as well as the relationship of cerebral structures with mathematical thinking was discussed. Strategies were developed taking into consideration levels that include cognitive, semiotic, language, affect and the overcoming of phobias to the subject. The fundamental conclusion was the imperative educational requirement in the near future of a new teacher, whose pedagogic formation must include the knowledge on the cerebral function, its structures and its implications to education, as well as a change in pedagogy and curricular structure in the teaching of mathematics.
Jitendra, Asha K; Petersen-Brown, Shawna; Lein, Amy E; Zaslofsky, Anne F; Kunkel, Amy K; Jung, Pyung-Gang; Egan, Andrea M
2015-01-01
This study examined the quality of the research base related to strategy instruction priming the underlying mathematical problem structure for students with learning disabilities and those at risk for mathematics difficulties. We evaluated the quality of methodological rigor of 18 group research studies using the criteria proposed by Gersten et al. and 10 single case design (SCD) research studies using criteria suggested by Horner et al. and the What Works Clearinghouse. Results indicated that 14 group design studies met the criteria for high-quality or acceptable research, whereas SCD studies did not meet the standards for an evidence-based practice. Based on these findings, strategy instruction priming the mathematics problem structure is considered an evidence-based practice using only group design methodological criteria. Implications for future research and for practice are discussed. © Hammill Institute on Disabilities 2013.
Online gaming for learning optimal team strategies in real time
Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.
2010-04-01
This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.
Artificial root foraging optimizer algorithm with hybrid strategies
Directory of Open Access Journals (Sweden)
Yang Liu
2017-02-01
Full Text Available In this work, a new plant-inspired optimization algorithm namely the hybrid artificial root foraging optimizion (HARFO is proposed, which mimics the iterative root foraging behaviors for complex optimization. In HARFO model, two innovative strategies were developed: one is the root-to-root communication strategy, which enables the individual exchange information with each other in different efficient topologies that can essentially improve the exploration ability; the other is co-evolution strategy, which can structure the hierarchical spatial population driven by evolutionary pressure of multiple sub-populations that ensure the diversity of root population to be well maintained. The proposed algorithm is benchmarked against four classical evolutionary algorithms on well-designed test function suites including both classical and composition test functions. Through the rigorous performance analysis that of all these tests highlight the significant performance improvement, and the comparative results show the superiority of the proposed algorithm.
Sari, Delsika Pramata; Darhim; Rosjanuardi, Rizky
2018-01-01
The purpose of this study was to investigate the errors experienced by students learning with REACT strategy and traditional learning in solving problems of mathematical representation ability. This study used quasi experimental pattern with static-group comparison design. The subjects of this study were 47 eighth grade students of junior high…
Comparison of Learning Strategies for Mathematics Achievement in Turkey with Eight Countries
Kilic, Serpil; Cene, Erhan; Demir, Ibrahim
2012-01-01
The purpose of this study was to examine learning strategies accounted for mathematics achievement across Turkey and neighboring countries. Turkey, Bulgaria, Greece, Azerbaijan, Russian Federation, Israel, Serbia, Romania and Jordan were involved in Programme for International Student Assessment (PISA 2009) study. Since other neighbors of Turkey…
Reduce, Reuse, Recycle: Resources and Strategies for the Use of Writing Projects in Mathematics
Latulippe, Joe; Latulippe, Christine
2014-01-01
As an often recommended but under-utilized pedagogical strategy, writing in mathematics has many benefits for students. However, creating and grading worthwhile writing projects can be more time-consuming than utilizing more traditional forms of assessment. This paper provides a concrete example of a writing project prompt, questions, directions,…
Teachers' Views about Multiple Strategies in Middle and High School Mathematics
Lynch, Kathleen; Star, Jon R.
2014-01-01
Despite extensive scholarship about the importance of teaching mathematics with multiple strategies in the elementary grades, there has been relatively little discussion of this practice in the middle and high school levels or in the context of introductory algebra. This article begins our exploration of this practice by addressing the following…
Problem Solving Strategies of Selected Pre-Service Secondary School Mathematics Teachers in Malaysia
Yew, Wun Theam; Zamri, Sharifah Norul Akmar Syed
2016-01-01
Problem solving strategies of eight pre-service secondary school mathematics teachers (PSSMTs) were examined in this study. A case study research design was employed and clinical interview technique was used to collect the data. Materials collected for analysis consisted of audiotapes and videotapes of clinical interviews, subjects' notes and…
Advancing Inclusive Mathematics Education: Strategies and Resources for Effective IEP Practices
Tan, Paulo
2017-01-01
Personal experiences promoting inclusive mathematics education for my own child have mostly been met with staunch resistance on the part of educators, and a resulting breakdown in collaborative efforts during individualized education program (IEP) meetings. However, I found that utilizing certain strategies and introducing innovative mathematics…
Problem Solving Strategies of Girls and Boys in Single-Sex Mathematics Classrooms
Che, Megan; Wiegert, Elaine; Threlkeld, Karen
2012-01-01
This study examines patterns in middle-grade boys' and girls' written problem solving strategies for a mathematical task involving proportional reasoning. The students participating in this study attend a coeducational charter middle school with single-sex classrooms. One hundred nineteen sixth-grade students' responses are analyzed by gender…
Turner, Julianne C.; Midgley, Carol; Meyer, Debra K.; Gheen, Margaret; Anderman, Eric M.; Kang, Yongjin; Patrick, Helen
2002-01-01
The relation between learning environment (perceptions of classroom goal structure and teachers' instructional discourse) and students' reported use of avoidance strategies (self-handicapping, avoidance of help seeking) and preference to avoid novelty in mathematics was examined. High incidence of motivational support was uniquely characteristic…
Badru, Ademola K.
2016-01-01
The study investigated Problem-based Instructional Strategy and Numerical ability as determinants of Senior Secondary Achievement in Mathematics. This study used 4 x 2 x 2 non-randomised control group Pretest-Posttest Quasi-experimental Factorial design. It consisted of two independent variables (treatment and Numerical ability) and one moderating…
Chatzistamatiou, Mariza; Dermitzaki, Irini; Efklides, Anastasia; Leondari, Angeliki
2015-01-01
The aim of the study was to investigate the relationships between elementary students' reported use of self-regulatory strategies in mathematics and their motivational and affective determinants. Participants of the study were 344 fifth- and sixth-grade Greek students. Students were asked to complete self-reported measures regarding the strategies…
Directory of Open Access Journals (Sweden)
Zili Zhang
Full Text Available Bi-objective Traveling Salesman Problem (bTSP is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM. PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.
Zhao, Hui; Wei, Jingxuan
2014-09-01
The key to the concept of tunable wavefront coding lies in detachable phase masks. Ojeda-Castaneda et al. (Progress in Electronics Research Symposium Proceedings, Cambridge, USA, July 5-8, 2010) described a typical design in which two components with cosinusoidal phase variation operate together to make defocus sensitivity tunable. The present study proposes an improved design and makes three contributions: (1) A mathematical derivation based on the stationary phase method explains why the detachable phase mask of Ojeda-Castaneda et al. tunes the defocus sensitivity. (2) The mathematical derivations show that the effective bandwidth wavefront coded imaging system is also tunable by making each component of the detachable phase mask move asymmetrically. An improved Fisher information-based optimization procedure was also designed to ascertain the optimal mask parameters corresponding to specific bandwidth. (3) Possible applications of the tunable bandwidth are demonstrated by simulated imaging.
Eringen, A Cemal
2013-01-01
Continuum Physics: Volume 1 - Mathematics is a collection of papers that discusses certain selected mathematical methods used in the study of continuum physics. Papers in this collection deal with developments in mathematics in continuum physics and its applications such as, group theory functional analysis, theory of invariants, and stochastic processes. Part I explains tensor analysis, including the geometry of subspaces and the geometry of Finsler. Part II discusses group theory, which also covers lattices, morphisms, and crystallographic groups. Part III reviews the theory of invariants th
International Nuclear Information System (INIS)
Vieira, Leonardo S.; Donatelli, Joao L.; Cruz, Manuel E.
2006-01-01
In this work we present the development and implementation of an integrated approach for mathematical exergoeconomic optimization of complex thermal systems. By exploiting the computational power of a professional process simulator, the proposed integrated approach permits the optimization routine to ignore the variables associated with the thermodynamic balance equations and thus deal only with the decision variables. To demonstrate the capabilities of the integrated approach, it is here applied to a complex cogeneration system, which includes all the major components of a typical thermal plant, and requires more than 800 variables for its simulation
Image de-noising based on mathematical morphology and multi-objective particle swarm optimization
Dou, Liyun; Xu, Dan; Chen, Hao; Liu, Yicheng
2017-07-01
To overcome the problem of image de-noising, an efficient image de-noising approach based on mathematical morphology and multi-objective particle swarm optimization (MOPSO) is proposed in this paper. Firstly, constructing a series and parallel compound morphology filter based on open-close (OC) operation and selecting a structural element with different sizes try best to eliminate all noise in a series link. Then, combining multi-objective particle swarm optimization (MOPSO) to solve the parameters setting of multiple structural element. Simulation result shows that our algorithm can achieve a superior performance compared with some traditional de-noising algorithm.
International Nuclear Information System (INIS)
Sutrisno; Widowati; Solikhin
2016-01-01
In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well. (paper)
Keren, Baruch; Pliskin, Joseph S
2011-12-01
The optimal timing for performing radical medical procedures as joint (e.g., hip) replacement must be seriously considered. In this paper we show that under deterministic assumptions the optimal timing for joint replacement is a solution of a mathematical programming problem, and under stochastic assumptions the optimal timing can be formulated as a stochastic programming problem. We formulate deterministic and stochastic models that can serve as decision support tools. The results show that the benefit from joint replacement surgery is heavily dependent on timing. Moreover, for a special case where the patient's remaining life is normally distributed along with a normally distributed survival of the new joint, the expected benefit function from surgery is completely solved. This enables practitioners to draw the expected benefit graph, to find the optimal timing, to evaluate the benefit for each patient, to set priorities among patients and to decide if joint replacement should be performed and when.
On the robust optimization to the uncertain vaccination strategy problem
International Nuclear Information System (INIS)
Chaerani, D.; Anggriani, N.; Firdaniza
2014-01-01
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented
On the robust optimization to the uncertain vaccination strategy problem
Energy Technology Data Exchange (ETDEWEB)
Chaerani, D., E-mail: d.chaerani@unpad.ac.id; Anggriani, N., E-mail: d.chaerani@unpad.ac.id; Firdaniza, E-mail: d.chaerani@unpad.ac.id [Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Padjadjaran Indonesia, Jalan Raya Bandung Sumedang KM 21 Jatinangor Sumedang 45363 (Indonesia)
2014-02-21
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.
Generating optimized stochastic power management strategies for electric car components
Energy Technology Data Exchange (ETDEWEB)
Fruth, Matthias [TraceTronic GmbH, Dresden (Germany); Bastian, Steve [Technische Univ. Dresden (Germany)
2012-11-01
With the increasing prevalence of electric vehicles, reducing the power consumption of car components becomes a necessity. For the example of a novel traffic-light assistance system, which makes speed recommendations based on the expected length of red-light phases, power-management strategies are used to control under which conditions radio communication, positioning systems and other components are switched to low-power (e.g. sleep) or high-power (e.g. idle/busy) states. We apply dynamic power management, an optimization technique well-known from other domains, in order to compute energy-optimal power-management strategies, sometimes resulting in these strategies being stochastic. On the example of the traffic-light assistant, we present a MATLAB/Simulink-implemented framework for the generation, simulation and formal analysis of optimized power-management strategies, which is based on this technique. We study capabilities and limitations of this approach and sketch further applications in the automotive domain. (orig.)
Application of optimal control strategies to HIV-malaria co-infection dynamics
Fatmawati; Windarto; Hanif, Lathifah
2018-03-01
This paper presents a mathematical model of HIV and malaria co-infection transmission dynamics. Optimal control strategies such as malaria preventive, anti-malaria and antiretroviral (ARV) treatments are considered into the model to reduce the co-infection. First, we studied the existence and stability of equilibria of the presented model without control variables. The model has four equilibria, namely the disease-free equilibrium, the HIV endemic equilibrium, the malaria endemic equilibrium, and the co-infection equilibrium. We also obtain two basic reproduction ratios corresponding to the diseases. It was found that the disease-free equilibrium is locally asymptotically stable whenever their respective basic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. sic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. Then, the optimal control theory for the model was derived analytically by using Pontryagin Maximum Principle. Numerical simulations of the optimal control strategies are also performed to illustrate the results. From the numerical results, we conclude that the best strategy is to combine the malaria prevention and ARV treatments in order to reduce malaria and HIV co-infection populations.
Control strategies for wind farm power optimization: LES study
Ciri, Umberto; Rotea, Mario; Leonardi, Stefano
2017-11-01
Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.
Automatic CT simulation optimization for radiation therapy: A general strategy.
Li, Hua; Yu, Lifeng; Anastasio, Mark A; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M; Low, Daniel A; Mutic, Sasa
2014-03-01
In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube potentials for patient sizes
Automatic CT simulation optimization for radiation therapy: A general strategy
Energy Technology Data Exchange (ETDEWEB)
Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M.; Mutic, Sasa [Department of Radiation Oncology, Washington University, St. Louis, Missouri 63110 (United States); Yu, Lifeng [Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905 (United States); Anastasio, Mark A. [Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63110 (United States); Low, Daniel A. [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California 90095 (United States)
2014-03-15
Purpose: In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. Methods: The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Results: Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube
Strategy for integration of coastal culture in learning process of mathematics in junior high school
Suyitno, H.; Zaenuri; Florentinus, T. S.; Zakaria, E.
2018-03-01
Traditional life in the fishing family is part of the local culture. Many School-age children in the fishing family drop-outs due to lack of parents motivation and the environment was less supportive. The problems were: (1) How the strategy of integration of local culture in learning process of mathematics in Junior High School (JHS)? (2) How to prepare the Mathematics Student’s Book for grade 7 of JHS that based on coastal culture, that has an ISBN, has international level, applicable, and in accordance with the current curriculum? The purposes of this research were: (1) to obtain the strategy of integration of local culture in learning process of mathematics in JHS, through FGD between UNNES and UKM; (2) to obtain the experts validation, through Focus Group Discussion (FGD) between UNNES and UKM toward the draft of the Mathematics Student’s Book for grade 7 of JHS that based on coastal culture; (3) produces Mathematics Student’s Book for grade 7 SMP which based on coastal culture and has an ISBN, international, applicable, and in accordance with the curriculum. The research activity was a qualitative research, so that the research methods include: (1) data reduction, (2) display data, (3) data interpretation, and (4) conclusion/verification. The main activities of this research: drafting the Mathematics Student’s Book of Grade 7 which based on coastal culture; get the validation from international partners;conducting FGD at Education Faculty of Universiti Kebangsaan Malaysia through the program of visiting lecturers for getting the Mathematics Student’s Book of grade 7 which based on coastal culture, registering for ISBN, and publishing the reasearch results in International seminar and International Journals. The results of this research were as follows. (1) Getting a good strategy for integration of local culture in learning process of mathematics in JHS. (2) Getting the Mathematics Student’s Book for grade 7 of JHS that based on coastal culture
Caviola, Sara; Carey, Emma; Mammarella, Irene C; Szucs, Denes
2017-01-01
We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth "strategy selection") in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations), with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research.
Eye Movements Reveal Optimal Strategies for Analogical Reasoning.
Vendetti, Michael S; Starr, Ariel; Johnson, Elizabeth L; Modavi, Kiana; Bunge, Silvia A
2017-01-01
Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D). We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.
Eye Movements Reveal Optimal Strategies for Analogical Reasoning
Directory of Open Access Journals (Sweden)
Michael S. Vendetti
2017-06-01
Full Text Available Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D. We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.
Optimal intervention strategies for cholera outbreak by education and chlorination
Bakhtiar, Toni
2016-01-01
This paper discusses the control of infectious diseases in the framework of optimal control approach. A case study on cholera control was studied by considering two control strategies, namely education and chlorination. We distinct the former control into one regarding person-to-person behaviour and another one concerning person-to-environment conduct. Model are divided into two interacted populations: human population which follows an SIR model and pathogen population. Pontryagin maximum principle was applied in deriving a set of differential equations which consists of dynamical and adjoin systems as optimality conditions. Then, the fourth order Runge-Kutta method was exploited to numerically solve the equation system. An illustrative example was provided to assess the effectiveness of the control strategies toward a set of control scenarios.
Wijayanti, R.; Waluya, S. B.; Masrukan
2018-03-01
The purpose of this research are (1) to analyze the learning quality of MEAs with MURDER strategy, (2) to analyze students’ mathematical literacy ability based on goal orientation in MEAs learning with MURDER strategy. This research is a mixed method research of concurrent embedded type where qualitative method as the primary method. The data were obtained using the methods of scale, observation, test and interviews. The results showed that (1) MEAs Learning with MURDER strategy on students' mathematical literacy ability is qualified, (2) Students who have mastery goal characteristics are able to master the seven components of mathematical literacy process although there are still two components that the solution is less than the maximum. Students who have performance goal characteristics have not mastered the components of mathematical literacy process with the maximum, they are only able to master the ability of using mathematics tool and the other components of mathematical literacy process is quite good.
Turbine Control Strategies for Wind Farm Power Optimization
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor
2015-01-01
In recent decades there has been increasing interest in green energies, of which wind energy is the most important one. In order to improve the competitiveness of the wind power plants, there are ongoing researches to decrease cost per energy unit and increase the efficiency of wind turbines...... and wind farms. One way of achieving these goals is to optimize the power generated by a wind farm. One optimization method is to choose appropriate operating points for the individual wind turbines in the farm. We have made three models of a wind farm based on three difference control strategies...... the generated power by changing the power reference of the individual wind turbines. We use the optimization setup to compare power production of the wind farm models. This paper shows that for the most frequent wind velocities (below and around the rated values), the generated powers of the wind farms...
Optimal sampling strategies for detecting zoonotic disease epidemics.
Directory of Open Access Journals (Sweden)
Jake M Ferguson
2014-06-01
Full Text Available The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
Optimal sampling strategies for detecting zoonotic disease epidemics.
Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W
2014-06-01
The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
International Nuclear Information System (INIS)
Godoy, E.; Benz, S.J.; Scenna, N.J.
2011-01-01
Optimal combined cycle gas turbine power plants characterized by minimum specific annual cost values are here determined for wide ranges of market conditions as given by the relative weights of capital investment and operative costs, by means of a non-linear mathematical programming model. On the other hand, as the technical optimization allows identifying trends in the system behavior and unveiling optimization opportunities, selected functional relationships are obtained as the thermodynamic optimal values of the decision variables are systematically linked to the ratio between the total heat transfer area and the net power production (here named as specific transfer area). A strategy for simplifying the resolution of the rigorous economic optimization problem of power plants is proposed based on the economic optima distinctive characteristics which describe the behavior of the decision variables of the power plant on its optima. Such approach results in a novel mathematical formulation shaped as a system of non-linear equations and additional constraints that is able to easily provide accurate estimations of the optimal values of the power plant design and operative variables. Research highlights: → We achieve relationships between power plants' economic and thermodynamic optima. → We achieve functionalities among thermodynamic optimal values of decision variables. → The rigorous optimization problem is reduced to a non-linear equations system. → Accurate estimations of power plants' design and operative variables are obtained.
Optimal mission planning of GEO on-orbit refueling in mixed strategy
Chen, Xiao-qian; Yu, Jing
2017-04-01
The mission planning of GEO on-orbit refueling (OOR) in Mixed strategy is studied in this paper. Specifically, one SSc will be launched to an orbital slot near the depot when multiple GEO satellites are reaching their end of lives. The SSc replenishes fuel from the depot and then extends the lifespan of the target satellites via refueling. In the mixed scenario, only some of the target satellites could be served by the SSc, and the remaining ones will be fueled by Pseudo SScs (the target satellite which has already been refueled by the SSc and now has sufficient fuel for its operation as well as the fuel to refuel other target satellites is called Pseudo SSc here). The mission sequences and fuel mass of the SSc and Pseudo SScs, the dry mass of the SSc are used as design variables, whereas the economic benefit of the whole mission is used as design objective. The economic cost and benefit models are stated first, and then a mathematical optimization model is proposed. A comprehensive solution method involving enumeration, particle swarm optimization and modification is developed. Numerical examples are carried out to demonstrate the effectiveness of the model and solution method. Economic efficiencies of different OOR strategies are compared and discussed. The mixed strategy would perform better than the other strategies only when the target satellites satisfy some conditions. This paper presents an available mixed strategy scheme for users and analyzes its advantages and disadvantages by comparing with some other OOR strategies, providing helpful references to decision makers. The best strategy in practical applications depends on the specific demands and user preference.
Global optimization numerical strategies for rate-independent processes
Czech Academy of Sciences Publication Activity Database
Benešová, Barbora
2011-01-01
Roč. 50, č. 2 (2011), s. 197-220 ISSN 0925-5001 R&D Projects: GA ČR GAP201/10/0357 Grant - others:GA MŠk(CZ) LC06052 Program:LC Institutional research plan: CEZ:AV0Z20760514 Keywords : rate-independent processes * numerical global optimization * energy estimates based algorithm Subject RIV: BA - General Mathematics Impact factor: 1.196, year: 2011 http://math.hnue.edu.vn/portal/rss.viewpage.php?id=0000037780&ap=L3BvcnRhbC9ncmFiYmVyLnBocD9jYXRpZD0xMDEyJnBhZ2U9Mg==
Stein, Sherman K
2010-01-01
Anyone can appreciate the beauty, depth, and vitality of mathematics with the help of this highly readable text, specially developed from a college course designed to appeal to students in a variety of fields. Readers with little mathematical background are exposed to a broad range of subjects chosen from number theory, topology, set theory, geometry, algebra, and analysis. Starting with a survey of questions on weight, the text discusses the primes, the fundamental theorem of arithmetic, rationals and irrationals, tiling, tiling and electricity, probability, infinite sets, and many other topi
Directory of Open Access Journals (Sweden)
Anne L. van de Ven
2012-03-01
Full Text Available Inefficient vascularization hinders the optimal transport of cell nutrients, oxygen, and drugs to cancer cells in solid tumors. Gradients of these substances maintain a heterogeneous cell-scale microenvironment through which drugs and their carriers must travel, significantly limiting optimal drug exposure. In this study, we integrate intravital microscopy with a mathematical model of cancer to evaluate the behavior of nanoparticle-based drug delivery systems designed to circumvent biophysical barriers. We simulate the effect of doxorubicin delivered via porous 1000 x 400 nm plateloid silicon particles to a solid tumor characterized by a realistic vasculature, and vary the parameters to determine how much drug per particle and how many particles need to be released within the vasculature in order to achieve remission of the tumor. We envision that this work will contribute to the development of quantitative measures of nanoparticle design and drug loading in order to optimize cancer treatment via nanotherapeutics.
Directory of Open Access Journals (Sweden)
Maciej Leszczyński
2017-01-01
Full Text Available We consider an optimal control problem for a general mathematical model of drug treatment with a single agent. The control represents the concentration of the agent and its effect (pharmacodynamics is modelled by a Hill function (i.e., Michaelis-Menten type kinetics. The aim is to minimize a cost functional consisting of a weighted average related to the state of the system (both at the end and during a fixed therapy horizon and to the total amount of drugs given. The latter is an indirect measure for the side effects of treatment. It is shown that optimal controls are continuous functions of time that change between full or no dose segments with connecting pieces that take values in the interior of the control set. Sufficient conditions for the strong local optimality of an extremal controlled trajectory in terms of the existence of a solution to a piecewise defined Riccati differential equation are given.
Directory of Open Access Journals (Sweden)
Narinder Singh
2018-03-01
Full Text Available The quest for an efficient nature-inspired optimization technique has continued over the last few decades. In this paper, a hybrid nature-inspired optimization technique has been proposed. The hybrid algorithm has been constructed using Mean Grey Wolf Optimizer (MGWO and Whale Optimizer Algorithm (WOA. We have utilized the spiral equation of Whale Optimizer Algorithm for two procedures in the Hybrid Approach GWO (HAGWO algorithm: (i firstly, we used the spiral equation in Grey Wolf Optimizer algorithm for balance between the exploitation and the exploration process in the new hybrid approach; and (ii secondly, we also applied this equation in the whole population in order to refrain from the premature convergence and trapping in local minima. The feasibility and effectiveness of the hybrid algorithm have been tested by solving some standard benchmarks, XOR, Baloon, Iris, Breast Cancer, Welded Beam Design, Pressure Vessel Design problems and comparing the results with those obtained through other metaheuristics. The solutions prove that the newly existing hybrid variant has higher stronger stability, faster convergence rate and computational accuracy than other nature-inspired metaheuristics on the maximum number of problems and can successfully resolve the function of constrained nonlinear optimization in reality.
Directory of Open Access Journals (Sweden)
I. V. Kuksova
2017-01-01
Full Text Available In this article a variant of the economic-mathematical substantiation of optimization approaches choice of tools for the survey of airfields, the mechanism of the use of multiple statistical criteria for optimality and usefulness of the decisions taken in this matter, when operating in conditions of uncertainty. Lately in the modern world in many socio-economic areas of human life quite often there are thematic challenges of managerial decision-making in a conflict environment and competition, when several in the General case, reasonable working actors perform collective decision-making, and the benefits of each depends not only on the chosen business strategies, but also from management decisions of other partners and the success of the experiments. Therefore, it is necessary to develop and substantiation of optimum variants of decision of choice of forces and means to perform tasks in conditions of uncertainty, that is also acceptable for military units. The actual problem currently is to optimize system control engineering-airfield security, the components of which perform their tasks under conditions of uncertainty. Analysis of opportunities of technical means (unmanned aerial vehicles shows that under the condition of equipping them with the appropriate equipment can be considered about the possibility of their use as part of a complex of technical means for inspection of airfields after the who enemy action in the runway. Therefore, the scientific goal in this article is to examine the possibilities of using technical means for inspection of airfield engineering and airfield services, and the aim of the study is using mathematical methods to justify the choice of the most effective means, from the point of view of economic cost of its introduction and use when performing tasks in conditions of uncertainty.
VI International Workshop on Nature Inspired Cooperative Strategies for Optimization
Otero, Fernando; Masegosa, Antonio
2014-01-01
Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm In...
Nuclear Power Plant Outage Optimization Strategy. 2016 Edition
International Nuclear Information System (INIS)
2016-10-01
This publication is an update of IAEA-TECDOC-1315, Nuclear Power Plant Outage Optimisation Strategy, which was published in 2002, and aims to communicate good outage management practices in a manner that can be used by operators and utilities in Member States. Nuclear power plant outage management is a key factor for safe and economic nuclear power plant performance. This publication discusses plant outage strategy and how this strategy is actually implemented. The main areas that are important for outage optimization that were identified by the utilities and government organizations participating in this report are: 1) organization and management; 2) outage planning and preparation; 3) outage execution; 4) safety outage review; and 5) counter measures to avoid the extension of outages and to facilitate the work in forced outages. Good outage management practices cover many different areas of work and this publication aims to communicate these good practices in a way that they can be used effectively by operators and utilities
International Nuclear Information System (INIS)
Oliver, Mike; Jensen, Michael; Chen, Jeff; Wong, Eugene
2009-01-01
Intensity-modulated arc therapy (IMAT) is a rotational variant of intensity-modulated radiation therapy (IMRT) that can be implemented with or without angular dose rate variation. The purpose of this study is to assess optimization strategies and initial conditions using a leaf position optimization (LPO) algorithm altered for variable dose rate IMAT. A concave planning target volume (PTV) with a central cylindrical organ at risk (OAR) was used in this study. The initial IMAT arcs were approximated by multiple static beams at 5 deg. angular increments where multi-leaf collimator (MLC) leaf positions were determined from the beam's eye view to irradiate the PTV but avoid the OAR. For the optimization strategy, two arcs with arc ranges of 280 deg. and 150 deg. were employed and plans were created using LPO alone, variable dose rate optimization (VDRO) alone, simultaneous LPO and VDRO and sequential combinations of these strategies. To assess the MLC initialization effect, three single 360 deg. arc plans with different initial MLC configurations were generated using the simultaneous LPO and VDRO. The effect of changing optimization degrees of freedom was investigated by employing 3 deg., 5 deg. and 10 deg. angular sampling intervals for the two 280 deg., two 150 deg. and single arc plans using LPO and VDRO. The objective function value, a conformity index, a dose homogeneity index, mean dose to OAR and normal tissues were computed and used to evaluate the treatment plans. This study shows that the best optimization strategy for a concave target is to use simultaneous MLC LPO and VDRO. We found that the optimization result is sensitive to the choice of initial MLC aperture shapes suggesting that an LPO-based IMAT plan may not be able to overcome local minima for this geometry. In conclusion, simultaneous MLC leaf position and VDRO are needed with the most appropriate initial conditions (MLC positions, arc ranges and number of arcs) for IMAT.
International Nuclear Information System (INIS)
Demazure, M.
1988-01-01
The 1988 progress report of the Mathematics center (Polytechnic School, France), is presented. The Center is composed of different research teams: analysis, Riemann geometry, group theory, formal calculus and algorithm geometry, dynamical systems, topology and singularity. For each team, the members, the research topics, the national and international cooperations, are given. The papers concerning the investigations carried out in 1988, are listed [fr
The Study of an Optimal Robust Design and Adjustable Ordering Strategies in the HSCM.
Liao, Hung-Chang; Chen, Yan-Kwang; Wang, Ya-huei
2015-01-01
The purpose of this study was to establish a hospital supply chain management (HSCM) model in which three kinds of drugs in the same class and with the same indications were used in creating an optimal robust design and adjustable ordering strategies to deal with a drug shortage. The main assumption was that although each doctor has his/her own prescription pattern, when there is a shortage of a particular drug, the doctor may choose a similar drug with the same indications as a replacement. Four steps were used to construct and analyze the HSCM model. The computation technology used included a simulation, a neural network (NN), and a genetic algorithm (GA). The mathematical methods of the simulation and the NN were used to construct a relationship between the factor levels and performance, while the GA was used to obtain the optimal combination of factor levels from the NN. A sensitivity analysis was also used to assess the change in the optimal factor levels. Adjustable ordering strategies were also developed to prevent drug shortages.
Sugimoto, Asuka; Sumi, Takuya; Kang, Jiyoung; Tateno, Masaru
2017-07-01
Recognition in biological macromolecular systems, such as DNA-protein recognition, is one of the most crucial problems to solve toward understanding the fundamental mechanisms of various biological processes. Since specific base sequences of genome DNA are discriminated by proteins, such as transcription factors (TFs), finding TF binding motifs (TFBMs) in whole genome DNA sequences is currently a central issue in interdisciplinary biophysical and information sciences. In the present study, a novel strategy to create a discriminant function for discrimination of TFBMs by constituting mathematical neural networks (NNs) is proposed, together with a method to determine the boundary of signals (TFBMs) and noise in the NN-score (output) space. This analysis also leads to the mathematical limitation of discrimination in the recognition of features representing TFBMs, in an information geometrical manifold. Thus, the present strategy enables the identification of the whole space of TFBMs, right up to the noise boundary.
Directory of Open Access Journals (Sweden)
Nicolae Petrescu
2010-01-01
Full Text Available This paper is intended to achieve a mathematical model for the optimal dimensioning of number and heights of somedams/thresholds during a downpour, a decrease of water flow rate being obtained and by the solid material depositionsbehind the constructions a new smaller slope of the valley that changes the torrential nature that had before theconstruction is obtained.The choice of the dam and its characteristic dimensions may be an optimization issue and the location of dams on thetorrential (rainfall aspect is dictated by the capabilities of the foundation and restraint so that the chosen solutions willhave to comply with these sites. Finally, the choice of optimal solution to limit torrential (rainfall aspect will be basedon a calculation where the number of thresholds / dams can be a variable related to this, their height properly varying.The calculation method presented is an attempt to demonstrate the multiple opportunities available to implement atechnical issue solving conditions offered by the mathematics against soil erosion, which now is currently very topicalon the environmental protection.
Optimal Dynamic Strategies for Index Tracking and Algorithmic Trading
Ward, Brian
In this thesis we study dynamic strategies for index tracking and algorithmic trading. Tracking problems have become ever more important in Financial Engineering as investors seek to precisely control their portfolio risks and exposures over different time horizons. This thesis analyzes various tracking problems and elucidates the tracking errors and strategies one can employ to minimize those errors and maximize profit. In Chapters 2 and 3, we study the empirical tracking properties of exchange traded funds (ETFs), leveraged ETFs (LETFs), and futures products related to spot gold and the Chicago Board Option Exchange (CBOE) Volatility Index (VIX), respectively. These two markets provide interesting and differing examples for understanding index tracking. We find that static strategies work well in the nonleveraged case for gold, but fail to track well in the corresponding leveraged case. For VIX, tracking via neither ETFs, nor futures\\ portfolios succeeds, even in the nonleveraged case. This motivates the need for dynamic strategies, some of which we construct in these two chapters and further expand on in Chapter 4. There, we analyze a framework for index tracking and risk exposure control through financial derivatives. We derive a tracking condition that restricts our exposure choices and also define a slippage process that characterizes the deviations from the index over longer horizons. The framework is applied to a number of models, for example, Black Scholes model and Heston model for equity index tracking, as well as the Square Root (SQR) model and the Concatenated Square Root (CSQR) model for VIX tracking. By specifying how each of these models fall into our framework, we are able to understand the tracking errors in each of these models. Finally, Chapter 5 analyzes a tracking problem of a different kind that arises in algorithmic trading: schedule following for optimal execution. We formulate and solve a stochastic control problem to obtain the optimal
Particle Swarm Optimization With Interswarm Interactive Learning Strategy.
Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui
2016-10-01
The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.
Cost-effectiveness analysis of optimal strategy for tumor treatment
International Nuclear Information System (INIS)
Pang, Liuyong; Zhao, Zhong; Song, Xinyu
2016-01-01
We propose and analyze an antitumor model with combined immunotherapy and chemotherapy. Firstly, we explore the treatment effects of single immunotherapy and single chemotherapy, respectively. Results indicate that neither immunotherapy nor chemotherapy alone are adequate to cure a tumor. Hence, we apply optimal theory to investigate how the combination of immunotherapy and chemotherapy should be implemented, for a certain time period, in order to reduce the number of tumor cells, while minimizing the implementation cost of the treatment strategy. Secondly, we establish the existence of the optimality system and use Pontryagin’s Maximum Principle to characterize the optimal levels of the two treatment measures. Furthermore, we calculate the incremental cost-effectiveness ratios to analyze the cost-effectiveness of all possible combinations of the two treatment measures. Finally, numerical results show that the combination of immunotherapy and chemotherapy is the most cost-effective strategy for tumor treatment, and able to eliminate the entire tumor with size 4.470 × 10"8 in a year.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Directory of Open Access Journals (Sweden)
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.
Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen
2017-02-01
Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.
Optimal Bidding Strategy for Renewable Microgrid with Active Network Management
Directory of Open Access Journals (Sweden)
Seung Wan Kim
2016-01-01
Full Text Available Active Network Management (ANM enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG and Battery Energy Storage System (BESS units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.
Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya
Directory of Open Access Journals (Sweden)
Gabriel Otieno
2016-03-01
Full Text Available Malaria remains a leading cause of mortality and morbidity among the children under five and pregnant women in sub-Saharan Africa, but it is preventable and controllable provided current recommended interventions are properly implemented. Better utilization of malaria intervention strategies will ensure the gain for the value for money and producing health improvements in the most cost effective way. The purpose of the value for money drive is to develop a better understanding (and better articulation of costs and results so that more informed, evidence-based choices could be made. Cost effectiveness analysis is carried out to inform decision makers on how to determine where to allocate resources for malaria interventions. This study carries out cost effective analysis of one or all possible combinations of the optimal malaria control strategies (Insecticide Treated Bednets—ITNs, Treatment, Indoor Residual Spray—IRS and Intermittent Preventive Treatment for Pregnant Women—IPTp for the four different transmission settings in order to assess the extent to which the intervention strategies are beneficial and cost effective. For the four different transmission settings in Kenya the optimal solution for the 15 strategies and their associated effectiveness are computed. Cost-effective analysis using Incremental Cost Effectiveness Ratio (ICER was done after ranking the strategies in order of the increasing effectiveness (total infections averted. The findings shows that for the endemic regions the combination of ITNs, IRS, and IPTp was the most cost-effective of all the combined strategies developed in this study for malaria disease control and prevention; for the epidemic prone areas is the combination of the treatment and IRS; for seasonal areas is the use of ITNs plus treatment; and for the low risk areas is the use of treatment only. Malaria transmission in Kenya can be minimized through tailor-made intervention strategies for malaria control
Electromagnetic Problems Solving by Conformal Mapping: A Mathematical Operator for Optimization
Directory of Open Access Journals (Sweden)
Wesley Pacheco Calixto
2010-01-01
Full Text Available Having the property to modify only the geometry of a polygonal structure, preserving its physical magnitudes, the Conformal Mapping is an exceptional tool to solve electromagnetism problems with known boundary conditions. This work aims to introduce a new developed mathematical operator, based on polynomial extrapolation. This operator has the capacity to accelerate an optimization method applied in conformal mappings, to determinate the equipotential lines, the field lines, the capacitance, and the permeance of some polygonal geometry electrical devices with an inner dielectric of permittivity ε. The results obtained in this work are compared with other simulations performed by the software of finite elements method, Flux 2D.
CSIR Research Space (South Africa)
Seid, ER
2014-05-01
Full Text Available and its as- sociated thermal storage policy for recircu- lated hot/cold heat storage medium (HEN). Most of the previous works solved this se- quentially. Foo et al. (2008) extended the minimum units targeting and network evo- lution techniques that were...) reviewed these techniques based on graphical-based pinch analysis and mathematical optimization approach. The seminal work on pinch analysis application to batch water network was reported by Wang and Smith (1994). Foo et al. (2005) proposed a time...
Testing of Strategies for the Acceleration of the Cost Optimization
Energy Technology Data Exchange (ETDEWEB)
Ponciroli, Roberto [Argonne National Lab. (ANL), Argonne, IL (United States); Vilim, Richard B. [Argonne National Lab. (ANL), Argonne, IL (United States)
2017-08-31
The general problem addressed in the Nuclear-Renewable Hybrid Energy System (N-R HES) project is finding the optimum economical dispatch (ED) and capacity planning solutions for the hybrid energy systems. In the present test-problem configuration, the N-R HES unit is composed of three electrical power-generating components, i.e. the Balance of Plant (BOP), the Secondary Energy Source (SES), and the Energy Storage (ES). In addition, there is an Industrial Process (IP), which is devoted to hydrogen generation. At this preliminary stage, the goal is to find the power outputs of each one of the N-R HES unit components (BOP, SES, ES) and the IP hydrogen production level that maximizes the unit profit by simultaneously satisfying individual component operational constraints. The optimization problem is meant to be solved in the Risk Analysis Virtual Environment (RAVEN) framework. The dynamic response of the N-R HES unit components is simulated by using dedicated object-oriented models written in the Modelica modeling language. Though this code coupling provides for very accurate predictions, the ensuing optimization problem is characterized by a very large number of solution variables. To ease the computational burden and to improve the path to a converged solution, a method to better estimate the initial guess for the optimization problem solution was developed. The proposed approach led to the definition of a suitable Monte Carlo-based optimization algorithm (called the preconditioner), which provides an initial guess for the optimal N-R HES power dispatch and the optimal installed capacity for each one of the unit components. The preconditioner samples a set of stochastic power scenarios for each one of the N-R HES unit components, and then for each of them the corresponding value of a suitably defined cost function is evaluated. After having simulated a sufficient number of power histories, the configuration which ensures the highest profit is selected as the optimal
Issues and Strategies in Solving Multidisciplinary Optimization Problems
Patnaik, Surya
2013-01-01
Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the
Directory of Open Access Journals (Sweden)
Wenjie Mei
2016-01-01
Full Text Available The paper reports a tooth profile modification method of spur gear. After establishing a standardized mathematical model for optimized tooth profile and simulating meshing process with ANSYS finite element analysis, we obtained 625 groups of gear models with different modification parameters. The group with minimum transmission errors owns the optimal parameters. Genetic algorithm was adopted in the entire process for the purpose of reducing the variation of transmission errors in meshing process. The arc and parabolic modification were doing the same processing. After comparing the transmission errors fluctuation produced by the meshing process of gear of nonmodification with arc modification and parabolic modification, we found that the best modification effects of arc modification and parabolic modification were both reduced by 90%. The modification method makes the gear drive process more stable and efficient, and it is also promising in general application for gear drive.
2011-04-30
a BS degree in Mathematics and an MS degree in Statistics and Financial and Actuarial Mathematics from Kiev National Taras Shevchenko University...degrees from Rutgers University in Industrial Engineering (PhD and MS) and Statistics (MS) and from Universidad Nacional Autonoma de Mexico in Actuarial ...Science. His research efforts focus on developing mathematical models for the analysis, computation, and optimization of system performance with
Strategies for Optimizing Algal Biology for Enhanced Biomass Production
Energy Technology Data Exchange (ETDEWEB)
Barry, Amanda N.; Starkenburg, Shawn R.; Sayre, Richard T., E-mail: rsayre@newmexicoconsortium.org [Los Alamos National Laboratory, New Mexico Consortium, Los Alamos, NM (United States)
2015-02-02
One of the most environmentally sustainable ways to produce high-energy density (oils) feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source) and subsequent carbon capture and sequestration has also been proposed in the intergovernmental panel on climate change report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass). To increase aerial carbon capture rates and biomass productivity, it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to twofold increases in biomass productivity.
Strategies for Optimizing Algal Biology for Enhanced Biomass Production
International Nuclear Information System (INIS)
Barry, Amanda N.; Starkenburg, Shawn R.; Sayre, Richard T.
2015-01-01
One of the most environmentally sustainable ways to produce high-energy density (oils) feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source) and subsequent carbon capture and sequestration has also been proposed in the intergovernmental panel on climate change report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass). To increase aerial carbon capture rates and biomass productivity, it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to twofold increases in biomass productivity.
Zetriuslita; Wahyudin; Jarnawi
2017-01-01
This research aims to describe and analyze result of applying Problem-Based Learning and Cognitive Conflict Strategy (PBLCCS) in increasing students' Mathematical Critical Thinking (MCT) ability and Mathematical Curiosity Attitude (MCA). Adopting a quasi-experimental method with pretest-posttest control group design and using mixed method with…
Directory of Open Access Journals (Sweden)
Samuel Adejare Awolola
2011-06-01
Full Text Available One dominant factor on how well students learn mathematics is the quality of teaching. Studies have shown that typical mathematics classroom is frosted with teaching technique that centered on explain – practice – memorize. There is a paucity particularly in Nigeria. This study therefore, investigated the effect of brain-based learning strategy on the achievement regarding the learning of Mathematics of 522 Senior Secondary School Students in Oyo State, Nigeria. The moderator effect of cognitive style was also examined on independent variable (instructional strategy and dependent variable (mathematics achievement. The study adopted a pretest-posttest non-equivalent control group design in a quasi – experimental setting. The ANCOVA statistic was used to analyzed the data collected fro the study. The result revealed significant main effect of treatment, (F(1,510 = 75.0; P < 0.05, cognitive style (F(1,510 = 23.78; P < 0.05 and significant interaction effect of treatment and cognitive style (F(1,510 = 5.027; P < 0.05 on achievement in mathematics. The result showed that brain-based instructional strategy enhanced students’ achievement in mathematics more than the conventional lecture method. It is therefore recommended that Teachers of mathematics should adopt the strategy in teaching mathematics in senior secondary school.
House, J. Daniel
2006-01-01
An important area for the application of instructional design is the development of effective teaching strategies for mathematics. Activities that include the use of computers, cooperative learning, and active learning materials are associated with mathematics achievement. Student self-beliefs are also significantly related to mathematics…
Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs
Directory of Open Access Journals (Sweden)
Jiajun Liu
2017-10-01
Full Text Available Energy storage systems (ESS play an important role in the performance of mining vehicles. A hybrid ESS combining both batteries (BTs and supercapacitors (SCs is one of the most promising solutions. As a case study, this paper discusses the optimal hybrid ESS sizing and energy management strategy (EMS of 14-ton underground load-haul-dump vehicles (LHDs. Three novel contributions are added to the relevant literature. First, a multi-objective optimization is formulated regarding energy consumption and the total cost of a hybrid ESS, which are the key factors of LHDs, and a battery capacity degradation model is used. During the process, dynamic programming (DP-based EMS is employed to obtain the optimal energy consumption and hybrid ESS power profiles. Second, a 10-year life cycle cost model of a hybrid ESS for LHDs is established to calculate the total cost, including capital cost, operating cost, and replacement cost. According to the optimization results, three solutions chosen from the Pareto front are compared comprehensively, and the optimal one is selected. Finally, the optimal and battery-only options are compared quantitatively using the same objectives, and the hybrid ESS is found to be a more economical and efficient option.
Study on Stochastic Optimal Electric Power Procurement Strategies with Uncertain Market Prices
Sakchai, Siripatanakulkhajorn; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji
The player in deregulated electricity markets can be categorized into three groups of GENCO (Generator Companies), TRNASCO (Transmission Companies), DISCO (Distribution Companies). This research focuses on the role of Distribution Companies, which purchase electricity from market at randomly fluctuating prices, and provide it to their customers at given fixed prices. Therefore Distribution companies have to take the risk stemming from price fluctuation of electricity instead of the customers. This entails the necessity to develop a certain method to make an optimal strategy for electricity procurement. In such a circumstance, this research has the purpose for proposing the mathematical method based on stochastic dynamic programming to evaluate the value of a long-term bilateral contract of electricity trade, and also a project of combination of the bilateral contract and power generation with their own generators for procuring electric power in deregulated market.
International Nuclear Information System (INIS)
Fernandes, Marco A.R.; Fernandes, David M.; Florentino, Helenice O.
2010-01-01
The work detaches the importance of the use of mathematical tools and computer systems for optimization of the planning in radiotherapy, seeking to the distribution of dose of appropriate radiation in the white volume that provides an ideal therapeutic rate between the tumor cells and the adjacent healthy tissues, extolled in the radiotherapy protocols. Examples of target volumes mathematically modeled are analyzed with the technique of linear programming, comparing the obtained results using the Simplex algorithm with those using the algorithm of Interior Points. The System Genesis II was used for obtaining of the isodose curves for the outline and geometry of fields idealized in the computer simulations, considering the parameters of a 10 MV photons beams. Both programming methods (Simplex and Interior Points) they resulted in a distribution of integral dose in the tumor volume and allow the adaptation of the dose in the critical organs inside of the restriction limits extolled. The choice of an or other method should take into account the facility and the need of limiting the programming time. The isodose curves, obtained with the Genesis II System, illustrate that the adjacent healthy tissues to the tumor receives larger doses than those reached in the computer simulations. More coincident values can be obtained altering the weights and some factors of minimization of the objective function. The prohibitive costs of the computer planning systems, at present available for radiotherapy, it motivates the researches to look for the implementation of simpler and so effective methods for optimization of the treatment plan. (author)
Sheu, Yun Robert; Feder, Elie; Balsim, Igor; Levin, Victor F; Bleicher, Andrew G; Branstetter, Barton F
2010-06-01
Peer review is an essential process for physicians because it facilitates improved quality of patient care and continuing physician learning and improvement. However, peer review often is not well received by radiologists who note that it is time intensive, is subjective, and lacks a demonstrable impact on patient care. Current advances in peer review include the RADPEER() system, with its standardization of discrepancies and incorporation of the peer-review process into the PACS itself. The purpose of this study was to build on RADPEER and similar systems by using a mathematical model to optimally select the types of cases to be reviewed, for each radiologist undergoing review, on the basis of the past frequency of interpretive error, the likelihood of morbidity from an error, the financial cost of an error, and the time required for the reviewing radiologist to interpret the study. The investigators compiled 612,890 preliminary radiology reports authored by residents and attending radiologists at a large tertiary care medical center from 1999 to 2004. Discrepancies between preliminary and final interpretations were classified by severity and validated by repeat review of major discrepancies. A mathematical model was then used to calculate, for each author of a preliminary report, the combined morbidity and financial costs of expected errors across 3 modalities (MRI, CT, and conventional radiography) and 4 departmental divisions (neuroradiology, abdominal imaging, musculoskeletal imaging, and thoracic imaging). A customized report was generated for each on-call radiologist that determined the category (modality and body part) with the highest total cost function. A universal total cost based on probability data from all radiologists was also compiled. The use of mathematical models to guide case selection could optimize the efficiency and effectiveness of physician time spent on peer review and produce more concrete and meaningful feedback to radiologists
Hopmann, Ch.; Windeck, C.; Kurth, K.; Behr, M.; Siegbert, R.; Elgeti, S.
2014-05-01
The rheological design of profile extrusion dies is one of the most challenging tasks in die design. As no analytical solution is available, the quality and the development time for a new design highly depend on the empirical knowledge of the die manufacturer. Usually, prior to start production several time-consuming, iterative running-in trials need to be performed to check the profile accuracy and the die geometry is reworked. An alternative are numerical flow simulations. These simulations enable to calculate the melt flow through a die so that the quality of the flow distribution can be analyzed. The objective of a current research project is to improve the automated optimization of profile extrusion dies. Special emphasis is put on choosing a convenient starting geometry and parameterization, which enable for possible deformations. In this work, three commonly used design features are examined with regard to their influence on the optimization results. Based on the results, a strategy is derived to select the most relevant areas of the flow channels for the optimization. For these characteristic areas recommendations are given concerning an efficient parameterization setup that still enables adequate deformations of the flow channel geometry. Exemplarily, this approach is applied to a L-shaped profile with different wall thicknesses. The die is optimized automatically and simulation results are qualitatively compared with experimental results. Furthermore, the strategy is applied to a complex extrusion die of a floor skirting profile to prove the universal adaptability.
Optimization of fuel cycle strategies with constraints on uranium availability
International Nuclear Information System (INIS)
Silvennoinen, P.; Vira, J.; Westerberg, R.
1982-01-01
Optimization of nuclear reactor and fuel cycle strategies is studied under the influence of reduced availability of uranium. The analysis is separated in two distinct steps. First, the global situation is considered within given high and low projections of the installed capacity up to the year 2025. Uranium is regarded as an exhaustible resource whose production cost would increase proportionally to increasing cumulative exploitation. Based on the estimates obtained for the uranium cost, a global strategy is derived by splitting the installed capacity between light water reactor (LWR) once-through, LWR recycle, and fast breeder reactor (FBR) alternatives. In the second phase, the nuclear program of an individual utility is optimized within the constraints imposed from the global scenario. Results from the global scenarios indicate that in a reference case the uranium price would triple by the year 2000, and the price escalation would continue throughout the planning period. In a pessimistic growth scenario where the global nuclear capacity would not exceed 600 GW(electric) in 2025, the uranium price would almost double by 2000. In both global scenarios, FBRs would be introduced, in the reference case after 2000 and in the pessimistic case after 2010. In spite of the increases in the uranium prices, the levelized power production cost would increase only by 45% up to 2025 in the utility case provided that the plutonium is incinerated as a substitute fuel
Cui, Jian; Zhao, Xue-Hong; Wang, Yan; Xiao, Ya-Bing; Jiang, Xue-Hui; Dai, Li
2014-01-01
Flow injection-hydride generation-atomic fluorescence spectrometry was a widely used method in the industries of health, environmental, geological and metallurgical fields for the merit of high sensitivity, wide measurement range and fast analytical speed. However, optimization of this method was too difficult as there exist so many parameters affecting the sensitivity and broadening. Generally, the optimal conditions were sought through several experiments. The present paper proposed a mathematical model between the parameters and sensitivity/broadening coefficients using the law of conservation of mass according to the characteristics of hydride chemical reaction and the composition of the system, which was proved to be accurate as comparing the theoretical simulation and experimental results through the test of arsanilic acid standard solution. Finally, this paper has put a relation map between the parameters and sensitivity/broadening coefficients, and summarized that GLS volume, carrier solution flow rate and sample loop volume were the most factors affecting sensitivity and broadening coefficients. Optimizing these three factors with this relation map, the relative sensitivity was advanced by 2.9 times and relative broadening was reduced by 0.76 times. This model can provide a theoretical guidance for the optimization of the experimental conditions.
Baranovskaya T. P.; Loyko V. I.; Makarevich O. A.; Bogoslavskiy S. N.
2014-01-01
The article suggests a mathematical model of optimization of the volume of material flows: the model for the ideal conditions; the model for the working conditions; generalized model of determining the optimal input parameters. These models optimize such parameters of inventory management in technology-integrated grain production systems, as the number of cycles supply, the volume of the source material and financial flows. The study was carried out on the example of the integrated system of ...
Survey Strategy Optimization for the Atacama Cosmology Telescope
De Bernardis, F.; Stevens, J. R.; Hasselfield, M.; Alonso, D.; Bond, J. R.; Calabrese, E.; Choi, S. K.; Crowley, K. T.; Devlin, M.; Wollack, E. J.
2016-01-01
In recent years there have been significant improvements in the sensitivity and the angular resolution of the instruments dedicated to the observation of the Cosmic Microwave Background (CMB). ACTPol is the first polarization receiver for the Atacama Cosmology Telescope (ACT) and is observing the CMB sky with arcmin resolution over approximately 2000 square degrees. Its upgrade, Advanced ACTPol (AdvACT), will observe the CMB in five frequency bands and over a larger area of the sky. We describe the optimization and implementation of the ACTPol and AdvACT surveys. The selection of the observed fields is driven mainly by the science goals, that is, small angular scale CMB measurements, B-mode measurements and cross-correlation studies. For the ACTPol survey we have observed patches of the southern galactic sky with low galactic foreground emissions which were also chosen to maximize the overlap with several galaxy surveys to allow unique cross-correlation studies. A wider field in the northern galactic cap ensured significant additional overlap with the BOSS spectroscopic survey. The exact shapes and footprints of the fields were optimized to achieve uniform coverage and to obtain cross-linked maps by observing the fields with different scan directions. We have maximized the efficiency of the survey by implementing a close to 24-hour observing strategy, switching between daytime and nighttime observing plans and minimizing the telescope idle time. We describe the challenges represented by the survey optimization for the significantly wider area observed by AdvACT, which will observe roughly half of the low-foreground sky. The survey strategies described here may prove useful for planning future ground-based CMB surveys, such as the Simons Observatory and CMB Stage IV surveys.
Directory of Open Access Journals (Sweden)
Sara Caviola
2017-09-01
Full Text Available We review how stress induction, time pressure manipulations and math anxiety can interfere with or modulate selection of problem-solving strategies (henceforth “strategy selection” in arithmetical tasks. Nineteen relevant articles were identified, which contain references to strategy selection and time limit (or time manipulations, with some also discussing emotional aspects in mathematical outcomes. Few of these take cognitive processes such as working memory or executive functions into consideration. We conclude that due to the sparsity of available literature our questions can only be partially answered and currently there is not much evidence of clear associations. We identify major gaps in knowledge and raise a series of open questions to guide further research.
Mathematical programming model for heat exchanger design through optimization of partial objectives
International Nuclear Information System (INIS)
Onishi, Viviani C.; Ravagnani, Mauro A.S.S.; Caballero, José A.
2013-01-01
Highlights: • Rigorous design of shell-and-tube heat exchangers according to TEMA standards. • Division of the problem into sets of equations that are easier to solve. • Selected heuristic objective functions based on the physical behavior of the problem. • Sequential optimization approach to avoid solutions stuck in local minimum. • The results obtained with this model improved the values reported in the literature. - Abstract: Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature
International Nuclear Information System (INIS)
Cox, G.; Beresford, N.A.; Alvarez-Farizo, B.; Oughton, D.; Kis, Z.; Eged, K.; Thorring, H.; Hunt, J.; Wright, S.; Barnett, C.L.; Gil, J.M.; Howard, B.J.; Crout, N.M.J.
2005-01-01
A spatially implemented model designed to assist the identification of optimal countermeasure strategies for radioactively contaminated regions is described. Collective and individual ingestion doses for people within the affected area are estimated together with collective exported ingestion dose. A range of countermeasures are incorporated within the model, and environmental restrictions have been included as appropriate. The model evaluates the effectiveness of a given combination of countermeasures through a cost function which balances the benefit obtained through the reduction in dose with the cost of implementation. The optimal countermeasure strategy is the combination of individual countermeasures (and when and where they are implemented) which gives the lowest value of the cost function. The model outputs should not be considered as definitive solutions, rather as interactive inputs to the decision making process. As a demonstration the model has been applied to a hypothetical scenario in Cumbria (UK). This scenario considered a published nuclear power plant accident scenario with a total deposition of 1.7 x 10 14 , 1.2 x 10 13 , 2.8 x 10 10 and 5.3 x 10 9 Bq for Cs-137, Sr-90, Pu-239/240 and Am-241, respectively. The model predicts that if no remediation measures were implemented the resulting collective dose would be approximately 36 000 person-Sv (predominantly from 137 Cs) over a 10-year period post-deposition. The optimal countermeasure strategy is predicted to avert approximately 33 000 person-Sv at a cost of approximately pound 160 million. The optimal strategy comprises a mixture of ploughing, AFCF (ammonium-ferric hexacyano-ferrate) administration, potassium fertiliser application, clean feeding of livestock and food restrictions. The model recommends specific areas within the contaminated area and time periods where these measures should be implemented
International Nuclear Information System (INIS)
Piacentino, A.; Gallea, R.; Cardona, F.; Lo Brano, V.; Ciulla, G.; Catrini, P.
2015-01-01
Highlights: • Lay-out, design and operation of trigeneration plant is optimized for hotel building. • The temporal basis used for the optimization is properly selected. • The influence of plant scheme on the optimal results is discussed. • Sensitivity analysis is performed for different levels of tax exemption on fuel. • Dynamic behavior of the cogeneration unit influences its optimal operation strategy. - Abstract: The large potential for energy saving by cogeneration and trigeneration in the building sector is scarcely exploited due to a number of obstacles in making the investments attractive. The analyst often encounters difficulties in identifying optimal design and operation strategies, since a number of factors, either endogenous (i.e. related with the energy load profiles) and exogenous (i.e. related with external conditions like energy prices and support mechanisms), influence the economic viability. In this paper a decision tool is adopted, which represents an upgrade of a software analyzed in previous papers; the tool simultaneously optimizes the plant lay-out, the sizes of the main components and their operation strategy. For a specific building in the hotel sector, a preliminary analysis is performed to identify the most promising plant configuration, in terms of type of cogeneration unit (either microturbine or diesel oil/natural gas-fueled reciprocate engine) and absorption chiller. Then, sensitivity analyses are carried out to investigate the effects induced by: (a) tax exemption for the fuel consumed in “efficient cogeneration” mode, (b) dynamic behavior of the prime mover and consequent capability to rapidly adjust its load level to follow the energy loads
Robust approximate optimal guidance strategies for aeroassisted orbital transfer missions
Ilgen, Marc R.
This thesis presents the application of game theoretic and regular perturbation methods to the problem of determining robust approximate optimal guidance laws for aeroassisted orbital transfer missions with atmospheric density and navigated state uncertainties. The optimal guidance problem is reformulated as a differential game problem with the guidance law designer and Nature as opposing players. The resulting equations comprise the necessary conditions for the optimal closed loop guidance strategy in the presence of worst case parameter variations. While these equations are nonlinear and cannot be solved analytically, the presence of a small parameter in the equations of motion allows the method of regular perturbations to be used to solve the equations approximately. This thesis is divided into five parts. The first part introduces the class of problems to be considered and presents results of previous research. The second part then presents explicit semianalytical guidance law techniques for the aerodynamically dominated region of flight. These guidance techniques are applied to unconstrained and control constrained aeroassisted plane change missions and Mars aerocapture missions, all subject to significant atmospheric density variations. The third part presents a guidance technique for aeroassisted orbital transfer problems in the gravitationally dominated region of flight. Regular perturbations are used to design an implicit guidance technique similar to the second variation technique but that removes the need for numerically computing an optimal trajectory prior to flight. This methodology is then applied to a set of aeroassisted inclination change missions. In the fourth part, the explicit regular perturbation solution technique is extended to include the class of guidance laws with partial state information. This methodology is then applied to an aeroassisted plane change mission using inertial measurements and subject to uncertainties in the initial value
Optimal strategy for selling on group-buying website
Directory of Open Access Journals (Sweden)
Xuan Jiang
2014-09-01
Full Text Available Purpose: The purpose of this paper is to help business marketers with offline channels to make decisions on whether to sell through Group-buying (GB websites and how to set online price with the coordination of maximum deal size on GB websites. Design/methodology/approach: Considering the deal structure of GB websites especially for the service fee and minimum deal size limit required by GB websites, advertising effect of selling on GB websites, and interaction between online and offline markets, an analytical model is built to derive optimal online price and maximum deal size for sellers selling through GB website. This paper aims to answer four research questions: (1 How to make a decision on maximum deal size with coordination of the deal price? (2 Will selling on GB websites always be better than staying with offline channel only? (3 What kind of products is more appropriate to sell on GB website? (4How could GB website operator induce sellers to offer deep discount in GB deals? Findings and Originality/value: This paper obtains optimal strategies for sellers selling on GB website and finds that: Even if a seller has sufficient capacity, he/she may still set a maximum deal size on the GB deal to take advantage of Advertisement with Limited Availability (ALA effect; Selling through GB website may not bring a higher profit than selling only through offline channel when a GB site only has a small consumer base and/or if there is a big overlap between the online and offline markets; Low margin products are more suitable for being sold online with ALA strategies (LP-ALA or HP-ALA than high margin ones; A GB site operator could set a small minimum deal size to induce deep discounts from the sellers selling through GB deals. Research limitations/implications: The present study assumed that the demand function is determinate and linear. It will be interesting to study how stochastic demand and a more general demand function affect the optimal
Directory of Open Access Journals (Sweden)
Paulo Cesar Chagas Rodrigues
2012-07-01
Full Text Available Acquire and produce what is strictly necessary are the goals of the organizations, since they aim companies more competitive and thereby reducing production costs. The research method is applied in nature, with a qualitative and quantitative approach, in which the objective of the research will be: exploratory and descriptive, with technical procedures, divided into: bibliographic, documentary, survey and concluding with a case study. On this assumption the main objective of this research is to develop and analyze a mathematical model that minimizes costs and maximizes the postponement of stocks in a company in the pulp, paper and paper products. Having been found only four papers, two articles and two theses that deal with the issue of demand management, supply chain and inventory postponement. These studies address the issue by modeling the productive time of the supply chain. For production segments this research may enable development of management practices demand and production strategy, allowing cost reductions and productivity gains possible. With the development of the mathematical model could ever analyze the behavior of demand and its influence on the productive strategy, strategy formulation regarding the purchase of raw materials and finished product storage in the last four years the company's results for the proposed model.
Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software
Directory of Open Access Journals (Sweden)
Abel Soares Siqueira
2016-04-01
Full Text Available A very important area of research in the field of Mathematical Optimization is the benchmarking of optimization packages to compare solvers. During benchmarking, one usually collects a large amount of information like CPU time, number of functions evaluations, number of iterations, and much more. This information, if presented as tables, can be difficult to analyze and compare due to large amount of data. Therefore tools to better process and understand optimization benchmark data have been developed. One of the most widespread tools is the Performance Profile graphics proposed by Dolan and Moré [2]. In this context, this paper describes perprof-py, a free/open source software that creates 'Performance Profile' graphics. This software produces graphics in PDF using LaTeX with PGF/TikZ [22] and PGFPLOTS [4] packages, in PNG using matplotlib [9], and in HTML using Bokeh [1]. Perprof-py can also be easily extended to be used with other plot libraries. It is implemented in Python 3 with support for internationalization, and is under the General Public License Version 3 (GPLv3.
Mathematical optimization of incore nuclear fuel management decisions: Status and trends
International Nuclear Information System (INIS)
Turinsky, P.J.
1999-01-01
Nuclear fuel management involves making decisions about the number of fresh assemblies to purchase and their Attributes (e.g. enrichment and burnable poison loading), burnt fuel to reinsert, location of the assemblies in the core (i.e. loading pattern (LP)), and insertion of control rods as a function of cycle exposure (i.e. control rod pattern (CRP)). The out-of-core and incore nuclear fuel management problems denote an artificial separation of decisions to simplify the decisionmaking. The out-of-core problem involves multicycle analysis so that levelized fuel cycle cost can be evaluated; whereas, the incore problem normally involves single cycle analysis. Decision variables for the incore problem normally include all of the above noted decisions with the exception of the number of fresh assemblies, which is restricted by discharge burnup limits and therefore involves multicycle considerations. This paper reports on the progress that is being made in addressing the incore nuclear fuel management problem utilizing formal mathematical optimization methods. Advances in utilizing the Simulating Annealing, Genetic Algorithm and Tabu Search methods, with applications to pressurized and boiling water reactor incore optimization problem, will be reviewed. Recent work on the addition of multiobjective optimization capability to aide the decision maker, and utilization of heuristic rules and incorporation of parallel algorithms to increase computational efficiency, will be discussed. (orig.) [de
International Nuclear Information System (INIS)
Beck, T.; Bieler, A.; Thomas, N.
2012-01-01
We present structural and thermal model (STM) tests of the BepiColombo laser altimeter (BELA) receiver baffle with emphasis on the correlation of the data with a thermal mathematical model. The test unit is a part of the thermal and optical protection of the BELA instrument being tested under infrared and solar irradiation at University of Bern. An iterative optimization method known as particle swarm optimization has been adapted to adjust the model parameters, mainly the linear conductivity, in such a way that model and test results match. The thermal model reproduces the thermal tests to an accuracy of 4.2 °C ± 3.2 °C in a temperature range of 200 °C after using only 600 iteration steps of the correlation algorithm. The use of this method brings major benefits to the accuracy of the results as well as to the computational time required for the correlation. - Highlights: ► We present model correlations of the BELA receiver baffle to thermal balance tests. ► Adaptive particle swarm optimization has been adapted for the correlation. ► The method improves the accuracy of the correlation and the computational time.
Directory of Open Access Journals (Sweden)
M. Boychuk
2015-10-01
Full Text Available The activity of distribution companies is multifaceted. Ihey establish contacts with producers and consumers, determine the range of prices of medicines, do promotions, hold stocks of pharmaceuticals and take risks in their further selling.Their internal problems are complicated by the political crisis in the country, decreased purchasing power of national currency, and the rise in interest rates on loans. Therefore the usage of stochastic models of dynamic systems for the research into optimizing the management of pharmaceutical products distribution companies taking into account credit payments is of great current interest. A stochastic model of the optimal credit strategy of a pharmaceutical distributor in the market of pharmaceutical products has been constructed in the article considering credit payments and income limitations. From the mathematical point of view the obtained problem is the one of stochastic optimal control where the amount of monetary credit is the control and the amount of pharmaceutical product is the solution curve. The model allows to identify the optimal cash loan and the corresponding optimal quantity of pharmaceutical product that comply with the differential model of the existing quantity of pharmaceutical products in the form of Ito; the condition of the existing initial stock of pharmaceutical products; the limitation on the amount of credit and profit received from the product selling and maximize the average integral income. The research of the stochastic optimal control problem involves the construction of the left process of crediting with determination of the shift point of that control, the choice of the right crediting process and the formation of the optimal credit process. It was found that the optimal control of the credit amount and the shift point of that control are the determined values and don’t depend on the coefficient in the Wiener process and the optimal trajectory of the amount of
Gradient Material Strategies for Hydrogel Optimization in Tissue Engineering Applications
2018-01-01
Although a number of combinatorial/high-throughput approaches have been developed for biomaterial hydrogel optimization, a gradient sample approach is particularly well suited to identify hydrogel property thresholds that alter cellular behavior in response to interacting with the hydrogel due to reduced variation in material preparation and the ability to screen biological response over a range instead of discrete samples each containing only one condition. This review highlights recent work on cell–hydrogel interactions using a gradient material sample approach. Fabrication strategies for composition, material and mechanical property, and bioactive signaling gradient hydrogels that can be used to examine cell–hydrogel interactions will be discussed. The effects of gradients in hydrogel samples on cellular adhesion, migration, proliferation, and differentiation will then be examined, providing an assessment of the current state of the field and the potential of wider use of the gradient sample approach to accelerate our understanding of matrices on cellular behavior. PMID:29485612
Optimizing urology group partnerships: collaboration strategies and compensation best practices.
Jacoby, Dana L; Maller, Bruce S; Peltier, Lisa R
2014-10-01
Market forces in health care have created substantial regulatory, legislative, and reimbursement changes that have had a significant impact on urology group practices. To maintain viability, many urology groups have merged into larger integrated entities. Although group operations vary considerably, the majority of groups have struggled with the development of a strong culture, effective decision-making, and consensus-building around shared resources, income, and expense. Creating a sustainable business model requires urology group leaders to allocate appropriate time and resources to address these issues in a proactive manner. This article outlines collaboration strategies for creating an effective culture, governance, and leadership, and provides practical suggestions for optimizing the performance of the urology group practice.
Optimal Strategies for Probing Terrestrial Exoplanet Atmospheres with JWST
Batalha, Natasha E.; Lewis, Nikole K.; Line, Michael
2018-01-01
It is imperative that the exoplanet community determines the feasibility and the resources needed to yield high fidelity atmospheric compositions from terrestrial exoplanets. In particular, LHS 1140b and the TRAPPIST-1 system, already slated for observations by JWST’s Guaranteed Time Observers, will be the first two terrestrial planets observed by JWST. I will discuss optimal observing strategies for observing these two systems, focusing on the NIRSpec Prism (1-5μm) and the combination of NIRISS SOSS (1-2.7μm) and NIRSpec G395H (3-5μm). I will also introduce currently unsupported JWST readmodes that have the potential to greatly increase the precision on our atmospheric spectra. Lastly, I will use information content theory to compute the expected confidence interval on the retrieved abundances of key molecular species and temperature profiles as a function of JWST observing cycles.
Optimized control strategy for crowbarless solid state modular power supply
International Nuclear Information System (INIS)
Upadhyay, R.; Badapanda, M.K.; Tripathi, A.; Hannurkar, P.R.; Pithawa, C.K.
2009-01-01
Solid state modular power supply with series connected IGBT based power modules have been employed as high voltage bias power supply of klystron amplifier. Auxiliary compensation of full wave inverter bridge with ZVS/ZCS operations of all IGBTs over entire operating range is incorporated. An optimized control strategy has been adopted for this power supply needing no output filter, making this scheme crowbarless and is presented in this paper. DSP based fully digital control with same duty cycle for all power modules, have been incorporated for regulating this power supply along with adequate protection features. Input to this power supply is taken directly from 11 kV line and the input system is intentionally made 24 pulsed to reduce the input harmonics, improve the input power factor significantly, there by requiring no line filters. Various steps have been taken to increase the efficiency of major subsystems, so as to improve the overall efficiency of this power supply significantly. (author)
Evolution strategy based optimal chiller loading for saving energy
International Nuclear Information System (INIS)
Chang, Y.-C.; Lee, C.-Y.; Chen, C.-R.; Chou, C.-J.; Chen, W.-H.; Chen, W.-H.
2009-01-01
This study employs evolution strategy (ES) to solve optimal chiller loading (OCL) problem. ES overcomes the flaw that Lagrangian method is not adaptable for solving OCL as the power consumption models or the kW-PLR (partial load ratio) curves include convex functions and concave functions simultaneously. The complicated process of evolution by the genetic algorithm (GA) method for solving OCL can also be simplified by the ES method. This study uses the PLR of chiller as the variable to be solved for the decoupled air conditioning system. After analysis and comparison of the case study, it has been concluded that this method not only solves the problems of Lagrangian method and GA method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems
Optimal Inspection and Repair Strategies for Structural Systems
DEFF Research Database (Denmark)
Sommer, A. M.; Nowak, A. S.; Thoft-Christensen, Palle
1992-01-01
and a design variable as optimization variables. A model for estimating the total expected costs for structural systems is given including the costs associated with the loss of individual structural members as well as the costs associated with the loss of at least one element of a particular group......A model for reliability-based repair and maintenance strategies of structural systems is described. The total expected costs in the lifetime of the structure are minimized with the number of inspections, the number and positions of the inspected points, the inspection efforts, the repair criteria...... of structural members and the costs associated with the simultaneous loss of all members of a specific group of structural members. The approach is based on the pre-posteriori analysis from the classical decision theory. Special emphasis is given to the problem of selecting the number of points in the structure...
Collins, Linda M
2018-01-01
This book presents a framework for development, optimization, and evaluation of behavioral, biobehavioral, and biomedical interventions. Behavioral, biobehavioral, and biomedical interventions are programs with the objective of improving and maintaining human health and well-being, broadly defined, in individuals, families, schools, organizations, or communities. These interventions may be aimed at, for example, preventing or treating disease, promoting physical and mental health, preventing violence, or improving academic achievement. This volume introduces the Multiphase Optimization Strategy (MOST), pioneered at The Methodology Center at the Pennsylvania State University, as an alternative to the classical approach of relying solely on the randomized controlled trial (RCT). MOST borrows heavily from perspectives taken and approaches used in engineering, and also integrates concepts from statistics and behavioral science, including the RCT. As described in detail in this book, MOST consists of ...
Optimal Order Strategy in Uncertain Demands with Free Shipping Option
Directory of Open Access Journals (Sweden)
Qing-Chun Meng
2014-01-01
Full Text Available Free shipping with conditions has become one of the most effective marketing tools; more and more companies especially e-business companies prefer to offer free shipping to buyers whenever their orders exceed the minimum quantity specified by them. But in practice, the demands of buyers are uncertain, which are affected by weather, season, and many other factors. Firstly, we model the centralization ordering problem of retailers who face stochastic demands when suppliers offer free shipping, in which limited distributional information such as known mean, support, and some deviation measures of the random data is needed only. Then, based on the linear decision rule mainly for stochastic programming, we analyze the optimal order strategies of retailers and discuss the approximate solution. Further, we present the core allocation between all retailers via dual and cooperative game theory. The existence of core shows that each retailer is pleased to cooperate with others in the centralization problem. Finally, a numerical example is implemented to discuss how uncertain data and parameters affect the optimal solution.
Monique Duval
2005-01-01
CERN Technical Training 2005: Learning for the LHC! CERN Technical Training, in collaboration with the AT-MEL-EM section, is organising a new course series in the framework of the 2005 CERN Technical Training programme: EMAG-2005 - Electromagnetic Design and Mathematical Optimization Methods in Magnet Technology, composed of three-hour lectures in the morning and topical seminars in the afternoon. The EMAG-2005 course series will run at CERN from Monday April 4 until Thursday April 14 (no lectures on Friday 8). The course series, in English, will focus on the foundations of electromagnetism and the design of accelerator magnets, both normal conducting and superconducting, employing analytical and numerical field computations. Examples of the LHC magnet design using the CERN field computation program ROXIE will be presented. However, EMAG-2005 is not a ROXIE user course: it is rather a course for users or potential users of numerical field computation software, and for magnet designers. The course will be o...
A Mathematical Formulation of the SCOLE Control Problem. Part 2: Optimal Compensator Design
Balakrishnan, A. V.
1988-01-01
The study initiated in Part 1 of this report is concluded and optimal feedback control (compensator) design for stability augmentation is considered, following the mathematical formulation developed in Part 1. Co-located (rate) sensors and (force and moment) actuators are assumed, and allowing for both sensor and actuator noise, stabilization is formulated as a stochastic regulator problem. Specializing the general theory developed by the author, a complete, closed form solution (believed to be new with this report) is obtained, taking advantage of the fact that the inherent structural damping is light. In particular, it is possible to solve in closed form the associated infinite-dimensional steady-state Riccati equations. The SCOLE model involves associated partial differential equations in a single space variable, but the compensator design theory developed is far more general since it is given in the abstract wave equation formulation. The results thus hold for any multibody system so long as the basic model is linear.
Heat integration of an Olefins Plant: Pinch Analysis and mathematical optimization working together
Directory of Open Access Journals (Sweden)
M. Beninca
2011-03-01
Full Text Available This work explores a two-step, complexity reducing methodology, to analyze heat integration opportunities of an existing Olefins Plant, identify and quantify reduction of energy consumption, and propose changes of the existing heat exchanger network to achieve these goals. Besides the analysis of plant design conditions, multiple operational scenarios were considered to propose modifications for handling real plant operation (flexibility. On the strength of plant complexity and large dimension, work methodology was split into two parts: initially, the whole plant was evaluated with traditional Pinch Analysis tools. Several opportunities were identified and modifications proposed. Modifications were segregated to represent small and independent portions of the original process. One of them was selected to be re-analyzed, considering two scenarios. Reduction of problem dimension allowed mathematical methodologies (formulation with decomposition, applying LP, MILP and NLP optimization methods to synthesize flexible networks to be applied, generating a feasible modification capable of fulfilling the proposed operational scenarios.
Optimizing the HLT Buffer Strategy with Monte Carlo Simulations
AUTHOR|(CDS)2266763
2017-01-01
This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.
Minimizing the effect of automotive pollution in urban geometry using mathematical optimization
Energy Technology Data Exchange (ETDEWEB)
Craig, K.J.; De Kock, D.J.; Snyman, J.A. [Pretoria Univ. (South Africa). Dept. of Mechanical and Aeronautical Engineering
2001-07-01
One of the factors that needs to be considered during the layout of new urban geometry (e.g. street direction, spacing and width, building height restrictions) is the effect of the air pollution associated with the automotive transport that would use routes in this urban area. Although the pollution is generated at street level, its effect can be widespread due to interaction of the pollutant dispersion and diffusion with the wind speed and direction. In order to study the effect of a new urban geometry on the pollutant levels and dispersion, a very time-consuming experimental or parametric numerical study would have to be performed. This paper proposes an alternative approach, that of combining mathematical optimization with the techniques of computational fluid dynamics (CFD). In essence, the meteorological information as represented by a wind rose (wind speed and direction), is used to calculate pollutant levels as a function of urban geometry variables: street canyon depth and street canyon width. The pollutant source specified in conjunction with a traffic scenario with CO is used as pollutant. The main aim of the study is to be able to suggest the most beneficial configuration of an idealized urban geometry that minimizes the peak pollutant levels due to assumed traffic distributions. This study uses two mathematical optimization methods. The first method is implemented through a successive maximization-minimization approach, while the second method determines the location of saddle points of the pollutant level, considered as a function of urban geometry and wind rose. Locally, a saddle point gives the best urban geometry for the worst meteorological scenario. The commercial CFD code, STAR-CD, is coupled with a version of the DYNAMIC-Q optimization algorithm of Snyman, first to successively locate maxima and minima in a min-max approach; and then to locate saddle points. It is shown that the saddle-point method is more cost-effective. The methodology
Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; vom Hofe, Rudolf
2013-01-01
This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10;…
Fadlelmula, Fatma Kayan; Cakiroglu, Erdinc; Sungur, Semra
2015-01-01
This study examines the interrelationships among students' motivational beliefs (i.e. achievement goal orientations, perception of classroom goal structure, and self-efficacy), use of self-regulated learning strategies (i.e. elaboration, organization, and metacognitive self-regulation strategies), and achievement in mathematics, by proposing and…
Verta, Antonella; Schena, Emiliano; Silvestri, Sergio
2010-06-01
The control of thermo-hygrometric conditions of gas delivered in neonatal mechanical ventilation appears to be a particularly difficult task, mainly due to the vast number of parameters to be monitored and the control strategies of heated humidifiers to be adopted. In the present paper, we describe the heat and fluid exchange occurring in a heated humidifier in mathematical terms; we analyze the sensitivity of the relative humidity of outlet gas as a function of thermo-hygrometric and fluid-dynamic parameters of delivered gas; we propose a control strategy that will enable the stability of outlet gas thermo-hygrometric conditions. The mathematical model is represented by a hyper-surface containing the functional relations between the input variables, which must be measured, and the output variables, which have to remain constant. Model sensitivity analysis shows that heated humidifier efficacy and stability of outlet gas thermo-hygrometric conditions are principally influenced by four parameters: liquid surface temperature, gas flow rate, inlet gas temperature and inlet gas relative humidity. The theoretical model has been experimentally validated in typical working conditions of neonatal applications. The control strategy has been implemented by a minimal measurement system composed of three thermometers, a humidity sensor, and a flow rate sensor, and based on the theoretical model. Outlet relative humidity, contained in the range 90+/-4% and 94+/-4%, corresponding with temperature variations in the range 28+/-2 degrees C and 38+/-2 degrees C respectively, has been obtained in the whole flow rate range typical of neonatal ventilation from 1 to 10 L/min. We conclude that in order to obtain the stability of the thermo-hygrometric conditions of the delivered gas mixture: (a) a control strategy with a more complex measurement system must be implemented (i.e. providing more input variables); (b) and the gas may also need to be pre-warmed before entering the humidifying
Zetriuslita Zetriuslita; Wahyudin Wahyudin; Jarnawi Afgani Dahlan
2018-01-01
This research aims to find out the association amongMathematical Critical Thinking (MCT) ability, Mathematical Communication, and Mathematical Curiosity Attitude (MCA) as the impact of applying Problem-Based Learning Cognitive Conflict Strategy(PBLCCS) in Number Theory course. The research method is correlative study. The instruments include a test for mathematical critical thinking skill and communication, and questionnaire to obtain the scores of mathematical curiosity attitude. The finding...
Fomina, E. V.; Kozhukhova, N. I.; Sverguzova, S. V.; Fomin, A. E.
2018-05-01
In this paper, the regression equations method for design of construction material was studied. Regression and polynomial equations representing the correlation between the studied parameters were proposed. The logic design and software interface of the regression equations method focused on parameter optimization to provide the energy saving effect at the stage of autoclave aerated concrete design considering the replacement of traditionally used quartz sand by coal mining by-product such as argillite. The mathematical model represented by a quadric polynomial for the design of experiment was obtained using calculated and experimental data. This allowed the estimation of relationship between the composition and final properties of the aerated concrete. The surface response graphically presented in a nomogram allowed the estimation of concrete properties in response to variation of composition within the x-space. The optimal range of argillite content was obtained leading to a reduction of raw materials demand, development of target plastic strength of aerated concrete as well as a reduction of curing time before autoclave treatment. Generally, this method allows the design of autoclave aerated concrete with required performance without additional resource and time costs.
A mathematical model of optimized radioiodine-131 therapy of Graves' hyperthyroidism
International Nuclear Information System (INIS)
Doi, Suhail AR; Loutfi, Issa; Al-Shoumer, Kamal AS
2001-01-01
The current status of radioiodine-131 (RaI) dosimetry for Graves' hyperthyroidism is not clear. Recurrent hyperthyroidism and iatrogenic hypothyroidism are two problems which interact such that trying to solve one leads to exacerbation of the other. Optimized RaI therapy has therefore begun to be defined just in terms of early hypothyroidism (ablative therapy) as physicians have given up on reducing hypothyroidism. Optimized therapy is evaluated both in terms of the greatest separation of cure rate from hypothyroidism rate (non-ablative therapy) or in terms of early hypothyroidism (ablative therapy) by mathematical modeling of outcome after radioiodine and critically discussing the three common methods of RaI dosing for Graves' disease. Cure follows a logarithmic relationship to activity administered or absorbed dose, while hypothyroidism follows a linear relationship. The effect of including or omitting factors in the calculation of the administered I–131 activity such as the measured thyroid uptake and effective half-life of RaI or giving extra compensation for gland size is discussed. Very little benefit can be gained by employing complicated methods of RaI dose selection for non-ablative therapy since the standard activity model shows the best potential for cure and prolonged euthyroidism. For ablative therapy, a standard MBq/g dosing provides the best outcome in terms of cure and early hypothyroidism
Mathematical modeling of zika virus disease with nonlinear incidence and optimal control
Goswami, Naba Kumar; Srivastav, Akhil Kumar; Ghosh, Mini; Shanmukha, B.
2018-04-01
The Zika virus was first discovered in a rhesus monkey in the Zika Forest of Uganda in 1947, and it was isolated from humans in Nigeria in 1952. Zika virus disease is primarily a mosquito-borne disease, which is transmitted to human primarily through the bite of an infected Aedes species mosquito. However, there is documented evidence of sexual transmission of this disease too. In this paper, a nonlinear mathematical model for Zika virus by considering nonlinear incidence is formulated and analyzed. The equilibria and the basic reproduction number (R0) of the model are found. The stability of the different equilibria of the model is discussed in detail. When the basic reproduction number R0 1, we have endemic equilibrium which is locally stable under some restriction on parameters. Further this model is extended to optimal control model and is analyzed by using Pontryagin’s Maximum Principle. It has been observed that optimal control plays a significant role in reducing the number of zika infectives. Finally, numerical simulation is performed to illustrate the analytical findings.
Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.
2017-03-01
General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.
Priatna, N.; Martadiputra, B. A. P.; Wibisono, Y.
2018-05-01
The development of science and technology requires reform in the utilization of various resources for mathematics teaching and learning process. One of the efforts that can be made is the implementation of GeoGebra-assisted Reciprocal Teaching strategy in mathematics instruction as an effective strategy in improving students’ cognitive, affective, and psychomotor abilities. This research is intended to implement GeoGebra-assisted Reciprocal Teaching strategy in improving abstraction ability, lateral thinking, and mathematical persistence of junior high school students. It employed quasi-experimental method with non-random pre-test and post-test control design. More specifically, it used the 2x3 factorial design, namely the learning factors that included GeoGebra-assisted Reciprocal Teaching and conventional teaching learning, and levels of early mathematical ability (high, middle, and low). The subjects in this research were the eighth grade students of junior high school, taken with purposive sampling. The results of this research show: Abstraction and lateral abilities of students who were taught with GeoGebra-assisted Reciprocal Teaching strategy were significantly higher than those of students who received conventional learning. Mathematical persistence of students taught with GeoGebra-assisted Reciprocal Teaching strategy was also significantly higher than of those taught with conventional learning.
Exploring the Optimal Strategy to Predict Essential Genes in Microbes
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Yao Lu
2011-12-01
Full Text Available Accurately predicting essential genes is important in many aspects of biology, medicine and bioengineering. In previous research, we have developed a machine learning based integrative algorithm to predict essential genes in bacterial species. This algorithm lends itself to two approaches for predicting essential genes: learning the traits from known essential genes in the target organism, or transferring essential gene annotations from a closely related model organism. However, for an understudied microbe, each approach has its potential limitations. The first is constricted by the often small number of known essential genes. The second is limited by the availability of model organisms and by evolutionary distance. In this study, we aim to determine the optimal strategy for predicting essential genes by examining four microbes with well-characterized essential genes. Our results suggest that, unless the known essential genes are few, learning from the known essential genes in the target organism usually outperforms transferring essential gene annotations from a related model organism. In fact, the required number of known essential genes is surprisingly small to make accurate predictions. In prokaryotes, when the number of known essential genes is greater than 2% of total genes, this approach already comes close to its optimal performance. In eukaryotes, achieving the same best performance requires over 4% of total genes, reflecting the increased complexity of eukaryotic organisms. Combining the two approaches resulted in an increased performance when the known essential genes are few. Our investigation thus provides key information on accurately predicting essential genes and will greatly facilitate annotations of microbial genomes.
Optimizing strategies to improve interprofessional practice for veterans, part 1
Directory of Open Access Journals (Sweden)
Bhattacharya SB
2014-04-01
Full Text Available Shelley B Bhattacharya,1–3 Michelle I Rossi,1,2 Jennifer M Mentz11Geriatric Research Education and Clinical Center (GRECC, Veteran's Affairs Pittsburgh Healthcare System, 2University of Pittsburgh Medical Center, Pittsburgh, PA, USA; 3Albert Schweitzer Fellowship Program, Pittsburgh, PA, USAIntroduction: Interprofessional patient care is a well-recognized path that health care systems are striving toward. The Veteran's Affairs (VA system initiated interprofessional practice (IPP models with their Geriatric Evaluation and Management (GEM programs. GEM programs incorporate a range of specialties, including but not limited to, medicine, nursing, social work, physical therapy and pharmacy, to collaboratively evaluate veterans. Despite being a valuable resource, they are now faced with significant cut-backs, including closures. The primary goal of this project was to assess how the GEM model could be optimized at the Pittsburgh, Pennsylvania VA to allow for the sustainability of this important IPP assessment. Part 1 of the study evaluated the IPP process using program, patient, and family surveys. Part 2 examined how well the geriatrician matched patients to specialists in the GEM model. This paper describes Part 1 of our study.Methods: Three strategies were used: 1 a national GEM program survey; 2 a veteran/family satisfaction survey; and 3 an absentee assessment.Results: Twenty-six of 92 programs responded to the GEM IPP survey. Six strategies were shared to optimize IPP models throughout the country. Of the 34 satisfaction surveys, 80% stated the GEM clinic was beneficial, 79% stated their concerns were addressed, and 100% would recommend GEM to their friends. Of the 24 absentee assessments, the top three reasons for missing the appointments were transportation, medical illnesses, and not knowing/remembering about the appointment. Absentee rate diminished from 41% to 19% after instituting a reminder phone call policy.Discussion: Maintaining the
Emergency strategy optimization for the environmental control system in manned spacecraft
Li, Guoxiang; Pang, Liping; Liu, Meng; Fang, Yufeng; Zhang, Helin
2018-02-01
It is very important for a manned environmental control system (ECS) to be able to reconfigure its operation strategy in emergency conditions. In this article, a multi-objective optimization is established to design the optimal emergency strategy for an ECS in an insufficient power supply condition. The maximum ECS lifetime and the minimum power consumption are chosen as the optimization objectives. Some adjustable key variables are chosen as the optimization variables, which finally represent the reconfigured emergency strategy. The non-dominated sorting genetic algorithm-II is adopted to solve this multi-objective optimization problem. Optimization processes are conducted at four different carbon dioxide partial pressure control levels. The study results show that the Pareto-optimal frontiers obtained from this multi-objective optimization can represent the relationship between the lifetime and the power consumption of the ECS. Hence, the preferred emergency operation strategy can be recommended for situations when there is suddenly insufficient power.
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
Repair rather than segregation of damage is the optimal unicellular aging strategy.
Clegg, Robert J; Dyson, Rosemary J; Kreft, Jan-Ulrich
2014-08-16
How aging, being unfavourable for the individual, can evolve is one of the fundamental problems of biology. Evidence for aging in unicellular organisms is far from conclusive. Some studies found aging even in symmetrically dividing unicellular species; others did not find aging in the same, or in different, unicellular species, or only under stress. Mathematical models suggested that segregation of non-genetic damage, as an aging strategy, would increase fitness. However, these models failed to consider repair as an alternative strategy or did not properly account for the benefits of repair. We used a new and improved individual-based model to examine rigorously the effect of a range of aging strategies on fitness in various environments. Repair of damage emerges as the best strategy despite its fitness costs, since it immediately increases growth rate. There is an optimal investment in repair that outperforms damage segregation in well-mixed, lasting and benign environments over a wide range of parameter values. Damage segregation becomes beneficial, and only in combination with repair, when three factors are combined: (i) the rate of damage accumulation is high, (ii) damage is toxic and (iii) efficiency of repair is low. In contrast to previous models, our model predicts that unicellular organisms should have active mechanisms to repair damage rather than age by segregating damage. Indeed, as predicted, all organisms have evolved active mechanisms of repair whilst aging in unicellular organisms is absent or minimal under benign conditions, apart from microorganisms with a different ecology, inhabiting short-lived environments strongly favouring early reproduction rather than longevity. Aging confers no fitness advantage for unicellular organisms in lasting environments under benign conditions, since repair of non-genetic damage is better than damage segregation.
Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations
Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying
2010-09-01
Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).
Holmes, Mark H.
2006-10-01
To help students grasp the intimate connections that exist between mathematics and its applications in other disciplines a library of interactive learning modules was developed. This library covers the mathematical areas normally studied by undergraduate students and is used in science courses at all levels. Moreover, the library is designed not just to provide critical connections across disciplines but to also provide longitudinal subject reinforcement as students progress in their studies. In the process of developing the modules a complete editing and publishing system was constructed that is optimized for automated maintenance and upgradeability of materials. The result is a single integrated production system for web-based educational materials. Included in this is a rigorous assessment program, involving both internal and external evaluations of each module. As will be seen, the formative evaluation obtained during the development of the library resulted in the modules successfully bridging multiple disciplines and breaking down the disciplinary barriers commonly found in their math and non-math courses.
Optimal Stochastic Advertising Strategies for the U.S. Beef Industry
Kun C. Lee; Stanley Schraufnagel; Earl O. Heady
1982-01-01
An important decision variable in the promotional strategy for the beef sector is the optimal level of advertising expenditures over time. Optimal stochastic and deterministic advertising expenditures are derived for the U.S. beef industry for the period `1966 through 1980. They are compared with historical levels and gains realized by optimal advertising strategies are measured. Finally, the optimal advertising expenditures in the future are forecasted.
International Nuclear Information System (INIS)
Gao, Jiajia; Huang, Gongsheng; Xu, Xinhua
2016-01-01
Highlights: • An optimization strategy for a small-scale air-conditioning system is developed. • The optimization strategy aims at optimizing the overall system energy consumption. • The strategy may guarantee the robust control of the space air temperature. • The performance of the optimization strategy was tested on a simulation platform. - Abstract: This paper studies the optimization of a small-scale central air-conditioning system, in which the cooling is provided by a ground source heat pump (GSHP) equipped with an on/off capacity control. The optimization strategy aims to optimize the overall system energy consumption and simultaneously guarantee the robustness of the space air temperature control without violating the allowed GSHP maximum start-ups number per hour specified by customers. The set-point of the chilled water return temperature and the width of the water temperature control band are used as the decision variables for the optimization. The performance of the proposed strategy was tested on a simulation platform. Results show that the optimization strategy can save the energy consumption by 9.59% in a typical spring day and 2.97% in a typical summer day. Meanwhile it is able to enhance the space air temperature control robustness when compared with a basic control strategy without optimization.
Noninfectious uveitis: strategies to optimize treatment compliance and adherence
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Dolz-Marco R
2015-08-01
Full Text Available Rosa Dolz-Marco,1 Roberto Gallego-Pinazo,1 Manuel Díaz-Llopis,2 Emmett T Cunningham Jr,3–6 J Fernando Arévalo7,8 1Unit of Macula, Department of Ophthalmology, University and Polytechnic Hospital La Fe, 2Faculty of Medicine, University of Valencia, Spain; 3Department of Ophthalmology, California Pacific Medical Center, San Francisco, 4Department of Ophthalmology, Stanford University School of Medicine, Stanford, 5The Francis I Proctor Foundation, University of California San Francisco Medical Center, 6West Coast Retina Medical Group, San Francisco, CA, USA; 7Vitreoretina Division, King Khaled Eye Specialist Hospital, Riyadh, Saudi Arabia; 8Retina Division, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA Abstract: Noninfectious uveitis includes a heterogenous group of sight-threatening ocular and systemic disorders. Significant progress has been made in the treatment of noninfectious uveitis in recent years, particularly with regard to the effective use of corticosteroids and non-corticosteroid immunosuppressive drugs, including biologic agents. All of these therapeutic approaches are limited, however, by any given patient’s ability to comply with and adhere to their prescribed treatment. In fact, compliance and adherence are among the most important patient-related determinants of treatment success. We discuss strategies to optimize compliance and adherence. Keywords: noninfectious uveitis, intraocular inflammation, immunosuppressive treatment, adherence, compliance, therapeutic failure
Optimal breast cancer screening strategies for older women: current perspectives
Directory of Open Access Journals (Sweden)
Braithwaite D
2016-02-01
Full Text Available Dejana Braithwaite,1 Joshua Demb,1 Louise M Henderson2 1Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, 2Department of Radiology, University of North Carolina, Chapel Hill, NC, USA Abstract: Breast cancer is a major cause of cancer-related deaths among older women, aged 65 years or older. Screening mammography has been shown to be effective in reducing breast cancer mortality in women aged 50–74 years but not among those aged 75 years or older. Given the large heterogeneity in comorbidity status and life expectancy among older women, controversy remains over screening mammography in this population. Diminished life expectancy with aging may decrease the potential screening benefit and increase the risk of harms. In this review, we summarize the evidence on screening mammography utilization, performance, and outcomes and highlight evidence gaps. Optimizing the screening strategy will involve separating older women who will benefit from screening from those who will not benefit by using information on comorbidity status and life expectancy. This review has identified areas related to screening mammography in older women that warrant additional research, including the need to evaluate emerging screening technologies, such as tomosynthesis among older women and precision cancer screening. In the absence of randomized controlled trials, the benefits and harms of continued screening mammography in older women need to be estimated using both population-based cohort data and simulation models. Keywords: aging, breast cancer, precision cancer screening
An Optimal Investment Strategy for Insurers in Incomplete Markets
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Mohamed Badaoui
2018-04-01
Full Text Available In this paper we consider the problem of an insurance company where the wealth of the insurer is described by a Cramér-Lundberg process. The insurer is allowed to invest in a risky asset with stochastic volatility subject to the influence of an economic factor and the remaining surplus in a bank account. The price of the risky asset and the economic factor are modeled by a system of correlated stochastic differential equations. In a finite horizon framework and assuming that the market is incomplete, we study the problem of maximizing the expected utility of terminal wealth. When the insurer’s preferences are exponential, an existence and uniqueness theorem is proven for the non-linear Hamilton-Jacobi-Bellman equation (HJB. The optimal strategy and the value function have been produced in closed form. In addition and in order to show the connection between the insurer’s decision and the correlation coefficient we present two numerical approaches: A Monte-Carlo method based on the stochastic representation of the solution of the insurer problem via Feynman-Kac’s formula, and a mixed Finite Difference Monte-Carlo one. Finally the results are presented in the case of Scott model.
Optimizing individual iron deficiency prevention strategies in physiological pregnancy
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Kramarskiy V.A.
2018-04-01
Full Text Available Sideropenia by the end of pregnancy takes place in all mothers without exception. Moreover, the selective administration of iron preparations, in contrast to the routine, makes it possible to avoid hemochromatosis, frequency of which in the general population makes from 0.5 to 13 %. The aim of the study was to optimize the individual strategy for the prevention of iron deficiency in physiological pregnancy. A prospective pre-experimental study was conducted, the criterion of inclusion in which was the mother’s extragenital and obstetrical pathology during the first half of pregnancy, a burdened obstetric and gynecological anamnesis. The study group of 98 women with a physiological pregnancy in the period of 20 to 24 weeks was recruited by simple ran- dom selection. Serum ferritin, hemoglobin, and serum iron were used to estimate iron deficiency. In the latent stage of iron deficiency against a background of monthly correction with Fenules ® in a dose of 90 mg of elemental iron per day, there was a significant increase in ferritin and iron in the blood rotor. In healthy mothers, during the gestational period of 20–24 weeks, a regularity arises in the replenishment of iron status, especially in the case of repeated pregnancy, which is successfully satisfied during the month of Fenules ® intake in doses of 45 mg or 90 mg per day with a serum ferritin level of, respectively, 30 up to 70 μg/l or less than 30 μg/l.
Invigorating self-regulated learning strategies of mathematics among higher education students
Chechi, Vijay Kumar; Bhalla, Jyoti
2017-07-01
The global market is transforming at its ever-increasing rate of knots. Consequently, the work skills challenges that current students will encounter throughout their lifetimes will be drastically different from those of present and past and proffering new-fangled opportunities and posing new challenges. However, in order to deal with tomorrow's opportunities and challenges students ought to equip with higher order cognitive skills which are substantially different from those needed in the past. In order to accomplish this intention, students must be academically self-regulated, as academic self-regulation is playing a vital role for academic success, particularly in higher education. Students must be prepared in such a way that they should take responsibility for their own learning. Self-regulation suggests activities and thinking processes that learners can engage in during his learning. Self-regulation is encompassing a number of inter-dependent aspect viz. affective beliefs, cognition and meta-cognitive skills [1]. It helps the learners to make sagacious use of their intellect and expertise [2]. As statistics has shown that the achievement of students in mathematics has persistently been poor. Along with it, mathematics is considered as one of the most important subject course in architecture, agriculture, medicine, pharmacy and especially in engineering. In spite of its importance, most of the students considered it as a dull and dry subject and their performance is remarkably low and alarming. Therefore, the present paper will highlight various factors affecting performance of higher education students in mathematics and will suggest different self-regulated learning strategies which will act as boon for higher education students.
Two Project-Based Strategies in an Interdisciplinary Mathematical Modeling in Biology Course
Ludwig, Patrice; Tongen, Anthony; Walton, Brian
2018-01-01
James Madison University faculty team-teach an interdisciplinary mathematical modeling course for mathematics and biology students. We have used two different project-based approaches to emphasize the mathematical concepts taught in class, while also exposing students to new areas of mathematics not formally covered in class. The first method…
Ayal, Carolina S.; Kusuma, Yaya S.; Sabandar, Jozua; Dahlan, Jarnawi Afgan
2016-01-01
Mathematical reasoning ability, are component that must be governable by the student. Mathematical reasoning plays an important role, both in solving problems and in conveying ideas when learning mathematics. In fact there ability are not still developed well, even in middle school. The importance of mathematical reasoning ability (KPM are…
Directory of Open Access Journals (Sweden)
Sara Tartof
Full Text Available The optimal long-term vaccination strategies to provide population-level protection against serogroup A Neisseria meningitidis (MenA are unknown. We developed an age-structured mathematical model of MenA transmission, colonization, and disease in the African meningitis belt, and used this model to explore the impact of various vaccination strategies.The model stratifies the simulated population into groups based on age, infection status, and MenA antibody levels. We defined the model parameters (such as birth and death rates, age-specific incidence rates, and age-specific duration of protection using published data and maximum likelihood estimation. We assessed the validity of the model by comparing simulated incidence of invasive MenA and prevalence of MenA carriage to observed incidence and carriage data.The model fit well to observed age- and season-specific prevalence of carriage (mean pseudo-R2 0.84 and incidence of invasive disease (mean R2 0.89. The model is able to reproduce the observed dynamics of MenA epidemics in the African meningitis belt, including seasonal increases in incidence, with large epidemics occurring every eight to twelve years. Following a mass vaccination campaign of all persons 1-29 years of age, the most effective modeled vaccination strategy is to conduct mass vaccination campaigns every 5 years for children 1-5 years of age. Less frequent campaigns covering broader age groups would also be effective, although somewhat less so. Introducing conjugate MenA vaccine into the EPI vaccination schedule at 9 months of age results in higher predicted incidence than periodic mass campaigns.We have developed the first mathematical model of MenA in Africa to incorporate age structures and progressively waning protection over time. Our model accurately reproduces key features of MenA epidemiology in the African meningitis belt. This model can help policy makers consider vaccine program effectiveness when determining the
Echolocating bats use a nearly time-optimal strategy to intercept prey.
Directory of Open Access Journals (Sweden)
Kaushik Ghose
2006-05-01
Full Text Available Acquisition of food in many animal species depends on the pursuit and capture of moving prey. Among modern humans, the pursuit and interception of moving targets plays a central role in a variety of sports, such as tennis, football, Frisbee, and baseball. Studies of target pursuit in animals, ranging from dragonflies to fish and dogs to humans, have suggested that they all use a constant bearing (CB strategy to pursue prey or other moving targets. CB is best known as the interception strategy employed by baseball outfielders to catch ballistic fly balls. CB is a time-optimal solution to catch targets moving along a straight line, or in a predictable fashion--such as a ballistic baseball, or a piece of food sinking in water. Many animals, however, have to capture prey that may make evasive and unpredictable maneuvers. Is CB an optimum solution to pursuing erratically moving targets? Do animals faced with such erratic prey also use CB? In this paper, we address these questions by studying prey capture in an insectivorous echolocating bat. Echolocating bats rely on sonar to pursue and capture flying insects. The bat's prey may emerge from foliage for a brief time, fly in erratic three-dimensional paths before returning to cover. Bats typically take less than one second to detect, localize and capture such insects. We used high speed stereo infra-red videography to study the three dimensional flight paths of the big brown bat, Eptesicus fuscus, as it chased erratically moving insects in a dark laboratory flight room. We quantified the bat's complex pursuit trajectories using a simple delay differential equation. Our analysis of the pursuit trajectories suggests that bats use a constant absolute target direction strategy during pursuit. We show mathematically that, unlike CB, this approach minimizes the time it takes for a pursuer to intercept an unpredictably moving target. Interestingly, the bat's behavior is similar to the interception strategy
Echolocating bats use a nearly time-optimal strategy to intercept prey.
Ghose, Kaushik; Horiuchi, Timothy K; Krishnaprasad, P S; Moss, Cynthia F
2006-05-01
Acquisition of food in many animal species depends on the pursuit and capture of moving prey. Among modern humans, the pursuit and interception of moving targets plays a central role in a variety of sports, such as tennis, football, Frisbee, and baseball. Studies of target pursuit in animals, ranging from dragonflies to fish and dogs to humans, have suggested that they all use a constant bearing (CB) strategy to pursue prey or other moving targets. CB is best known as the interception strategy employed by baseball outfielders to catch ballistic fly balls. CB is a time-optimal solution to catch targets moving along a straight line, or in a predictable fashion--such as a ballistic baseball, or a piece of food sinking in water. Many animals, however, have to capture prey that may make evasive and unpredictable maneuvers. Is CB an optimum solution to pursuing erratically moving targets? Do animals faced with such erratic prey also use CB? In this paper, we address these questions by studying prey capture in an insectivorous echolocating bat. Echolocating bats rely on sonar to pursue and capture flying insects. The bat's prey may emerge from foliage for a brief time, fly in erratic three-dimensional paths before returning to cover. Bats typically take less than one second to detect, localize and capture such insects. We used high speed stereo infra-red videography to study the three dimensional flight paths of the big brown bat, Eptesicus fuscus, as it chased erratically moving insects in a dark laboratory flight room. We quantified the bat's complex pursuit trajectories using a simple delay differential equation. Our analysis of the pursuit trajectories suggests that bats use a constant absolute target direction strategy during pursuit. We show mathematically that, unlike CB, this approach minimizes the time it takes for a pursuer to intercept an unpredictably moving target. Interestingly, the bat's behavior is similar to the interception strategy implemented in some
Directory of Open Access Journals (Sweden)
I. I. Kravchenko
2016-01-01
Full Text Available Experience in application of multi-operational machines CNC (MOM CNC shows that they are efficient only in case of significantly increasing productivity and dramatically reducing time-to-market cycle of new products. Most full technological MOM capabilities are revealed when processing the complex body parts. The more complex is a part design and the more is its number of machined surfaces, the more tools are necessary for its processing and positioning, the more is an efficiency of their application. At the same time, the case history of using these machines in industry shows that MOM CNC are, virtually, used mostly for technological processes of universal equipment, which is absolutely unacceptable. One way to improve the processing performance on MOM CNC is to reduce nonproductive machine time through reducing the mutual idle movements of the working machine. This problem is solved using dynamic programming methods, one of which is the solution of the traveling salesman problem (Bellman's method. With a known plan for treatment of all elementary surfaces of the body part, i.e. the known number of performed transitions, each transition is represented as a vertex of some graph, while technological links between the vertices are its edges. A mathematical model is developed on the Bellman principle, which is adapted to technological tasks to minimize the idle time of mutual idle movements of the working machine to perform all transitions in the optimal sequence. The initial data to fill matrix of time expenditures are time consumed by the hardware after executing the i-th transition, and necessary to complete the j-transition. The programmer fills in matrix cells according to known routing body part taking into account the time for part and table positioning, tool exchange, spindle and table approach to the working zone, and the time of table rotation, etc. The mathematical model was tested when machining the body part with 36 transitions on the
Strategies of solving arithmetic word problems in students with learning difficulties in mathematics
Kalan, Marko
2015-01-01
Problem solving as an important skill is, beside arithmetic, measure and algebra, included in standards of school mathematics (National Council of Teachers of Mathematics) (NCTM, 2000) and needed as a necessary skill for successfulness in science, technology, engineering and mathematics (STEM) (National Mathematics Advisory Panel, 2008). Since solving of human problems is connected to the real life, the arithmetic word problems (in short AWP) are an important kind of mathematics tasks in scho...
International Nuclear Information System (INIS)
Tzolakis, G.; Papanikolaou, P.; Kolokotronis, D.; Samaras, N.; Tourlidakis, A.; Tomboulides, A.
2012-01-01
Since most of the world's electric energy production is mainly based on fossil fuels and need for better efficiency of the energy conversion systems is imminent, mathematical programming algorithms were applied for the simulation and optimization of a detailed model of an existing lignite-fired power plant in Kozani, Greece (KARDIA IV). The optimization of its overall thermal efficiency, using as control variables the mass flow rates of the steam turbine extractions and the fuel consumption, was performed with the use of the simulation and optimization software gPROMS. The power plant components' mathematical models were imported in software by the authors and the results showed that further increase to the overall thermal efficiency of the plant can be achieved (a 0.55% absolute increase) through reduction of the HP turbine's and increase of the LP turbine's extractions mass flow rates and the parallel reduction of the fuel consumption by 2.05% which also results to an equivalent reduction of the greenhouse gasses. The setup of the mathematical model and the flexibility of gPROMS, make this software applicable to various power plants. - Highlights: ► Modeling and simulation of the flue gases circuit of a specific plant. ► Designing of modules in gPROMS FO (Foreign Objects). ► Simulation of the complete detailed plant with gPROMS. ► Optimization using a non-linear optimization algorithm of the plant's efficiency.
Mathematics, Pricing, Market Risk Management and Trading Strategies for Financial Derivatives (1/3)
CERN. Geneva; Coffey, Brian
2009-01-01
Abstract: An introduction to the mathematics and practicalities of market trading and risk management for financial derivatives, the course will focus on examples from the short-term and long term Foreign Exchange (FX) and Interest Rate (IR) derivatives markets. Topics: - Government Bonds and IR Curves - Stochastic FX, Black-Scholes Vanilla FX Options and Martingales - Risk Management and Market Trading for Vanilla FX Options, Market Implied Volatility, Valuation and Risk Management, Market Trading Strategies - Stochastic IR Curves and Implied Volatility, IR Derivatives - Long Term FX Options: Interaction of Stochastic FX and Stochastic IR Vanilla Foreign Exchange (FX) Options - $ Government Bonds, Interest Rate (IR) Curves, Continuous IR - Domestic ($) and Foreign (Yen) Government Bonds, IR curves - Stochastic Spot FX, Forward FX: Ito processes for $ and Yen Investors - Black-Scholes Vanilla FX Options, Connection to Heat/Diffusion Equation - Stochastic Differential Equations with Mart...
Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; Vom Hofe, Rudolf
2013-01-01
This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; Mage = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.
DEFF Research Database (Denmark)
Tajsoleiman, Tannaz; J. Abdekhodaie, Mohammad; Gernaey, Krist
2016-01-01
simulation of cartilage cell culture under a perfusion flow, which allows not only to characterize the supply of nutrients and metabolic products inside a fibrous scaffold, but also to assess the overall culture condition and predict the cell growth rate. Afterwards, the simulation results supported finding...... an optimized design of the scaffold within a new mathematical optimization algorithm that is proposed. The main concept of this optimization routine isto maintain a large effective surface while simultaneously keeping the shear stress levelin an operating range that is expected to be supporting growth....... Therewith, it should bepossible to gradually reach improved culture efficiency as defined in the objective function....
Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies.
Lorenz, Todd C
2012-05-22
In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek's microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase. PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: • Set up reactions and thermal cycling
Local Stability Analysis of an Infection-Age Mathematical Model for ...
African Journals Online (AJOL)
Timothy
1Department of Mathematics/Statistics/Computer Science, Federal University of Agriculture, Makurdi, ... ABSTRACT: An infection age structured mathematical model for tuberculosis disease ...... its applications to optimal vaccination strategies.
Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen
2018-02-07
The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small
Strategies towards an optimized use of the shallow geothermal potential
Schelenz, S.; Firmbach, L.; Kalbacher, T.; Goerke, U.; Kolditz, O.; Dietrich, P.; Vienken, T.
2013-12-01
Thermal use of the shallow subsurface for heat generation, cooling and thermal energy storage is increasingly gaining importance in reconsideration of future energy supplies, e.g. in the course of German energy transition, with application shifting from isolated to intensive use. The planning and dimensioning of (geo-)thermal applications is strongly influenced by the availability of exploration data. Hence, reliable site-specific dimensioning of systems for the thermal use of the shallow subsurface will contribute to an increase in resource efficiency, cost reduction during installation and operation, as well as reduction of environmental impacts and prevention of resource over-exploitation. Despite large cumulative investments that are being made for the utilization of the shallow thermal potential, thermal energy is in many cases exploited without prior on-site exploration and investigation of the local geothermal potential, due to the lack of adequate and cost-efficient exploration techniques. We will present new strategies for an optimized utilization of urban thermal potential, showcased at a currently developed residential neighborhood with high demand for shallow geothermal applications, based on a) enhanced site characterization and b) simulation of different site specific application scenarios. For enhanced site characterization, surface geophysics and vertical high resolution direct push-profiling were combined for reliable determination of aquifer structure and aquifer parameterization. Based on the site characterization, different site specific geothermal application scenarios, including different system types and system configurations, were simulated using OpenGeoSys to guarantee an environmental and economic sustainable thermal use of the shallow subsurface.
Bacterial Quorum Sensing Stabilizes Cooperation by Optimizing Growth Strategies.
Bruger, Eric L; Waters, Christopher M
2016-11-15
Communication has been suggested as a mechanism to stabilize cooperation. In bacteria, chemical communication, termed quorum sensing (QS), has been hypothesized to fill this role, and extracellular public goods are often induced by QS at high cell densities. Here we show, with the bacterium Vibrio harveyi, that QS provides strong resistance against invasion of a QS defector strain by maximizing the cellular growth rate at low cell densities while achieving maximum productivity through protease upregulation at high cell densities. In contrast, QS mutants that act as defectors or unconditional cooperators maximize either the growth rate or the growth yield, respectively, and thus are less fit than the wild-type QS strain. Our findings provide experimental evidence that regulation mediated by microbial communication can optimize growth strategies and stabilize cooperative phenotypes by preventing defector invasion, even under well-mixed conditions. This effect is due to a combination of responsiveness to environmental conditions provided by QS, lowering of competitive costs when QS is not induced, and pleiotropic constraints imposed on defectors that do not perform QS. Cooperation is a fundamental problem for evolutionary biology to explain. Conditional participation through phenotypic plasticity driven by communication is a potential solution to this dilemma. Thus, among bacteria, QS has been proposed to be a proximate stabilizing mechanism for cooperative behaviors. Here, we empirically demonstrate that QS in V. harveyi prevents cheating and subsequent invasion by nonproducing defectors by maximizing the growth rate at low cell densities and the growth yield at high cell densities, whereas an unconditional cooperator is rapidly driven to extinction by defectors. Our findings provide experimental evidence that QS regulation prevents the invasion of cooperative populations by QS defectors even under unstructured conditions, and they strongly support the role of
Energy Technology Data Exchange (ETDEWEB)
Rabi, Jose A.; Souza-Santos, Marcio L. de [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica. Dept. de Energia]. E-mails: jrabi@fem.unicamp.br; dss@fem.unicamp.br
2000-07-01
Modeling and simulation of fluidized-bed equipment have demonstrated their importance as a tool for design and optimization of industrial equipment. Accordingly, this work carries on an optimization study of a fluidized-bed boiler with the aid of a comprehensive mathematical simulator. The configuration data of the boiler are based on a particular Babcock and Wilcox Co. (USA) test unit. Due to their importance, the number of tubes in the bed section and the air excess are chosen as the parameters upon which the optimization study is based. On their turn, the fixed-carbon conversion factor and the boiler efficiency are chosen as two distinct optimization objectives. The results from both preliminary searches are compared. The present work is intended to be just a study on possible routes for future optimization of larger boilers. Nonetheless, the present discussion might give some insight on the equipment behavior. (author)
Development and Utilization of mathematical Optimization in Advanced Fuel Cycle Systems Analysis
International Nuclear Information System (INIS)
Turinsky, Paul; Hays, Ross
2011-01-01
Over the past sixty years, a wide variety of nuclear power technologies have been theorized, investigated and tested to various degrees. These technologies, if properly applied, could provide a stable, long-term, economical source of CO2-free electric power. However, the recycling of nuclear fuel introduces a degree of coupling between reactor systems which must be accounted for when making long term strategic plans. This work investigates the use of a simulated annealing optimization algorithm coupled together with the VISION fuel cycle simulation model in order to identify attractive strategies from economic, evironmental, non-proliferation and waste-disposal perspectives, which each have associated an objective function. The simulated annealing optimization algorithm works by perturbing the fraction of new reactor capacity allocated to each available reactor type (using a set of heuristic rules) then evaluating the resulting deployment scenario outcomes using the VISION model and the chosen objective functions. These new scenarios, which are either accepted or rejected according the the Metropolis Criterion, are then used as the basis for further perturbations. By repeating this process several thousand times, a family of near-optimal solutions are obtained. Preliminary results from this work using a two-step, Once-through LWR to Full-recycle/FRburner deployment scenario with exponentially increasing electric demand indicate that the algorithm is capable of finding reactor deployment profiles that reduce the long-term-heat waste disposal burden relative to an initial reference scenario. Further work is under way to refine the current results and to extend them to include the other objective functions and to examine the optimization trade-offs that exist between these different objectives.
Development and Utilization of mathematical Optimization in Advanced Fuel Cycle Systems Analysis
Energy Technology Data Exchange (ETDEWEB)
Turinsky, Paul; Hays, Ross
2011-09-02
Over the past sixty years, a wide variety of nuclear power technologies have been theorized, investigated and tested to various degrees. These technologies, if properly applied, could provide a stable, long-term, economical source of CO2-free electric power. However, the recycling of nuclear fuel introduces a degree of coupling between reactor systems which must be accounted for when making long term strategic plans. This work investigates the use of a simulated annealing optimization algorithm coupled together with the VISION fuel cycle simulation model in order to identify attractive strategies from economic, evironmental, non-proliferation and waste-disposal perspectives, which each have associated an objective function. The simulated annealing optimization algorithm works by perturbing the fraction of new reactor capacity allocated to each available reactor type (using a set of heuristic rules) then evaluating the resulting deployment scenario outcomes using the VISION model and the chosen objective functions. These new scenarios, which are either accepted or rejected according the the Metropolis Criterion, are then used as the basis for further perturbations. By repeating this process several thousand times, a family of near-optimal solutions are obtained. Preliminary results from this work using a two-step, Once-through LWR to Full-recycle/FRburner deployment scenario with exponentially increasing electric demand indicate that the algorithm is capable of nding reactor deployment pro les that reduce the long-term-heat waste disposal burden relative to an initial reference scenario. Further work is under way to re ne the current results and to extend them to include the other objective functions and to examine the optimization trade-o s that exist between these di erent objectives.
International Nuclear Information System (INIS)
Wang, Xinli; Cai, Wenjian; Lu, Jiangang; Sun, Youxian; Zhao, Lei
2015-01-01
This study presents a model-based optimization strategy for an actual chiller driven dehumidifier of liquid desiccant dehumidification system operating with lithium chloride solution. By analyzing the characteristics of the components, energy predictive models for the components in the dehumidifier are developed. To minimize the energy usage while maintaining the outlet air conditions at the pre-specified set-points, an optimization problem is formulated with an objective function, the constraints of mechanical limitations and components interactions. Model-based optimization strategy using genetic algorithm is proposed to obtain the optimal set-points for desiccant solution temperature and flow rate, to minimize the energy usage in the dehumidifier. Experimental studies on an actual system are carried out to compare energy consumption between the proposed optimization and the conventional strategies. The results demonstrate that energy consumption using the proposed optimization strategy can be reduced by 12.2% in the dehumidifier operation. - Highlights: • Present a model-based optimization strategy for energy saving in LDDS. • Energy predictive models for components in dehumidifier are developed. • The Optimization strategy are applied and tested in an actual LDDS. • Optimization strategy can achieve energy savings by 12% during operation
Directory of Open Access Journals (Sweden)
O. V. Fomin
2013-10-01
Full Text Available Purpose. Presentation of features and example of the use of the offered determination algorithm of optimum geometrical parameters for the components of freight cars on the basis of the generalized mathematical models, which is realized using computer. Methodology. The developed approach to search for optimal geometrical parameters can be described as the determination of optimal decision of the selected set of possible variants. Findings. The presented application example of the offered algorithm proved its operation capacity and efficiency of use. Originality. The determination procedure of optimal geometrical parameters for freight car components on the basis of the generalized mathematical models was formalized in the paper. Practical value. Practical introduction of the research results for universal open cars allows one to reduce container of their design and accordingly to increase the carrying capacity almost by100 kg with the improvement of strength characteristics. Taking into account the mass of their park this will provide a considerable economic effect when producing and operating. The offered approach is oriented to the distribution of the software packages (for example Microsoft Excel, which are used by technical services of the most enterprises, and does not require additional capital investments (acquisitions of the specialized programs and proper technical staff training. This proves the correctness of the research direction. The offered algorithm can be used for the solution of other optimization tasks on the basis of the generalized mathematical models.
Optimal strategy analysis based on robust predictive control for inventory system with random demand
Saputra, Aditya; Widowati, Sutrisno
2017-12-01
In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.
Johnson, K. D.; Pinder, G. F.
2013-12-01
The objective of the project is the creation of a new, computationally based, approach to the collection, evaluation and use of data for the purpose of determining optimal strategies for investment in the solution of remediation of contaminant source areas and similar environmental problems. The research focuses on the use of existing mathematical tools assembled in a unique fashion. The area of application of this new capability is optimal (least-cost) groundwater contamination source identification; we wish to identify the physical environments wherein it may be cost-prohibitive to identify a contaminant source, the optimal strategy to protect the environment from additional insult and formulate strategies for cost-effective environmental restoration. The computational underpinnings of the proposed approach encompass the integration into a unique of several known applied-mathematical tools. The resulting tool integration achieves the following: 1) simulate groundwater flow and contaminant transport under uncertainty, that is when the physical parameters such as hydraulic conductivity are known to be described by a random field; 2) define such a random field from available field data or be able to provide insight into the sampling strategy needed to create such a field; 3) incorporate subjective information, such as the opinions of experts on the importance of factors such as locations of waste landfills; 4) optimize a search strategy for finding a potential source location and to optimally combine field information with model results to provide the best possible representation of the mean contaminant field and its geostatistics. Our approach combines in a symbiotic manner methodologies found in numerical simulation, random field analysis, Kalman filtering, fuzzy set theory and search theory. Testing the algorithm for this stage of the work, we will focus on fabricated field situations wherein we can a priori specify the degree of uncertainty associated with the
Guerrero-Ortiz, Carolina; Mena-Lorca, Jaime
2015-01-01
International audience; This study analyses the results obtained from comparing the paths shown by expert mathematicians on the one hand and mathematics teachers on the other, when addressing a hypothetical problem that requires the construction of a mathematical model. The research was conducted with a qualitative approach, applying a case study which involved a group of mathematics teachers and three experts from different mathematical areas. The results show that the process of constructin...
Implementation of an optimal control energy management strategy in a hybrid truck
Mullem, D. van; Keulen, T. van; Kessels, J.T.B.A.; Jager, B. de; Steinbuch, M.
2010-01-01
Energy Management Strategies for hybrid powertrains control the power split, between the engine and electric motor, of a hybrid vehicle, with fuel consumption or emission minimization as objective. Optimal control theory can be applied to rewrite the optimization problem to an optimization
Li, Rui
2009-01-01
The target of this work is to extend the canonical Evolution Strategies (ES) from traditional real-valued parameter optimization domain to mixed-integer parameter optimization domain. This is necessary because there exist numerous practical optimization problems from industry in which the set of
Abdullah, Nasarudin; Halim, Lilia; Zakaria, Effandi
2014-01-01
This study aimed to determine the impact of strategic thinking and visual representation approaches (VStops) on the achievement, conceptual knowledge, metacognitive awareness, awareness of problem-solving strategies, and student attitudes toward mathematical word problem solving among primary school students. The experimental group (N = 96)…
Kaur, Berinderjeet; Areepattamannil, Shaljan
2012-01-01
This study, drawing on data from the Programme for International Student Assessment (PISA) 2009, explored the influences of metacognitive and self-regulated learning strategies for reading on mathematical literacy of adolescents in Australia and Singapore. Ordinary least squares (OLS) regression analyses revealed the positive influences of…
Peltier, Corey; Vannest, Kimberly J.
2016-01-01
The purpose of this study was to analyze the effects of schema instruction on the mathematical problem solving of students with emotional or behavioral disorders (EBD). The participants were two fourth-grade students identified with EBD. The intervention package consisted of schema instruction, strategy instruction on problem-solving heuristics…
Suhaimi, Zuhairina; Shahrill, Masitah; Tengah, Khairul Amilin; Abbas, Nor'Arifahwati Haji
2016-01-01
This study incorporated the use of writing-to-learn strategy, particularly journal writing, in Grade 10 mathematics lessons. Although part of a study conducted to investigate the effects of journal writing on academically lower-achieving learners with English as their second language, this paper will focus only on the students' perceptions of…
Awofala, Adeneye O. A.; Arigbabu, Abayomi A.; Awofala, Awoyemi A.
2013-01-01
The study investigated the relative effectiveness of framing and team assisted individualised (TAI) instructional strategies on the attitudes toward mathematics of 350 senior secondary school year two Nigerian students. The moderating effects of gender and style of categorisation were also examined. The study adopted pre-test and post-test control…
Qudah, Ahmad Hassan
2016-01-01
This study aimed at identify the effect of using a proposed teaching strategy based on the selective thinking in acquire mathematical concepts by Classroom Teacher Students at Al- al- Bayt University, The sample of the study consisted of (74) students, equally distributed into a control group and an experimental group. The selective thinking…
Frederick-Jonah, Toinpere Mercy; Igbojinwaekwu, Patrick Chukwuemeka
2015-01-01
This study investigated the effects of game and poem-enhanced instructional strategies on students' interest in mathematics. The moderating effects of verbal ability were also examined on the dependent variable. A quasi-experimental design was adopted. Three hundred and forty four students in the sixth year of their primary education (primary 6…
Koyuncu, Ilhan; Akyuz, Didem; Cakiroglu, Erdinc
2015-01-01
This study aims to investigate plane geometry problem-solving strategies of prospective mathematics teachers using dynamic geometry software (DGS) and paper-and-pencil (PPB) environments after receiving an instruction with GeoGebra (GGB). Four plane geometry problems were used in a multiple case study design to understand the solution strategies…
Nandi, Swapan Kumar; Jana, Soovoojeet; Mandal, Manotosh; Kar, T. K.
In this paper, we proposed and analyzed a susceptible-infected-recovered (SIR) type epidemic model to investigate the effect of transport-related infectious diseases namely tuberculosis, measles, rubella, influenza, sexually transmitted diseases, etc. The existence and stability criteria of both the diseases include free equilibrium point and endemic equilibrium point which are established and the threshold parametric condition for which the system passes through a transcritical bifurcation is also obtained. Optimal control strategy for control parameters is formulated and solved both theoretically and numerically. Lastly, we not only illustrate our theoretical results through graphical illustrations but also computer simulation is used to show that our model would be a good model to study the SARS epidemic in 2003.
Anodic Cyclization Reactions and the Mechanistic Strategies That Enable Optimization.
Feng, Ruozhu; Smith, Jake A; Moeller, Kevin D
2017-09-19
Oxidation reactions are powerful tools for synthesis because they allow us to reverse the polarity of electron-rich functional groups, generate highly reactive intermediates, and increase the functionality of molecules. For this reason, oxidation reactions have been and continue to be the subject of intense study. Central to these efforts is the development of mechanism-based strategies that allow us to think about the reactive intermediates that are frequently central to the success of the reactions and the mechanistic pathways that those intermediates trigger. For example, consider oxidative cyclization reactions that are triggered by the removal of an electron from an electron-rich olefin and lead to cyclic products that are functionalized for further elaboration. For these reactions to be successful, the radical cation intermediate must first be generated using conditions that limit its polymerization and then channeled down a productive desired pathway. Following the cyclization, a second oxidation step is necessary for product formation, after which the resulting cation must be quenched in a controlled fashion to avoid undesired elimination reactions. Problems can arise at any one or all of these steps, a fact that frequently complicates reaction optimization and can discourage the development of new transformations. Fortunately, anodic electrochemistry offers an outstanding opportunity to systematically probe the mechanism of oxidative cyclization reactions. The use of electrochemical methods allows for the generation of radical cations under neutral conditions in an environment that helps prevent polymerization of the intermediate. Once the intermediates have been generated, a series of "telltale indicators" can be used to diagnose which step in an oxidative cyclization is problematic for less successful transformation. A set of potential solutions to address each type of problem encountered has been developed. For example, problems with the initial
Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; N. Soltani, Mohsen
2017-01-01
Offshore wind farm has drawn more and more attention recently due to its higher energy capacity and more freedom to occupy area. However, the investment is higher. In order to make a cost-effective wind farm, the wind farm layout should be optimized. The wake effect is one of the dominant factors...... leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing...... the direction of wind farm placement and the spacing between WTs, the control strategy’s impact on energy yields is also discussed. Since the problem is non-convex and lots of optimization variables are involved, an evolutionary algorithm, the particle swarm optimization algorithm (PSO), is adopted to find...
Verguet, Stéphane; Johri, Mira; Morris, Shaun K; Gauvreau, Cindy L; Jha, Prabhat; Jit, Mark
2015-03-03
The Measles & Rubella Initiative, a broad consortium of global health agencies, has provided support to measles-burdened countries, focusing on sustaining high coverage of routine immunization of children and supplementing it with a second dose opportunity for measles vaccine through supplemental immunization activities (SIAs). We estimate optimal scheduling of SIAs in countries with the highest measles burden. We develop an age-stratified dynamic compartmental model of measles transmission. We explore the frequency of SIAs in order to achieve measles control in selected countries and two Indian states with high measles burden. Specifically, we compute the maximum allowable time period between two consecutive SIAs to achieve measles control. Our analysis indicates that a single SIA will not control measles transmission in any of the countries with high measles burden. However, regular SIAs at high coverage levels are a viable strategy to prevent measles outbreaks. The periodicity of SIAs differs between countries and even within a single country, and is determined by population demographics and existing routine immunization coverage. Our analysis can guide country policymakers deciding on the optimal scheduling of SIA campaigns and the best combination of routine and SIA vaccination to control measles. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Lotfian, Reza; Najafi, Mehdi
2018-02-26
Background Every year, many mining accidents occur in underground mines all over the world resulting in the death and maiming of many miners and heavy financial losses to mining companies. Underground mining accounts for an increasing share of these events due to their special circumstances and the risks of working therein. Thus, the optimal location of emergency stations within the network of an underground mine in order to provide medical first aid and transport injured people at the right time, plays an essential role in reducing deaths and disabilities caused by accidents Objective The main objective of this study is to determine the location of emergency stations (ES) within the network of an underground coal mine in order to minimize the outreach time for the injured. Methods A three-objective mathematical model is presented for placement of ES facility location selection and allocation of facilities to the injured in various stopes. Results Taking into account the radius of influence for each ES, the proposed model is capable to reduce the maximum time for provision of emergency services in the event of accident for each stope. In addition, the coverage or lack of coverage of each stope by any of the emergency facility is determined by means of Floyd-Warshall algorithm and graph. To solve the problem, a global criterion method using GAMS software is used to evaluate the accuracy and efficiency of the model. Conclusions 7 locations were selected from among 46 candidates for the establishment of emergency facilities in Tabas underground coal mine. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Energy Technology Data Exchange (ETDEWEB)
1994-01-01
The report with collected proceedings from a conference, deals with mathematics of oil recovery with the focus on history match and recovery optimization. Topics of proceedings are as follow: Calculating optimal parameters for history matching; new technique to improve the efficiency of history matching of full-field models; flow constrained reservoir characterization using Bayesian inversion; analysis of multi-well pressure transient data; new approach combining neural networks and simulated annealing for solving petroleum inverse problems; automatic history matching by use of response surfaces and experimental design; determining the optimum location of a production well in oil reservoirs. Seven papers are prepared. 108 refs., 45 figs., 12 tabs.
Optimal Allocation of the Irrigation Water Through a Non Linear Mathematical Model
Directory of Open Access Journals (Sweden)
P. Rubino
2008-09-01
Full Text Available A study on the optimal allocation of the irrigation water among 9 crops (autumnal and spring sugar beet, spring and summer grain maize, dry and shell bean, eggplant, pepper and processing tomato has been carried out, utilizing experimental data of yield response to irrigation obtained in different years in Southern Italy (Policoro MT, 40° 12’ Northern Lat.; 16° 40’Western Long.. Fitting Mitscherlich’s equation modified by Giardini and Borin to the experimental data of each crop, the curve response parameters have been calculated: A = maximum achievable yield in the considered area (t ha-1; b = extra-irrigation water used by the crop (m3 ha-1; c = water action factor (ha m- 3; K, calculated only for tomato crop. ,decreasing factor due to the water exceeding the optimal seasonal irrigation volume (100% of the Crop Maximum Evapotranspiration less effective rainfall, ETMlr. The A values, using the prices of the agricultural produces and the irrigation water tariffs applied by the Consorzio Irriguo della Capitanata, have been converted in Value of Production (VP less the fixed and variable irrigation costs (VPlic. The equation parameters were used in a non linear mathematical model written in GAMS (General Algebraic Modelling System, in order to define the best irrigation water allocation amongst the 9 crops across the entire range of water availability and the volume of maximum economical advantage, hypothesising that each crop occupied the same surface (1 ha. This seasonal irrigation volume, that corresponded to the maximum total VPlic, was equal to 37000 m3. Moreover, the model allowed to define the best irrigation water distribution among the crops also for total available volumes lower than that of maximum economical advantage (37000 m3. Finally, it has been underlined that the vegetable crops should be irrigated with seasonal irrigation volumes equal to 100% of the ETM, whereas the summer and spring maize and the autumnal and spring
Mathematical modeling for prediction and optimization of TIG welding pool geometry
Directory of Open Access Journals (Sweden)
U. Esme
2009-04-01
Full Text Available In this work, nonlinear and multi-objective mathematical models were developed to determine the process parameters corresponding to optimum weld pool geometry. The objectives of the developed mathematical models are to maximize tensile load (TL, penetration (P, area of penetration (AP and/or minimize heat affected zone (HAZ, upper width (UW and upper height (UH depending upon the requirements.
Erdogan, Abdulkadir
2015-01-01
Turkish primary mathematics curriculum emphasizes the role of problem solving for teaching mathematics and pays particular attention to problem solving strategies. Patterns as a subject and the use of patterns as a non-routine problem solving strategy are also emphasized in the curriculum. The primary purpose of this study was to determine how…
Directory of Open Access Journals (Sweden)
Mircea LUPU
2012-05-01
Full Text Available The people’s life and activity in nature and society depends primary by air, water, light, climate, ground and by using the aeolian, hydraulic, mechanic and electrical energies, generated by the dynamics of these environments. The dynamics of these phenomena from the nature is linear and majority nonlinear, probabilistic – inducing a mathematical modeling – for the optimal control, with the equations with a big complexity. In the paper the author presents new mathematical models and methods in the optimization of these phenomena with technical applications: the optimization of the hydraulic, aeolian turbine’s blades or for the eliminating air pollutants and residual water purification; the actions hydropneumatics (robotics to balance the ship in roll stability, optimizing the sails (wind powered for extreme durability or propelling force, optimizing aircraft profiles for the drag or the lift forces, directing navigation, parachute brake, the wall, etc. The scientific results are accompanied by numerical calculations, integrating in the specialized literature from our country and foreign.
Optimal Software Strategies in the Presence of Network Externalities
Liu, Yipeng
2009-01-01
Network externalities or alternatively termed network effects are pervasive in computer software markets. While software vendors consider pricing strategies, they must also take into account the impact of network externalities on their sales. My main interest in this research is to describe a firm's strategies and behaviors in the presence of…
Optimizing the stirring strategy for the vibrating intrinsic reverberation chamber
Serra, Ramiro; Serra, Ramiro; Leferink, Frank Bernardus Johannes
2010-01-01
This work describes the definition, application and assessment of a factorial plan with the aim of gaining insight on what kind of stirring strategy could work the best in a vibrating intrinsic reverberation chamber. Three different stirring strategies were defined as factors of a factorial
Optimal Pricing Strategies for New Products in Dynamic Oligopolies
Engelbert Dockner; Steffen Jørgensen
1988-01-01
This paper deals with the determination of optimal pricing policies for firms in oligopolistic markets. The problem is studied as a differential game and optimal pricing policies are established as Nash open-loop controls. Cost learning effects are assumed such that unit costs are decreasing with cumulative output. Discounting of future profits is also taken into consideration. Initially, the problem is addressed in a general framework, and we proceed to study some specific cases that are rel...
Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units
Directory of Open Access Journals (Sweden)
Jinjiao Hou
2018-05-01
Full Text Available This paper proposes a multi-objective optimization method for the start-up strategy of pumped storage units (PSU for the first time. In the multi-objective optimization method, the speed rise time and the overshoot during the process of the start-up are taken as the objectives. A precise simulation platform is built for simulating the transient process of start-up, and for calculating the objectives based on the process. The Multi-objective Particle Swarm Optimization algorithm (MOPSO is adopted to optimize the widely applied start-up strategies based on one-stage direct guide vane control (DGVC, and two-stage DGVC. Based on the Pareto Front obtained, a multi-objective decision-making method based on the relative objective proximity is used to sort the solutions in the Pareto Front. Start-up strategy optimization for a PSU of a pumped storage power station in Jiangxi Province in China is conducted in experiments. The results show that: (1 compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize; (2 multi-objective optimization of strategy based on two-stage DGVC achieves better solution for a quick and smooth start-up of PSU than that of the strategy based on one-stage DGVC.
Heinsch, Stephen C; Das, Siba R; Smanski, Michael J
2018-01-01
Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems.
DEFF Research Database (Denmark)
Lund, Henrik; Salgi, Georges; Elmegaard, Brian
2009-01-01
on electricity spot markets by storing energy when electricity prices are low and producing electricity when prices are high. In order to make a profit on such markets, CAES plant operators have to identify proper strategies to decide when to sell and when to buy electricity. This paper describes three...... plants will not be able to achieve such optimal operation, since the fluctuations of spot market prices in the coming hours and days are not known. Consequently, two simple practical strategies have been identified and compared to the results of the optimal strategy. This comparison shows that...... independent computer-based methodologies which may be used for identifying the optimal operation strategy for a given CAES plant, on a given spot market and in a given year. The optimal strategy is identified as the one which provides the best business-economic net earnings for the plant. In practice, CAES...
Directory of Open Access Journals (Sweden)
Heri Retnawati
2017-07-01
Full Text Available The quality of national examination items plays an enormous role in identifying students’ competencies mastery and their difficulties. This study aims to identify the difficult items in the Junior High School Mathematics National Examination, to find the factors that cause students’ difficulty and to reveal the strategies that the teachers and the students might implement in order to overcome them. The study is phenomenological research with the mixed methods. The data were collected using documentation of students’ responses and focus group discussion (FGD of teachers. The data analysis was conducted using Milles & Hubberman steps. The results of the study showed that there were 4 difficult items of the 40 test items for the students. The students’ difficulties were the lack of concept understanding, difficulties in calculating, difficulties in selecting information, being deceived by the distractors, being unaccustomed to completing complex and non-integers test items, and completing contextual test items that have been presented in the form of figures or narrative texts.
Optimal Strategy Analysis of a Competing Portfolio Market with a Polyvariant Profit Function
International Nuclear Information System (INIS)
Bogolubov, Nikolai N. Jr.; Kyshakevych, Bohdan Yu.; Blackmore, Denis; Prykarpatsky, Anatoliy K.
2010-12-01
A competing market model with a polyvariant profit function that assumes 'zeitnot' stock behavior of clients is formulated within the banking portfolio medium and then analyzed from the perspective of devising optimal strategies. An associated Markov process method for finding an optimal choice strategy for monovariant and bivariant profit functions is developed. Under certain conditions on the bank 'promotional' parameter with respect to the 'fee' for a missed share package transaction and at an asymptotically large enough portfolio volume, universal transcendental equations - determining the optimal share package choice among competing strategies with monovariant and bivariant profit functions - are obtained. (author)
Anwar, Md Rajib; Camarda, Kyle V; Kieweg, Sarah L
2015-06-25
Topically applied microbicide gels can provide a self-administered and effective strategy to prevent sexually transmitted infections (STIs). We have investigated the interplay between vaginal tissue elasticity and the yield-stress of non-Newtonian fluids during microbicide deployment. We have developed a mathematical model of tissue deformation driven spreading of microbicidal gels based on thin film lubrication approximation and demonstrated the effect of tissue elasticity and fluid yield-stress on the spreading dynamics. Our results show that both elasticity of tissue and yield-stress rheology of gel are strong determinants of the coating behavior. An optimization framework has been demonstrated which leverages the flow dynamics of yield-stress fluid during deployment to maximize retention while reaching target coating length for a given tissue elasticity. Copyright © 2015 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Marya Viorst Gwadz
2017-05-01
Full Text Available Abstract Background More than half of persons living with HIV (PLWH in the United States are insufficiently engaged in HIV primary care and not taking antiretroviral therapy (ART, mainly African Americans/Blacks and Hispanics. In the proposed project, a potent and innovative research methodology, the multiphase optimization strategy (MOST, will be employed to develop a highly efficacious, efficient, scalable, and cost-effective intervention to increase engagement along the HIV care continuum. Whereas randomized controlled trials are valuable for evaluating the efficacy of multi-component interventions as a package, they are not designed to evaluate which specific components contribute to efficacy. MOST, a pioneering, engineering-inspired framework, addresses this problem through highly efficient randomized experimentation to assess the performance of individual intervention components and their interactions. We propose to use MOST to engineer an intervention to increase engagement along the HIV care continuum for African American/Black and Hispanic PLWH not well engaged in care and not taking ART. Further, the intervention will be optimized for cost-effectiveness. A similar set of multi-level factors impede both HIV care and ART initiation for African American/Black and Hispanic PLWH, primary among them individual- (e.g., substance use, distrust, fear, social- (e.g., stigma, and structural-level barriers (e.g., difficulties accessing ancillary services. Guided by a multi-level social cognitive theory, and using the motivational interviewing approach, the study will evaluate five distinct culturally based intervention components (i.e., counseling sessions, pre-adherence preparation, support groups, peer mentorship, and patient navigation, each designed to address a specific barrier to HIV care and ART initiation. These components are well-grounded in the empirical literature and were found acceptable, feasible, and promising with respect to
Scout or Cavalry? Optimal Discovery Strategies for GRBs
International Nuclear Information System (INIS)
Nemiroff, Robert J.
2004-01-01
Many present and past gamma-ray burst (GRB) detectors try to be not only a 'scout', discovering new GRBs, but also the 'cavalry', simultaneously optimizing on-board science return. Recently, however, most GRB science return has moved out from the gamma-ray energy bands where discovery usually occurs. Therefore a future gamma-ray instrument that is only a scout might best optimize future GRB science. Such a scout would specialize solely in the initial discovery of GRBs, determining only those properties that would allow an unambiguous handoff to waiting cavalry instruments. Preliminary general principles of scout design and cadence are discussed. Scouts could implement observing algorithms optimized for finding GRBs with specific attributes of duration, location, or energy. Scout sky-scanning algorithms utilizing a return cadence near to desired durations of short GRBs are suggested as a method of discovering GRBs in the unexplored short duration part of the GRB duration distribution
Investment Strategies Optimization based on a SAX-GA Methodology
Canelas, António M L; Horta, Nuno C G
2013-01-01
This book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
The role of mathematical models in the optimization of radiopharmaceutical therapy
International Nuclear Information System (INIS)
Divgi, C.
2001-01-01
Mathematical models have been used in radiopharmaceutical therapy for over five decades. These have served to determine the amount of radioactivity required to treat disease, as in the therapy of hyperthyroidism with iodine-131, or, more frequently, to determine the largest amount of radioactivity that can be safely administered. Mathematical models are especially useful in the determination of fractionated radiopharmaceutical therapy. This review will briefly outline the historical development and current utility of mathematical models in radiopharmaceutical therapy, including thyroid disorders and radioimmunotherapy; and describe the potential of modeling in fractionated therapy. The extended application of such models to currently used radiopharmaceutical therapy based on indices of body mass or surface area, to alleviate toxicity and increase radiation dose to tumour, will be proposed. Finally, future applications of mathematical models in radiopharmaceutical therapy will be outlined. (author)
Mohammad Aghaei; Amin Asadollahi; Elham Vahedi; Mahdi Pirooz
2013-01-01
To maintain and achieve optimal growth, development and to be more competitive, organizations need a comprehensive and coherent plan compatible with their objectives and goals which is called strategic planning. This research aims to analyse strategically “Etka Chain Stores” and to propose optimal strategies by using SWOT model and based on fuzzy logic. The scope of this research is limited to “Etka Chain stores in Tehran”. As instrumentation, a questioner, consisting of 138 questions, was us...
Optimizing torque vectoring strategies for an electric vehicle concept
van Boekel, J.J.P.; Besselink, I.J.M.; Nijmeijer, H.; Rauh, J.; Knorr, S.; Durnberger, J.
2013-01-01
As part of the internship project carried out at Daimler AG, this report describes the application and optimization of torque vectoring on a research vehicle based on the Mercedes- Benz SLS AMG E-CELL. A concise introduction is given regarding the MATLAB scripts and Simulink models that were used
Taxing Strategies for Carbon Emissions: A Bilevel Optimization Approach
Directory of Open Access Journals (Sweden)
Wei Wei
2014-04-01
Full Text Available This paper presents a quantitative and computational method to determine the optimal tax rate among generating units. To strike a balance between the reduction of carbon emission and the profit of energy sectors, the proposed bilevel optimization model can be regarded as a Stackelberg game between the government agency and the generation companies. The upper-level, which represents the government agency, aims to limit total carbon emissions within a certain level by setting optimal tax rates among generators according to their emission performances. The lower-level, which represents decision behaviors of the grid operator, tries to minimize the total production cost under the tax rates set by the government. The bilevel optimization model is finally reformulated into a mixed integer linear program (MILP which can be solved by off-the-shelf MILP solvers. Case studies on a 10-unit system as well as a provincial power grid in China demonstrate the validity of the proposed method and its capability in practical applications.
An Optimal Stochastic Investment and Consumption Strategy with ...
African Journals Online (AJOL)
This paper considers a single investor who owns a production plant that generates units of consumption goods in a capitalist economy. The goal is to choose optimal investment and consumption policies that maximize the finite horizon expected discounted logarithmic utility of consumption and terminal wealth. A dynamical ...
Optimal detection and control strategies for invasive species management
Shefali V. Mehta; Robert G. Haight; Frances R. Homans; Stephen Polasky; Robert C. Venette
2007-01-01
The increasing economic and environmental losses caused by non-native invasive species amplify the value of identifying and implementing optimal management options to prevent, detect, and control invasive species. Previous literature has focused largely on preventing introductions of invasive species and post-detection control activities; few have addressed the role of...
DEFF Research Database (Denmark)
Bozkurt, Hande; Quaglia, Alberto; Gernaey, Krist
The increasing number of alternative wastewater treatment (WWT) technologies and stricter effluent requirements imposed by regulations make the early stage decision making for WWTP layout design, which is currently based on expert decisions and previous experiences, much harder. This paper...... therefore proposes a new approach based on mathematical programming to manage the complexity of the problem and generate/identify novel and optimal WWTP layouts for municipal/domestic wastewater treatment. Towards this end, after developing a database consisting of primary, secondary and tertiary WWT...... solved to obtain the optimal WWT network and the optimal wastewater and sludge flow through the network. The tool is evaluated on a case study, which was chosen as the Benchmark Simulation Model no.1 (BSM1) and many retrofitting options for obtaining a cost-effective treatment were investigated...
International Nuclear Information System (INIS)
Hayes, R.B.; Haskell, E.H.; Kenner, G.H.
1996-01-01
Additive dose methods commonly used in electron paramagnetic resonance (EPR) dosimetry are time consuming and labor intensive. We have developed a mathematical approach for determining optimal spacing of applied doses and the number of spectra which should be taken at each dose level. Expected uncertainitites in the data points are assumed to be normally distributed with a fixed standard deviation and linearity of dose response is also assumed. The optimum spacing and number of points necessary for the minimal error can be estimated, as can the likely error in the resulting estimate. When low doses are being estimated for tooth enamel samples the optimal spacing is shown to be a concentration of points near the zero dose value with fewer spectra taken at a single high dose value within the range of known linearity. Optimization of the analytical process results in increased accuracy and sample throughput
Andreescu, Titu; Tetiva, Marian
2017-01-01
Building bridges between classical results and contemporary nonstandard problems, Mathematical Bridges embraces important topics in analysis and algebra from a problem-solving perspective. Blending old and new techniques, tactics and strategies used in solving challenging mathematical problems, readers will discover numerous genuine mathematical gems throughout that will heighten their appreciation of the inherent beauty of mathematics. Most of the problems are original to the authors and are intertwined in a well-motivated exposition driven by representative examples. The book is structured to assist the reader in formulating and proving conjectures, as well as devising solutions to important mathematical problems by making connections between various concepts and ideas from different areas of mathematics. Instructors and educators teaching problem-solving courses or organizing mathematics clubs, as well as motivated mathematics students from high school juniors to college seniors, will find Mathematical Bri...
Chang, Jen-Mei; Kwon, Chuhee; Stevens, Lora; Buonora, Paul
2016-01-01
This article presents implementation details and findings of a National Science Foundation Scholarship in Science, Technology, Engineering, and Mathematics Program (S-STEM) consisting of many high-impact practices to recruit and retain students in the physical sciences and mathematics programs, particularly first-generation and underrepresented…
Teachers Implementing Mathematical Problem Posing in the Classroom: Challenges and Strategies
Leung, Shuk-kwan S.
2013-01-01
This paper reports a study about how a teacher educator shared knowledge with teachers when they worked together to implement mathematical problem posing (MPP) in the classroom. It includes feasible methods for getting practitioners to use research-based tasks aligned to the curriculum in order to encourage children to pose mathematical problems.…
Relationship between Pedagogical Strategies and Teachers' Content Knowledge of Mathematics
Kanyongo, Gibbs Y.; Brown, Launcelot I.
2013-01-01
This study employed regression analysis to investigate the relationship between primary school teachers' pedagogical practices and their knowledge of mathematics. The sample composed of 606 Grade 6 mathematics teachers in Namibia, i.e. 304 (50.2%) males and 302 (49.8%) females. The study utilized existing questionnaire data collected by the…
Investigating the Optimal Management Strategy for a Healthcare Facility Maintenance Program
National Research Council Canada - National Science Library
Gaillard, Daria
2004-01-01
...: strategic partnering with an equipment management firm. The objective of this study is to create a decision-model for selecting the optimal management strategy for a healthcare organization's facility maintenance program...
An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model
International Nuclear Information System (INIS)
Liu, Kailong; Li, Kang; Yang, Zhile; Zhang, Cheng; Deng, Jing
2017-01-01
Lithium-ion batteries are widely adopted as the power supplies for electric vehicles. A key but challenging issue is to achieve optimal battery charging, while taking into account of various constraints for safe, efficient and reliable operation. In this paper, a triple-objective function is first formulated for battery charging based on a coupled thermoelectric model. An advanced optimal charging strategy is then proposed to develop the optimal constant-current-constant-voltage (CCCV) charge current profile, which gives the best trade-off among three conflicting but important objectives for battery management. To be specific, a coupled thermoelectric battery model is first presented. Then, a specific triple-objective function consisting of three objectives, namely charging time, energy loss, and temperature rise (both the interior and surface), is proposed. Heuristic methods such as Teaching-learning-based-optimization (TLBO) and particle swarm optimization (PSO) are applied to optimize the triple-objective function, and their optimization performances are compared. The impacts of the weights for different terms in the objective function are then assessed. Experimental results show that the proposed optimal charging strategy is capable of offering desirable effective optimal charging current profiles and a proper trade-off among the conflicting objectives. Further, the proposed optimal charging strategy can be easily extended to other battery types.
Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time
Directory of Open Access Journals (Sweden)
Daheng Peng
2017-10-01
Full Text Available In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.
Ndeffo Mbah , Martial L.; Gilligan , Christopher A.
2010-01-01
Abstract There is growing interest in incorporating economic factors into epidemiological models in order to identify optimal strategies for disease control when resources are limited. In this paper we consider how to optimize the control of a pathogen that is capable of infecting multiple hosts with different rates of transmission within and between species. Our objective is to find control strategies that maximize the discounted number of healthy individuals. We consider two clas...
Directory of Open Access Journals (Sweden)
Musa Danjuma SHEHU
2008-06-01
Full Text Available This paper lays emphasis on formulation of two dimensional differential games via optimal control theory and consideration of control systems whose dynamics is described by a system of Ordinary Differential equation in the form of linear equation under the influence of two controls U(. and V(.. Base on this, strategies were constructed. Hence we determine the optimal strategy for a control say U(. under a perturbation generated by the second control V(. within a given manifold M.
The CEV Model and Its Application in a Study of Optimal Investment Strategy
Directory of Open Access Journals (Sweden)
Aiyin Wang
2014-01-01
Full Text Available The constant elasticity of variance (CEV model is used to describe the price of the risky asset. Maximizing the expected utility relating to the Hamilton-Jacobi-Bellman (HJB equation which describes the optimal investment strategies, we obtain a partial differential equation. Applying the Legendre transform, we transform the equation into a dual problem and obtain an approximation solution and an optimal investment strategies for the exponential utility function.
Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time
Daheng Peng; Fang Zhang
2017-01-01
In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.
Optimized Control Strategy For Over Loaded Offshore Wind Turbines
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Knudsen, Torben; Wisniewski, Rafal
2015-01-01
controller tuning for a given wind turbine. It also enables a very safe and robust comparison between a new control strategy and the present one. Main body of abstract Is it true that power de-rating indeed the best way to reduce loads? The power de-rating approach has the drawback of only indirectly...
Provencher, Véronique; Desrosiers, Johanne; Demers, Louise; Carmichael, Pierre-Hugues
2016-01-01
This study aimed to (1) determine the categories of behavioral coping strategies most strongly correlated with optimal seniors' social participation in different activity and role domains and (2) identify the demographic, health and environmental factors associated with the use of these coping strategies optimizing social participation. The sample consisted of 350 randomly recruited community-dwelling older adults (≥65 years). Coping strategies and social participation were measured, respectively, using the Inventory of Coping Strategies Used by the Elderly and Assessment of Life Habits questionnaires. Information about demographic, health and environmental factors was also collected during the interview. Regression analyses showed a strong relationship between the use of cooking- and transportation-related coping strategies and optimal participation in the domains of nutrition and community life, respectively. Older age and living alone were associated with increased use of cooking-related strategies, while good self-rated health and not living in a seniors' residence were correlated with greater use of transportation-related strategies. Our study helped to identify useful behavioral coping strategies that should be incorporated in disability prevention programs designed to promote community-dwelling seniors' social participation. However, the appropriateness of these strategies depends on whether they are used in relevant contexts and tailored to specific needs. Our results support the relevance of including behavioral coping strategies related to cooking and transportation in disability prevention programs designed to promote community-dwelling seniors' social participation in the domains of nutrition and community life, respectively. Older age and living alone were associated with increased use of cooking-related strategies, while good self-rated health and not living in a seniors' residence were correlated with greater use of transportation
Toropov, Andrey A; Toropova, Alla P
2014-06-01
The experimental data on the bacterial reverse mutation test on C60 nanoparticles (TA100) is examined as an endpoint. By means of the optimal descriptors calculated with the Monte Carlo method a mathematical model of the endpoint has been built up. The model is the mathematical function of (i) dose (g/plate); (ii) metabolic activation (i.e. with S9 mix or without S9 mix); and (iii) illumination (i.e. dark or irradiation). The statistical quality of the model is the following: n=10, r(2)=0.7549, q(2)=0.5709, s=7.67, F=25 (Training set); n=5, r(2)=0.8987, s=18.4 (Calibration set); and n=5, r(2)=0.6968, s=10.9 (Validation set). Copyright © 2013 Elsevier Ltd. All rights reserved.
Maintenance and test strategies to optimize NPP equipment performance
International Nuclear Information System (INIS)
Mayer, S.; Tomic, B.
2000-01-01
This paper proposes an approach to maintenance optimization of nuclear power plant components, which can help to increase both safety and availability. In order to evaluate the benefits of preventive maintenance on a quantitative basis, a software code has been developed for component performance and reliability simulation of safety related nuclear power plant equipment. A three state Markov model will be introduced, considering a degraded state in addition to an operational state and a failed state. (author)
Optimal Input Strategy for Plug and Play Process Control Systems
DEFF Research Database (Denmark)
Kragelund, Martin Nygaard; Leth, John-Josef; Wisniewski, Rafal
2010-01-01
This paper considers the problem of optimal operation of a plant, which goal is to maintain production at minimum cost. The system considered in this work consists of a joined plant and redundant input systems. It is assumed that each input system contributes to a flow of goods into the joined pa...... the performance of the plant. The results are applied to a coal fired power plant where an additional new fuel system, gas, becomes available....
Systems analysis as a tool for optimal process strategy
International Nuclear Information System (INIS)
Ditterich, K.; Schneider, J.
1975-09-01
For the description and the optimal treatment of complex processes, the methods of Systems Analysis are used as the most promising approach in recent times. In general every process should be optimised with respect to reliability, safety, economy and environmental pollution. In this paper the complex relations between these general optimisation postulates are established in qualitative form. These general trend relations have to be quantified for every particular system studied in practice
Mathematics Boot Camps: A Strategy for Helping Students to Bypass Remedial Courses
Hamilton, Marilyn A. L.
Many community colleges struggle to find the best strategy to help incoming at-risk students prepare for the placement test. The purpose of this quantitative quasi-experimental study, was to answer the question as to which of 2 programs, a 2-week, face-to-face mathematics refresher program, Math Boost-Up, or an online-only program, might increase the ACCUPLACER posttest scores of incoming community college students. The study used archival data for 136 students who self-selected to either participate in the Math Boost-Up program (the experiment group), or in the online-only program (the comparison group). Knowles's theory of adult learning, andragogy, served as the theoretical framework. Spearman, Kruskal-Wallis, Mann-Whitney, and chi-square tests were used to measure the effect of 4 moderator variables (age, high school GPA, number of minutes spent in MyFoundationsLab, and number of days spent in face-to-face sessions) on the pre- and posttest scores of students in each group. The results indicated that students in the Math Boost-Up program experienced statistically significant gains in arithmetic and elementary algebra than did those students in the online-only program. The results also indicated that the 4 moderator variables affected gains in posttest scores. Additionally, the results disproved the andragogical premise that students would be self-directed and would self-select to participate in the intervention. A recommendation was that participation in the face-to-face refresher program should be mandatory. The study contributes to social change by providing evidence that short-term refresher programs could increase the scores of students on placement tests.
Optimal Quality Strategy and Matching Service on Crowdfunding Platforms
Directory of Open Access Journals (Sweden)
Wenqing Wu
2018-04-01
Full Text Available This paper develops a crowdfunding platform model incorporating quality and a matching service from the perspective of a two-sided market. It aims to explore the impact of different factors on the optimal quality threshold and matching service in a context of crowdfunding from the perspective of a two-sided market. We discuss the impact of different factors on the optimal quality threshold and matching service. Two important influential factors are under consideration, simultaneously. One is the quality threshold of admission and the other is the matching efficiency on crowdfunding platforms. This paper develops a two-sided market model incorporating quality, a matching service, and the characters of crowdfunding campaigns. After attempting to solve the model by derivative method, this paper identifies the mechanism of how the parameters influence the optimal quality threshold and matching service. Additionally, it compares the platform profits in scenarios with and without an exclusion policy. The results demonstrate that excluding low-quality projects is profitable when funder preference for project quality is substantial enough. Crowdfunding platform managers would be unwise to admit the quality threshold of the crowdfunding project and charge entrance fees when the parameter of funder preference for project quality is small.
Multiresolution strategies for the numerical solution of optimal control problems
Jain, Sachin
There exist many numerical techniques for solving optimal control problems but less work has been done in the field of making these algorithms run faster and more robustly. The main motivation of this work is to solve optimal control problems accurately in a fast and efficient way. Optimal control problems are often characterized by discontinuities or switchings in the control variables. One way of accurately capturing the irregularities in the solution is to use a high resolution (dense) uniform grid. This requires a large amount of computational resources both in terms of CPU time and memory. Hence, in order to accurately capture any irregularities in the solution using a few computational resources, one can refine the mesh locally in the region close to an irregularity instead of refining the mesh uniformly over the whole domain. Therefore, a novel multiresolution scheme for data compression has been designed which is shown to outperform similar data compression schemes. Specifically, we have shown that the proposed approach results in fewer grid points in the grid compared to a common multiresolution data compression scheme. The validity of the proposed mesh refinement algorithm has been verified by solving several challenging initial-boundary value problems for evolution equations in 1D. The examples have demonstrated the stability and robustness of the proposed algorithm. The algorithm adapted dynamically to any existing or emerging irregularities in the solution by automatically allocating more grid points to the region where the solution exhibited sharp features and fewer points to the region where the solution was smooth. Thereby, the computational time and memory usage has been reduced significantly, while maintaining an accuracy equivalent to the one obtained using a fine uniform mesh. Next, a direct multiresolution-based approach for solving trajectory optimization problems is developed. The original optimal control problem is transcribed into a
Directory of Open Access Journals (Sweden)
Jingxian Hao
2016-11-01
Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2012-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2013-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
Dynamic optimal strategies in transboundary pollution game under learning by doing
Chang, Shuhua; Qin, Weihua; Wang, Xinyu
2018-01-01
In this paper, we present a transboundary pollution game, in which emission permits trading and pollution abatement costs under learning by doing are considered. In this model, the abatement cost mainly depends on the level of pollution abatement and the experience of using pollution abatement technology. We use optimal control theory to investigate the optimal emission paths and the optimal pollution abatement strategies under cooperative and noncooperative games, respectively. Additionally, the effects of parameters on the results have been examined.
The Optimal Strategy to Research Pension Funds in China Based on the Loss Function
Directory of Open Access Journals (Sweden)
Jian-wei Gao
2007-10-01
Full Text Available Based on the theory of actuarial present value, a pension fund investment goal can be formulated as an objective function. The mean-variance model is extended by defining the objective loss function. Furthermore, using the theory of stochastic optimal control, an optimal investment model is established under the minimum expectation of loss function. In the light of the Hamilton-Jacobi-Bellman (HJB equation, the analytic solution of the optimal investment strategy problem is derived.
The Optimal Strategy to Research Pension Funds in China Based on the Loss Function
Gao, Jian-wei; Guo, Hong-zhen; Ye, Yan-cheng
2007-01-01
Based on the theory of actuarial present value, a pension fund investment goal can be formulated as an objective function. The mean-variance model is extended by defining the objective loss function. Furthermore, using the theory of stochastic optimal control, an optimal investment model is established under the minimum expectation of loss function. In the light of the Hamilton-Jacobi-Bellman (HJB) equation, the analytic solution of the optimal investment strategy problem is derived.
Optimal vaccination strategies against vector-borne diseases
DEFF Research Database (Denmark)
Græsbøll, Kaare; Enøe, Claes; Bødker, Rene
2014-01-01
Using a process oriented semi-agent based model, we simulated the spread of Bluetongue virus by Culicoides, biting midges, between cattle in Denmark. We evaluated the minimum vaccination cover and minimum cost for eight different preventive vaccination strategies in Denmark. The simulation model ...... results when index cases were in the vaccinated areas. However, given that the long-range spread of midge borne disease is still poorly quantified, more robust national vaccination schemes seem preferable....
Optimal Pricing Strategy for Wireless Social Community Networks
Mazloumian, Amin; Manshaei, Mohammad Hossein; Felegyhazi, Mark; Hubaux, Jean-Pierre
2008-01-01
The increasing number of mobile applications fuels the demand for affordable and ubiquitous wireless access. The traditional wireless network technologies such as EV-DO or WiMAX provide this service but require a huge upfront investment in infrastructure and spectrum. On the contrary, as they do not have to face such an investment, social community operators rely on subscribers who constitute a community of users. The pricing strategy of the provided wireless access is an open problem for thi...
In-operation learning of optimal wind farm operation strategy
Oliva Gratacós, Joan
2017-01-01
In a wind farm, power losses due to wind turbine wake effects can be up to 30-40% under certain conditions. As the global installed wind power capacity increases, the mitigation of wake effects in wind farms is gaining more importance. Following a conventional control strategy, each individual turbine maximizes its own power production without taking into consideration its effects on the performance of downstream turbines. Therefore, this control scheme results in operation con...
Optimization Strategy to Capitalize on the Romanian Tourism Potential
PhD Lecturer Dindire Laura; PhD Reader Dugan Silvia
2010-01-01
An important direction of the improvement of promotional activities achieved both by the decisional governmental and non-governmental organisms within the tourist services sector and by the tourism firms, both on an intern and international level, is the promotional strategy. Consisting in the mastership of obtaining the best results, through organizing, coordination, prediction, communication and control activities, the promotional management means knowing and understanding the intern and in...
Fueling strategies to optimize performance: training high or training low?
Burke, L M
2010-10-01
Availability of carbohydrate as a substrate for the muscle and central nervous system is critical for the performance of both intermittent high-intensity work and prolonged aerobic exercise. Therefore, strategies that promote carbohydrate availability, such as ingesting carbohydrate before, during and after exercise, are critical for the performance of many sports and a key component of current sports nutrition guidelines. Guidelines for daily carbohydrate intakes have evolved from the "one size fits all" recommendation for a high-carbohydrate diets to an individualized approach to fuel needs based on the athlete's body size and exercise program. More recently, it has been suggested that athletes should train with low carbohydrate stores but restore fuel availability for competition ("train low, compete high"), based on observations that the intracellular signaling pathways underpinning adaptations to training are enhanced when exercise is undertaken with low glycogen stores. The present literature is limited to studies of "twice a day" training (low glycogen for the second session) or withholding carbohydrate intake during training sessions. Despite increasing the muscle adaptive response and reducing the reliance on carbohydrate utilization during exercise, there is no clear evidence that these strategies enhance exercise performance. Further studies on dietary periodization strategies, especially those mimicking real-life athletic practices, are needed. © 2010 John Wiley & Sons A/S.
Improved quantum-behaved particle swarm optimization with local search strategy
Directory of Open Access Journals (Sweden)
Maolong Xi
2017-03-01
Full Text Available Quantum-behaved particle swarm optimization, which was motivated by analysis of particle swarm optimization and quantum system, has shown compared performance in finding the optimal solutions for many optimization problems to other evolutionary algorithms. To address the problem of premature, a local search strategy is proposed to improve the performance of quantum-behaved particle swarm optimization. In proposed local search strategy, a super particle is presented which is a collection body of randomly selected particles’ dimension information in the swarm. The selected probability of particles in swarm is different and determined by their fitness values. To minimization problems, the fitness value of one particle is smaller; the selected probability is more and will contribute more information in constructing the super particle. In addition, in order to investigate the influence on algorithm performance with different local search space, four methods of computing the local search radius are applied in local search strategy and propose four variants of local search quantum-behaved particle swarm optimization. Empirical studies on a suite of well-known benchmark functions are undertaken in order to make an overall performance comparison among the proposed methods and other quantum-behaved particle swarm optimization. The simulation results show that the proposed quantum-behaved particle swarm optimization variants have better advantages over the original quantum-behaved particle swarm optimization.
A Mathematical Model of Economic Population Dynamics in a Country That Has Optimal Zakat Management
Subhan, M.
2018-04-01
Zakat is the main tools against two issues in Islamic economy: economic justice and helping the poor. However, no government of Islamic countries can solve the economic disparity today. A mathematical model could give some understanding about this phenomenon. The goal of this research is to obtain a mathematical model that can describe the dynamic of economic group population. The research is theoretical based on relevance references. From the analytical and numerical simulation, we conclude that well-manage zakat and full comitment of the wealthy can achieve wealth equilibrium that represents minimum poverty.
Integrated Emission Management strategy for cost-optimal engine-aftertreatment operation
Cloudt, R.P.M.; Willems, F.P.T.
2011-01-01
A new cost-based control strategy is presented that optimizes engine-aftertreatment performance under all operating conditions. This Integrated Emission Management strategy minimizes fuel consumption within the set emission limits by on-line adjustment of air management based on the actual state of
Optimization as a Reasoning Strategy for Dealing with Socioscientific Decision-Making Situations
Papadouris, Nicos
2012-01-01
This paper reports on an attempt to help 12-year-old students develop a specific optimization strategy for selecting among possible solutions in socioscientific decision-making situations. We have developed teaching and learning materials for elaborating this strategy, and we have implemented them in two intact classes (N = 48). Prior to and after…
Exploring optimal fertigation strategies for orange production, using soil-crop modelling
Qin, Wei; Heinen, Marius; Assinck, Falentijn B.T.; Oenema, Oene
2016-01-01
Water and nitrogen (N) are two key limiting factors in orange (Citrus sinensis) production. The amount and the timing of water and N application are critical, but optimal strategies have not yet been well established. This study presents an analysis of 47 fertigation strategies examined by a
Optimal Coordinated Strategy Analysis for the Procurement Logistics of a Steel Group
Directory of Open Access Journals (Sweden)
Lianbo Deng
2014-01-01
Full Text Available This paper focuses on the optimization of an internal coordinated procurement logistics system in a steel group and the decision on the coordinated procurement strategy by minimizing the logistics costs. Considering the coordinated procurement strategy and the procurement logistics costs, the aim of the optimization model was to maximize the degree of quality satisfaction and to minimize the procurement logistics costs. The model was transformed into a single-objective model and solved using a simulated annealing algorithm. In the algorithm, the supplier of each subsidiary was selected according to the evaluation result for independent procurement. Finally, the effect of different parameters on the coordinated procurement strategy was analysed. The results showed that the coordinated strategy can clearly save procurement costs; that the strategy appears to be more cooperative when the quality requirement is not stricter; and that the coordinated costs have a strong effect on the coordinated procurement strategy.
Optimization Strategy of the APR+ BOP Technical Specifications
International Nuclear Information System (INIS)
Cho, Yoon Sang; Lee, Jae Gon; Han, Sung Heum
2016-01-01
The BOP is one of the key factors for successful project implementation of NPP. In constructing the APR1400 NPP, the BOP procurement has been one of the biggest concerns. Due to the design changes and increased capacity of equipment in NPP, lots of BOPs should be ‘first supplied equipment’ [hereinafter, ‘FSE’]. The manufacture-ability, and the performances of FSEs have not been fully proved and tested, manufacturers and suppliers are requested to submit Reports for Equipment Qualification Evaluation in accordance with 10 CFR 50.49, IEEE 323. They need at least 1-2 years’ tests for Environment Qualification (EQ) and Seismic Qualification (SQ). This study is focused how to prepare the BOP purchase specifications in order to control the FSEs, especially in safety class equipment. With the optimization plan for BOP packages of this study, the FSEs’ occurrence can be reasonably controlled as low as possible. For successful NPP project, the concerns in procuring BOPs shall be fully analyzed beforehand. Now Korea is preparing new era of APR+, with closing the time of APR1400. The technical specification of APR+ BOPs can be developed and prepared successfully and very effectively according to this optimization plan. This will be a great contribution not only in constructing APR+ in time, but also in exporting APR+ overseas, all over the world in the future
Optimization Strategy of the APR+ BOP Technical Specifications
Energy Technology Data Exchange (ETDEWEB)
Cho, Yoon Sang; Lee, Jae Gon; Han, Sung Heum [KHNP CRI, Daejeon (Korea, Republic of)
2016-10-15
The BOP is one of the key factors for successful project implementation of NPP. In constructing the APR1400 NPP, the BOP procurement has been one of the biggest concerns. Due to the design changes and increased capacity of equipment in NPP, lots of BOPs should be ‘first supplied equipment’ [hereinafter, ‘FSE’]. The manufacture-ability, and the performances of FSEs have not been fully proved and tested, manufacturers and suppliers are requested to submit Reports for Equipment Qualification Evaluation in accordance with 10 CFR 50.49, IEEE 323. They need at least 1-2 years’ tests for Environment Qualification (EQ) and Seismic Qualification (SQ). This study is focused how to prepare the BOP purchase specifications in order to control the FSEs, especially in safety class equipment. With the optimization plan for BOP packages of this study, the FSEs’ occurrence can be reasonably controlled as low as possible. For successful NPP project, the concerns in procuring BOPs shall be fully analyzed beforehand. Now Korea is preparing new era of APR+, with closing the time of APR1400. The technical specification of APR+ BOPs can be developed and prepared successfully and very effectively according to this optimization plan. This will be a great contribution not only in constructing APR+ in time, but also in exporting APR+ overseas, all over the world in the future.
Muratore-Ginanneschi, Paolo
2005-05-01
Investment strategies in multiplicative Markovian market models with transaction costs are defined using growth optimal criteria. The optimal strategy is shown to consist in holding the amount of capital invested in stocks within an interval around an ideal optimal investment. The size of the holding interval is determined by the intensity of the transaction costs and the time horizon. The inclusion of financial derivatives in the models is also considered. All the results presented in this contributions were previously derived in collaboration with E. Aurell.
Energy Technology Data Exchange (ETDEWEB)
Aha, Ulrich
2013-07-01
Maintenance strategies are aimed to keep a technical facility functioning in spite of damaging processes (wear, corrosion, fatigue) with simultaneous control of these processes. The project optimization of maintenance strategies in case of data uncertainties is aimed to optimize maintenance measures like preventive measures (lubrication etc.), inspections and replacements to keep the facility/plant operating including the minimization of financial costs. The report covers the following topics: modeling assumptions, model development and optimization procedure, results for a conventional power plant and an oxyfuel plant.
Multi-step optimization strategy for fuel-optimal orbital transfer of low-thrust spacecraft
Rasotto, M.; Armellin, R.; Di Lizia, P.
2016-03-01
An effective method for the design of fuel-optimal transfers in two- and three-body dynamics is presented. The optimal control problem is formulated using calculus of variation and primer vector theory. This leads to a multi-point boundary value problem (MPBVP), characterized by complex inner constraints and a discontinuous thrust profile. The first issue is addressed by embedding the MPBVP in a parametric optimization problem, thus allowing a simplification of the set of transversality constraints. The second problem is solved by representing the discontinuous control function by a smooth function depending on a continuation parameter. The resulting trajectory optimization method can deal with different intermediate conditions, and no a priori knowledge of the control structure is required. Test cases in both the two- and three-body dynamics show the capability of the method in solving complex trajectory design problems.
Directory of Open Access Journals (Sweden)
Qijia Yao
2017-07-01
Full Text Available The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated, and a hybrid optimization strategy based on Gauss pseudospectral method (GPM and direct shooting method (DSM is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions. The results indicate that the method is effective with good robustness. Keywords: Motion planning, Multibody spacecraft, Optimal control, Gauss pseudospectral method, Direct shooting method
Hamidi, Ahd; Kreeftenberg, Hans; V D Pol, Leo; Ghimire, Saroj; V D Wielen, Luuk A M; Ottens, Marcel
2016-05-01
Vaccination is one of the most successful public health interventions being a cost-effective tool in preventing deaths among young children. The earliest vaccines were developed following empirical methods, creating vaccines by trial and error. New process development tools, for example mathematical modeling, as well as new regulatory initiatives requiring better understanding of both the product and the process are being applied to well-characterized biopharmaceuticals (for example recombinant proteins). The vaccine industry is still running behind in comparison to these industries. A production process for a new Haemophilus influenzae type b (Hib) conjugate vaccine, including related quality control (QC) tests, was developed and transferred to a number of emerging vaccine manufacturers. This contributed to a sustainable global supply of affordable Hib conjugate vaccines, as illustrated by the market launch of the first Hib vaccine based on this technology in 2007 and concomitant price reduction of Hib vaccines. This paper describes the development approach followed for this Hib conjugate vaccine as well as the mathematical modeling tool applied recently in order to indicate options for further improvements of the initial Hib process. The strategy followed during the process development of this Hib conjugate vaccine was a targeted and integrated approach based on prior knowledge and experience with similar products using multi-disciplinary expertise. Mathematical modeling was used to develop a predictive model for the initial Hib process (the 'baseline' model) as well as an 'optimized' model, by proposing a number of process changes which could lead to further reduction in price. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:568-580, 2016. © 2016 American Institute of Chemical Engineers.
Dispositional optimism and coping strategies in patients with a kidney transplant.
Costa-Requena, Gemma; Cantarell-Aixendri, M Carmen; Parramon-Puig, Gemma; Serón-Micas, Daniel
2014-01-01
Dispositional optimism is a personal resource that determines the coping style and adaptive response to chronic diseases. The aim of this study was to assess the correlations between dispositional optimism and coping strategies in patients with recent kidney transplantation and evaluate the differences in the use of coping strategies in accordance with the level of dispositional optimism. Patients who were hospitalised in the nephrology department were selected consecutively after kidney transplantation was performed. The evaluation instruments were the Life Orientation Test-Revised, and the Coping Strategies Inventory. The data were analysed with central tendency measures, correlation analyses and means were compared using Student’s t-test. 66 patients with a kidney transplant participated in the study. The coping styles that characterised patients with a recent kidney transplantation were Social withdrawal and Problem avoidance. Correlations between dispositional optimism and coping strategies were significant in a positive direction in Problem-solving (p<.05) and Cognitive restructuring (p<.01), and inversely with Self-criticism (p<.05). Differences in dispositional optimism created significant differences in the Self-Criticism dimension (t=2.58; p<.01). Dispositional optimism scores provide differences in coping responses after kidney transplantation. Moreover, coping strategies may influence the patient’s perception of emotional wellbeing after kidney transplantation.
Tank waste remediation system optimized processing strategy with an altered treatment scheme
International Nuclear Information System (INIS)
Slaathaug, E.J.
1996-03-01
This report provides an alternative strategy evolved from the current Hanford Site Tank Waste Remediation System (TWRS) programmatic baseline for accomplishing the treatment and disposal of the Hanford Site tank wastes. This optimized processing strategy with an altered treatment scheme performs the major elements of the TWRS Program, but modifies the deployment of selected treatment technologies to reduce the program cost. The present program for development of waste retrieval, pretreatment, and vitrification technologies continues, but the optimized processing strategy reuses a single facility to accomplish the separations/low-activity waste (LAW) vitrification and the high-level waste (HLW) vitrification processes sequentially, thereby eliminating the need for a separate HLW vitrification facility
Optimization of remediation strategies using vadose zone monitoring systems
Dahan, Ofer
2016-04-01
In-situ bio-remediation of the vadose zone depends mainly on the ability to change the subsurface hydrological, physical and chemical conditions in order to enable development of specific, indigenous, pollutants degrading bacteria. As such the remediation efficiency is much dependent on the ability to implement optimal hydraulic and chemical conditions in deep sections of the vadose zone. These conditions are usually determined in laboratory experiments where parameters such as the chemical composition of the soil water solution, redox potential and water content of the sediment are fully controlled. Usually, implementation of desired optimal degradation conditions in deep vadose zone at full scale field setups is achieved through infiltration of water enriched with chemical additives on the land surface. It is assumed that deep percolation into the vadose zone would create chemical conditions that promote biodegradation of specific compounds. However, application of water with specific chemical conditions near land surface dose not necessarily results in promoting of desired chemical and hydraulic conditions in deep sections of the vadose zone. A vadose-zone monitoring system (VMS) that was recently developed allows continuous monitoring of the hydrological and chemical properties of deep sections of the unsaturated zone. The VMS includes flexible time-domain reflectometry (FTDR) probes which allow continuous monitoring of the temporal variation of the vadose zone water content, and vadose-zone sampling ports (VSPs) which are designed to allow frequent sampling of the sediment pore-water and gas at multiple depths. Implementation of the vadose zone monitoring system in sites that undergoes active remediation provides real time information on the actual chemical and hydrological conditions in the vadose zone as the remediation process progresses. Up-to-date the system has been successfully implemented in several studies on water flow and contaminant transport in
Optimizing noise control strategy in a forging workshop.
Razavi, Hamideh; Ramazanifar, Ehsan; Bagherzadeh, Jalal
2014-01-01
In this paper, a computer program based on a genetic algorithm is developed to find an economic solution for noise control in a forging workshop. Initially, input data, including characteristics of sound sources, human exposure, abatement techniques, and production plans are inserted into the model. Using sound pressure levels at working locations, the operators who are at higher risk are identified and picked out for the next step. The program is devised in MATLAB such that the parameters can be easily defined and changed for comparison. The final results are structured into 4 sections that specify an appropriate abatement method for each operator and machine, minimum allowance time for high-risk operators, required damping material for enclosures, and minimum total cost of these treatments. The validity of input data in addition to proper settings in the optimization model ensures the final solution is practical and economically reasonable.
Optimization of wind farm power production using innovative control strategies
DEFF Research Database (Denmark)
Duc, Thomas
Wind energy has experienced a very significant growth and cost reduction over the past decade, and is now able to compete with conventional power generation sources. New concepts are currently investigated to decrease costs of production of electricity even further. Wind farm coordinated control...... deficit caused by the wake downstream, or yawing the turbine to deflect the wake away from the downwind turbine. Simulation results found in the literature indicate that an increase in overall power production can be obtained. However they underline the high sensitivity of these gains to incoming wind...... aligned wind turbines. The experimental results show that the scenarios implemented during the first measurement campaign did not achieve an increase in overall power production, which confirms the difficulty to realize wind farm power optimization in real operating conditions. In the curtailment field...
Optimal dispatch strategy for the agile virtual power plant
DEFF Research Database (Denmark)
Petersen, Mette Højgaard; Bendtsen, Jan Dimon; Stoustrup, Jakob
2012-01-01
The introduction of large ratios of renewable energy into the existing power system is complicated by the inherent variability of production technologies, which harvest energy from wind, sun and waves. Fluctuations of renewable power production can be predicted to some extent, but the assumption...... of perfect prediction is unrealistic. This paper therefore introduces the Agile Virtual Power Plant. The Agile Virtual Power Plant assumes that the base load production planning based on best available knowledge is already given, so imbalances cannot be predicted. Consequently the Agile Virtual Power Plant...... attempts to preserve maneuverability (stay agile) rather than optimize performance according to predictions. In this paper the imbalance compensation problem for an Agile Virtual Power Plant is formulated. It is proved formally, that when local units are power and energy constrained integrators a dispatch...
Experimental transport phenomena and optimization strategies for thermoelectrics
Energy Technology Data Exchange (ETDEWEB)
Ehrlich, A C; Gillespie, D J
1997-07-01
When a new and promising thermoelectric material is discovered, an effort is undertaken to improve its figure of merit. If the effort is to be more efficient than one of trial and error with perhaps some rule of thumb guidance then it is important to be able to make the connection between experimental data and the underlying material characteristics, electronic and phononic, that influence the figure of merit. Transport and fermiology experimental data can be used to evaluate these material characteristics and thus establish trends as a function of some controllable parameter, such as composition. In this paper some of the generic-materials characteristics, generally believed to be required for a high figure of merit, will be discussed in terms of the experimental approach to their evaluation and optimization. Transport and fermiology experiments will be emphasized and both will be outlined in what they can reveal and what can be obscured by the simplifying assumptions generally used in their interpretation.
Optimal Sizing and Control Strategy Design for Heavy Hybrid Electric Truck
Directory of Open Access Journals (Sweden)
Yuan Zou
2012-01-01
Full Text Available Due to the complexity of the hybrid powertrain, the control is highly involved to improve the collaborations of the different components. For the specific powertrain, the components' sizing just gives the possibility to propel the vehicle and the control will realize the function of the propulsion. Definitely the components' sizing also gives the constraints to the control design, which cause a close coupling between the sizing and control strategy design. This paper presents a parametric study focused on sizing of the powertrain components and optimization of the power split between the engine and electric motor for minimizing the fuel consumption. A framework is put forward to accomplish the optimal sizing and control design for a heavy parallel pre-AMT hybrid truck under the natural driving schedule. The iterative plant-controller combined optimization methodology is adopted to optimize the key parameters of the plant and control strategy simultaneously. A scalable powertrain model based on a bilevel optimization framework is built. Dynamic programming is applied to find the optimal control in the inner loop with a prescribed cycle. The parameters are optimized in the outer loop. The results are analysed and the optimal sizing and control strategy are achieved simultaneously.
Footprints of Optimal Protein Assembly Strategies in the Operonic Structure of Prokaryotes
Directory of Open Access Journals (Sweden)
Jan Ewald
2015-04-01
Full Text Available In this work, we investigate optimality principles behind synthesis strategies for protein complexes using a dynamic optimization approach. We show that the cellular capacity of protein synthesis has a strong influence on optimal synthesis strategies reaching from a simultaneous to a sequential synthesis of the subunits of a protein complex. Sequential synthesis is preferred if protein synthesis is strongly limited, whereas a simultaneous synthesis is optimal in situations with a high protein synthesis capacity. We confirm the predictions of our optimization approach through the analysis of the operonic organization of protein complexes in several hundred prokaryotes. Thereby, we are able to show that cellular protein synthesis capacity is a driving force in the dissolution of operons comprising the subunits of a protein complex. Thus, we also provide a tested hypothesis explaining why the subunits of many prokaryotic protein complexes are distributed across several operons despite the presumably less precise co-regulation.
Optimizing Lidar Scanning Strategies for Wind Energy Measurements (Invited)
Newman, J. F.; Bonin, T. A.; Klein, P.; Wharton, S.; Chilson, P. B.
2013-12-01
Environmental concerns and rising fossil fuel prices have prompted rapid development in the renewable energy sector. Wind energy, in particular, has become increasingly popular in the United States. However, the intermittency of available wind energy makes it difficult to integrate wind energy into the power grid. Thus, the expansion and successful implementation of wind energy requires accurate wind resource assessments and wind power forecasts. The actual power produced by a turbine is affected by the wind speeds and turbulence levels experienced across the turbine rotor disk. Because of the range of measurement heights required for wind power estimation, remote sensing devices (e.g., lidar) are ideally suited for these purposes. However, the volume averaging inherent in remote sensing technology produces turbulence estimates that are different from those estimated by a sonic anemometer mounted on a standard meteorological tower. In addition, most lidars intended for wind energy purposes utilize a standard Doppler beam-swinging or Velocity-Azimuth Display technique to estimate the three-dimensional wind vector. These scanning strategies are ideal for measuring mean wind speeds but are likely inadequate for measuring turbulence. In order to examine the impact of different lidar scanning strategies on turbulence measurements, a WindCube lidar, a scanning Halo lidar, and a scanning Galion lidar were deployed at the Southern Great Plains Atmospheric Radiation Measurement (ARM) site in Summer 2013. Existing instrumentation at the ARM site, including a 60-m meteorological tower and an additional scanning Halo lidar, were used in conjunction with the deployed lidars to evaluate several user-defined scanning strategies. For part of the experiment, all three scanning lidars were pointed at approximately the same point in space and a tri-Doppler analysis was completed to calculate the three-dimensional wind vector every 1 second. In another part of the experiment, one of
Directory of Open Access Journals (Sweden)
Rafał Dreżewski
2018-05-01
Full Text Available In this paper, the evolutionary algorithm for the optimization of Forex market trading strategies is proposed. The introduction to issues related to the financial markets and the evolutionary algorithms precedes the main part of the paper, in which the proposed trading system is presented. The system uses the evolutionary algorithm for optimization of a parameterized greedy strategy, which is then used as an investment strategy on the Forex market. In the proposed system, a model of the Forex market was developed, including all elements that are necessary for simulating realistic trading processes. The proposed evolutionary algorithm contains several novel mechanisms that were introduced to optimize the greedy strategy. The most important of the proposed techniques are the mechanisms for maintaining the population diversity, a mechanism for protecting the best individuals in the population, the mechanisms preventing the excessive growth of the population, the mechanisms of the initialization of the population after moving the time window and a mechanism of choosing the best strategies used for trading. The experiments, conducted with the use of real-world Forex market data, were aimed at testing the quality of the results obtained using the proposed algorithm and comparing them with the results obtained by the buy-and-hold strategy. By comparing our results with the results of the buy-and-hold strategy, we attempted to verify the validity of the efficient market hypothesis. The credibility of the hypothesis would have more general implications for many different areas of our lives, including future sustainable development policies.
Asymptotic Normality of the Optimal Solution in Multiresponse Surface Mathematical Programming
Díaz-García, José A.; Caro-Lopera, Francisco J.
2015-01-01
An explicit form for the perturbation effect on the matrix of regression coeffi- cients on the optimal solution in multiresponse surface methodology is obtained in this paper. Then, the sensitivity analysis of the optimal solution is studied and the critical point characterisation of the convex program, associated with the optimum of a multiresponse surface, is also analysed. Finally, the asymptotic normality of the optimal solution is derived by the standard methods.
Cho, Moon-Heum; Heron, Michele L.
2015-01-01
Enrollment in online remedial mathematics courses has increased in popularity in institutions of higher learning; however, students unskilled in self-regulated learning (SRL) find online remedial mathematics courses particularly challenging. We investigated the role of SRL, specifically motivation, emotion, and learning strategies, in students'…
House, J. Daniel
2005-01-01
Recent mathematics assessments have indicated that students in several Asian countries have tended to score above international averages. Research findings indicate that there are cultural differences in expectations for student achievement in mathematics and in classroom practices and instructional strategies. The importance of the motivational…
Directory of Open Access Journals (Sweden)
Asa Kuntifatin Warda
2017-11-01
Full Text Available Type of this study is quantitative. The purpose of this study was to determine the effectiveness of SSCS learning model with KNWS strategy towards mathematical creative thinking ability and self confidence of students. The populations of this study was students at grade VIII SMP Muhammadiyah 8 Semarang academic year 2016/2017. The sampling was done by cluster random sampling technique, which were chosen VIIIA as experiment class and VIIIC as control class. Data collection methods used documentation, a test, a questionnaire, and an observation. The result of this study stated that the mathematical creative thinking ability of the experiment class students had reached the classical completeness, percentage of mastery learning on mathematical creative thinking ability of the experiment class students was better than that percentage of the control class students, average of test result on mathematical creative thinking ability of the experiment class students was better than that average of the control class students, average of self confidence score of the experiment class students was better than that average of the control class students, teacher ability and the learning activities at the experiment class students included in good category, response of the experiment class students to joint the learning is positive.
Optimal combined purchasing strategies for a risk-averse manufacturer under price uncertainty
Directory of Open Access Journals (Sweden)
Qiao Wu
2015-09-01
Full Text Available Purpose: The purpose of our paper is to analyze optimal purchasing strategies when a manufacturer can buy raw materials from a long-term contract supplier and a spot market under spot price uncertainty. Design/methodology/approach: This procurement model can be solved by using dynamic programming. First, we maximize the DM’s utility of the second period, obtaining the optimal contract quantity and spot quantity for the second period. Then, maximize the DM’s utility of both periods, obtaining the optimal purchasing strategy for the first period. We use a numerical method to compare the performance level of a pure spot sourcing strategy with that of a mixed strategy. Findings: Our results show that optimal purchasing strategies vary with the trend of contract prices. If the contract price falls, the total quantity purchased in period 1 will decrease in the degree of risk aversion. If the contract price increases, the total quantity purchased in period 1 will increase in the degree of risk aversion. The relationship between the optimal contract quantity and the degree of risk aversion depends on whether the expected spot price or the contract price is larger in period 2. Finally, we compare the performance levels between a combined strategy and a spot sourcing strategy. It shows that a combined strategy is optimal for a risk-averse buyer. Originality/value: It’s challenging to deal with a two-period procurement problem with risk consideration. We have obtained results of a two-period procurement problem with two sourcing options, namely contract procurement and spot purchases. Our model incorporates the buyer’s risk aversion factor and the change of contract prices, which are not addressed in early studies.
Optimal swimming strategies in mate searching pelagic copepods
DEFF Research Database (Denmark)
Kiørboe, Thomas
2008-01-01
Male copepods must swim to find females, but swimming increases the risk of meeting predators and is expensive in terms of energy expenditure. Here I address the trade-offs between gains and risks and the question of how much and how fast to swim using simple models that optimise the number...... of lifetime mate encounters. Radically different swimming strategies are predicted for different feeding behaviours, and these predictions are tested experimentally using representative species. In general, male swimming speeds and the difference in swimming speeds between the genders are predicted...... and observed to increase with increasing conflict between mate searching and feeding. It is high in ambush feeders, where searching (swimming) and feeding are mutually exclusive and low in species, where the matured males do not feed at all. Ambush feeding males alternate between stationary ambush feeding...
Approximate representation of optimal strategies from influence diagrams
DEFF Research Database (Denmark)
Jensen, Finn V.
2008-01-01
, and where the policy functions for the decisions have so large do- mains that they cannot be represented directly in a strategy tree. The approach is to have separate ID representations for each decision variable. In each representation the actual information is fully exploited, however the representation...... of policies for future decisions are approximations. We call the approximation information abstraction. It consists in introducing a dummy structure connecting the past with the decision. We study how to specify, implement and learn information abstraction.......There are three phases in the life of a decision problem, specification, solution, and rep- resentation of solution. The specification and solution phases are off-line, while the rep- resention of solution often shall serve an on-line situation with rather tough constraints on time and space. One...
Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang
2016-01-01
For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.
Combining two strategies to optimize biometric decisions against spoofing attacks
Li, Weifeng; Poh, Norman; Zhou, Yicong
2014-09-01
Spoof attack by replicating biometric traits represents a real threat to an automatic biometric verification/ authentication system. This is because the system, originally designed to distinguish between genuine users from impostors, simply cannot distinguish between a replicated biometric sample (replica) from a live sample. An effective solution is to obtain some measures that can indicate whether or not a biometric trait has been tempered with, e.g., liveness detection measures. These measures are referred to as evidence of spoofing or anti-spoofing measures. In order to make the final accept/rejection decision, a straightforward solution to define two thresholds: one for the anti-spoofing measure, and another for the verification score. We compared two variants of a method that relies on applying two thresholds - one to the verification (matching) score and another to the anti-spoofing measure. Our experiments carried out using a signature database as well as by simulation show that both the brute-force and its probabilistic variant turn out to be optimal under different operating conditions.
Energy Optimization Using a Case-Based Reasoning Strategy.
González-Briones, Alfonso; Prieto, Javier; De La Prieta, Fernando; Herrera-Viedma, Enrique; Corchado, Juan M
2018-03-15
At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
An optimal strategy for functional mapping of dynamic trait loci.
Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling
2010-02-01
As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.
Advanced Variance Reduction Strategies for Optimizing Mesh Tallies in MAVRIC
International Nuclear Information System (INIS)
Peplow, Douglas E.; Blakeman, Edward D; Wagner, John C
2007-01-01
More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficiently optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS)
Optimal investment strategies in decentralized renewable power generation under uncertainty
International Nuclear Information System (INIS)
Fleten, S.-E.; Maribu, K.M.; Wangensteen, I.
2007-01-01
This paper presents a method for evaluating investments in decentralized renewable power generation under price un certainty. The analysis is applicable for a client with an electricity load and a renewable resource that can be utilized for power generation. The investor has a deferrable opportunity to invest in one local power generating unit, with the objective to maximize the profits from the opportunity. Renewable electricity generation can serve local load when generation and load coincide in time, and surplus power can be exported to the grid. The problem is to find the price intervals and the capacity of the generator at which to invest. Results from a case with wind power generation for an office building suggests it is optimal to wait for higher prices than the net present value break-even price under price uncertainty, and that capacity choice can depend on the current market price and the price volatility. With low price volatility there can be more than one investment price interval for different units with intermediate waiting regions between them. High price volatility increases the value of the investment opportunity, and therefore makes it more attractive to postpone investment until larger units are profitable. (author)
Energy Optimization Using a Case-Based Reasoning Strategy
Directory of Open Access Journals (Sweden)
Alfonso González-Briones
2018-03-01
Full Text Available At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS deployed in a Cloud environment with a wireless sensor network (WSN in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN. The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
Energy Optimization Using a Case-Based Reasoning Strategy
Herrera-Viedma, Enrique
2018-01-01
At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices. PMID:29543729
Directory of Open Access Journals (Sweden)
Craig George Leslie Hopf
2015-12-01
Full Text Available This paper’s primary alternative hypothesis is Ha: profitable exchange-traded horserace betting fund with deterministic payoff exists for acceptable institutional portfolio return—risk. The primary hypothesis challenges the semi-strong efficient market hypothesis applied to horse race wagering. An optimal deterministic betting model (DBM is derived from the existing stochastic model fundamentals, mathematical pooling principles, and new theorem. The exchange-traded betting fund (ETBF is derived from force of interest first principles. An ETBF driven by DBM processes conjointly defines the research’s betting strategy. Alpha is excess return above financial benchmark, and invokes betting strategy alpha that is composed of model alpha and fund alpha. The results and analysis from statistical testing of a global stratified data sample of three hundred galloper horse races accepted at the ninety-five percent confidence-level positive betting strategy alpha, to endorse an exchange-traded horse race betting fund with deterministic payoff into financial market.
Directory of Open Access Journals (Sweden)
Yulia G. Krasnozhon
2018-03-01
Full Text Available Modern information technologies have an increasing importance for development dynamics and management structure of an enterprise. The management efficiency of implementation of modern information technologies directly related to the quality of information security incident management. However, issues of assessment of the impact of information security incidents management on quality and efficiency of the enterprise management system are not sufficiently highlighted neither in Russian nor in foreign literature. The main direction to approach these problems is the optimization of the process automation system of the information security incident management. Today a special attention is paid to IT-technologies while dealing with information security incidents at mission-critical facilities in Russian Federation such as the Federal Tax Service of Russia (FTS. It is proposed to use the mathematical apparatus of queueing theory in order to build a mathematical model of the system optimization. The developed model allows to estimate quality of the management taking into account the rules and restrictions imposed on the system by the effects of information security incidents. Here an example is given in order to demonstrate the system in work. The obtained statistical data are shown. An implementation of the system discussed here will improve the quality of the Russian FTS services and make responses to information security incidents faster.
A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.
Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei
2017-09-21
In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.
Hızır, Ahmet Esat; Hizir, Ahmet Esat
2006-01-01
Sustainability is an emerging issue as a direct consequence of the population increase in the world. Urban transport systems play a crucial role in maintaining sustainability. Recently, sustainable urban transportation has become a major research area. Most of these studies propose evaluation methods that use simulation tools to assess the sustainability of different transportation policies. Despite all studies, there seems to be lack of mathematical programming models to determine the optima...
Optimal bidding strategies for competitive generators and large consumers
International Nuclear Information System (INIS)
Fushuan Wen; David, A.K.
2001-01-01
There exists the potential for gaming such as strategic bidding by participants (power suppliers and large consumers) in a deregulated power market, which is more an oligopoly than a laissez-faire market. Each participant can increase his or her own profit through strategic bidding but this has a negative effect on maximising social welfare. A method to build bidding strategies for both power suppliers and large consumers in a poolco-type electricity market is presented in this paper. It is assumed that each supplier/large consumer bids a linear supply/demand function, and the system is dispatched to maximise social welfare. Each supplier/large consumer chooses the coefficients in the linear supply/demand function to maximise benefits, subject to expectations about how rival participants will bid. The problem is formulated as a stochastic optimisation problem, and solved by a Monte Carlo approach. A numerical example with six suppliers and two large consumers serves to illustrate the essential features of the method. (author)
Communication strategies to optimize commitments and investments in iron programming.
Griffiths, Marcia
2002-04-01
There is consensus that a communications component is crucial to the success of iron supplementation and fortification programs. However, in many instances, we have not applied what we know about successful advocacy and program communications to iron programs. Communication must play a larger and more central role in iron programs to overcome several common shortcomings and allow the use of new commitments and investments in iron programming to optimum advantage. One shortcoming is that iron program communication has been driven primarily by the supply side of the supply-demand continuum. That is, technical information has been given without thought for what people want to know or do. To overcome this, the communication component, which should be responsive to the consumer perspective, must be considered at program inception, not enlisted late in the program cycle as a remedy when interventions fail to reach their targets. Another shortcoming is the lack of program focus on behavior. Because the "technology" of iron, a supplement, or fortified or specific local food must be combined with appropriate consumer behavior, it is not enough to promote the technology. The appropriate use of technology must be ensured, and this requires precise and strategically crafted communications. A small number of projects from countries as diverse as Indonesia, Egypt, Nicaragua and Peru offer examples of successful communications efforts and strategies for adaptation by other countries.
An Equivalent Emission Minimization Strategy for Causal Optimal Control of Diesel Engines
Directory of Open Access Journals (Sweden)
Stephan Zentner
2014-02-01
Full Text Available One of the main challenges during the development of operating strategies for modern diesel engines is the reduction of the CO2 emissions, while complying with ever more stringent limits for the pollutant emissions. The inherent trade-off between the emissions of CO2 and pollutants renders a simultaneous reduction difficult. Therefore, an optimal operating strategy is sought that yields minimal CO2 emissions, while holding the cumulative pollutant emissions at the allowed level. Such an operating strategy can be obtained offline by solving a constrained optimal control problem. However, the final-value constraint on the cumulated pollutant emissions prevents this approach from being adopted for causal control. This paper proposes a framework for causal optimal control of diesel engines. The optimization problem can be solved online when the constrained minimization of the CO2 emissions is reformulated as an unconstrained minimization of the CO2 emissions and the weighted pollutant emissions (i.e., equivalent emissions. However, the weighting factors are not known a priori. A method for the online calculation of these weighting factors is proposed. It is based on the Hamilton–Jacobi–Bellman (HJB equation and a physically motivated approximation of the optimal cost-to-go. A case study shows that the causal control strategy defined by the online calculation of the equivalence factor and the minimization of the equivalent emissions is only slightly inferior to the non-causal offline optimization, while being applicable to online control.
Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong
2017-06-01
In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.
A Particle Swarm Optimization Variant with an Inner Variable Learning Strategy
Directory of Open Access Journals (Sweden)
Guohua Wu
2014-01-01
Full Text Available Although Particle Swarm Optimization (PSO has demonstrated competitive performance in solving global optimization problems, it exhibits some limitations when dealing with optimization problems with high dimensionality and complex landscape. In this paper, we integrate some problem-oriented knowledge into the design of a certain PSO variant. The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL is particularly efficient for optimizing functions with symmetric variables. Symmetric variables of the optimized function have to satisfy a certain quantitative relation. Based on this knowledge, the inner variable learning (IVL strategy helps the particle to inspect the relation among its inner variables, determine the exemplar variable for all other variables, and then make each variable learn from the exemplar variable in terms of their quantitative relations. In addition, we design a new trap detection and jumping out strategy to help particles escape from local optima. The trap detection operation is employed at the level of individual particles whereas the trap jumping out strategy is adaptive in its nature. Experimental simulations completed for some representative optimization functions demonstrate the excellent performance of PSO-IVL. The effectiveness of the PSO-IVL stresses a usefulness of augmenting evolutionary algorithms by problem-oriented domain knowledge.
Strategies to Optimize Adult Stem Cell Therapy for Tissue Regeneration
Directory of Open Access Journals (Sweden)
Shan Liu
2016-06-01
Full Text Available Stem cell therapy aims to replace damaged or aged cells with healthy functioning cells in congenital defects, tissue injuries, autoimmune disorders, and neurogenic degenerative diseases. Among various types of stem cells, adult stem cells (i.e., tissue-specific stem cells commit to becoming the functional cells from their tissue of origin. These cells are the most commonly used in cell-based therapy since they do not confer risk of teratomas, do not require fetal stem cell maneuvers and thus are free of ethical concerns, and they confer low immunogenicity (even if allogenous. The goal of this review is to summarize the current state of the art and advances in using stem cell therapy for tissue repair in solid organs. Here we address key factors in cell preparation, such as the source of adult stem cells, optimal cell types for implantation (universal mesenchymal stem cells vs. tissue-specific stem cells, or induced vs. non-induced stem cells, early or late passages of stem cells, stem cells with endogenous or exogenous growth factors, preconditioning of stem cells (hypoxia, growth factors, or conditioned medium, using various controlled release systems to deliver growth factors with hydrogels or microspheres to provide apposite interactions of stem cells and their niche. We also review several approaches of cell delivery that affect the outcomes of cell therapy, including the appropriate routes of cell administration (systemic, intravenous, or intraperitoneal vs. local administration, timing for cell therapy (immediate vs. a few days after injury, single injection of a large number of cells vs. multiple smaller injections, a single site for injection vs. multiple sites and use of rodents vs. larger animal models. Future directions of stem cell-based therapies are also discussed to guide potential clinical applications.
A review of strategies to address the shortage of science and mathematics educators in grades 10-12
Magano, Florence Lesedi
For an education system to function effectively it is important that its planning functions are executed effectively and efficiently. Among others this implies that the system must know what the teacher supply and demand is and how it will change in time. If the teacher supply and demand is known it could result in sound intervention strategies being developed and implemented. Education planners will be able to plan for the number of bursaries to be awarded and in which subject fields; it will be known how many foreign teachers to employ and for which subjects. This is the basic rationale that underpins this study. This study explored the problem of teacher demand and supply in the Further Education and Training (FET) phase (Grades 10 to 12) in South Africa and offers a critical analysis of strategies adopted by Provincial Education Departments in an endeavour to diminish the demand for teachers, specifically for Mathematics and Science, in rural and poor schools. Initially the study involved a secondary data analysis to extrapolate the demand and supply of teachers in Mathematics and Science over the next ten years. The first key finding of the study was that the data needed for such an analysis does not exist in any reliable form that would facilitate the development of such a projection. What the study had to rely on was anecdotal evidence that suggests that a shortage of Mathematics and Science teachers does exist and that posts are often filled by unqualified and under-qualified staff. In the second phase of the research in which the study explored the effectiveness of strategies developed to address the shortage of Mathematics and Science teachers, a qualitative research approach was adopted within a descriptive interpretive design. The views and opinions of human resource managers responsible for post provisioning in schools were explored through in-depth interviews to understand the types of strategy adopted by the provinces, their potential to alleviate
Bogoljubova, M. N.; Afonasov, A. I.; Kozlov, B. N.; Shavdurov, D. E.
2018-05-01
A predictive simulation technique of optimal cutting modes in the turning of workpieces made of nickel-based heat-resistant alloys, different from the well-known ones, is proposed. The impact of various factors on the cutting process with the purpose of determining optimal parameters of machining in concordance with certain effectiveness criteria is analyzed in the paper. A mathematical model of optimization, algorithms and computer programmes, visual graphical forms reflecting dependences of the effectiveness criteria – productivity, net cost, and tool life on parameters of the technological process - have been worked out. A nonlinear model for multidimensional functions, “solution of the equation with multiple unknowns”, “a coordinate descent method” and heuristic algorithms are accepted to solve the problem of optimization of cutting mode parameters. Research shows that in machining of workpieces made from heat-resistant alloy AISI N07263, the highest possible productivity will be achieved with the following parameters: cutting speed v = 22.1 m/min., feed rate s=0.26 mm/rev; tool life T = 18 min.; net cost – 2.45 per hour.
Development of a codon optimization strategy using the efor RED reporter gene as a test case
Yip, Chee-Hoo; Yarkoni, Orr; Ajioka, James; Wan, Kiew-Lian; Nathan, Sheila
2018-04-01
Synthetic biology is a platform that enables high-level synthesis of useful products such as pharmaceutically related drugs, bioplastics and green fuels from synthetic DNA constructs. Large-scale expression of these products can be achieved in an industrial compliant host such as Escherichia coli. To maximise the production of recombinant proteins in a heterologous host, the genes of interest are usually codon optimized based on the codon usage of the host. However, the bioinformatics freeware available for standard codon optimization might not be ideal in determining the best sequence for the synthesis of synthetic DNA. Synthesis of incorrect sequences can prove to be a costly error and to avoid this, a codon optimization strategy was developed based on the E. coli codon usage using the efor RED reporter gene as a test case. This strategy replaces codons encoding for serine, leucine, proline and threonine with the most frequently used codons in E. coli. Furthermore, codons encoding for valine and glycine are substituted with the second highly used codons in E. coli. Both the optimized and original efor RED genes were ligated to the pJS209 plasmid backbone using Gibson Assembly and the recombinant DNAs were transformed into E. coli E. cloni 10G strain. The fluorescence intensity per cell density of the optimized sequence was improved by 20% compared to the original sequence. Hence, the developed codon optimization strategy is proposed when designing an optimal sequence for heterologous protein production in E. coli.
A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles
Directory of Open Access Journals (Sweden)
Chaoying Xia
2017-07-01
Full Text Available This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs. The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA. The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin’s minimum principle (PMP-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions.
An optimal staggered harvesting strategy for herbaceous biomass energy crops
Energy Technology Data Exchange (ETDEWEB)
Bhat, M.G.; English, B.C. [Univ. of Tennessee, Knoxville, TN (United States)
1993-12-31
Biofuel research over the past two decades indicates lignocellulosic crops are a reliable source of feedstock for alternative energy. However, under the current technology of producing, harvesting and converting biomass crops, the cost of biofuel is not competitive with conventional biofuel. Cost of harvesting biomass feedstock is a single largest component of feedstock cost so there is a cost advantage in designing a biomass harvesting system. Traditional farmer-initiated harvesting operation causes over investment. This study develops a least-cost, time-distributed (staggered) harvesting system for example switch grass, that calls for an effective coordination between farmers, processing plant and a single third-party custom harvester. A linear programming model explicitly accounts for the trade-off between yield loss and benefit of reduced machinery overhead cost, associated with the staggered harvesting system. Total cost of producing and harvesting switch grass will decline by 17.94 percent from conventional non-staggered to proposed staggered harvesting strategy. Harvesting machinery cost alone experiences a significant reduction of 39.68 percent from moving from former to latter. The net return to farmers is estimated to increase by 160.40 percent. Per tonne and per hectare costs of feedstock production will decline by 17.94 percent and 24.78 percent, respectively. These results clearly lend support to the view that the traditional system of single period harvesting calls for over investment on agricultural machinery which escalates the feedstock cost. This social loss to the society in the form of escalated harvesting cost can be avoided if there is a proper coordination among farmers, processing plant and custom harvesters as to when and how biomass crop needs to be planted and harvested. Such an institutional arrangement benefits producers, processing plant and, in turn, end users of biofuels.
Mathematical modeling of an urban pigeon population subject to local management strategies.
Haidar, I; Alvarez, I; Prévot, A C
2017-06-01
This paper addresses the issue of managing urban pigeon population using some possible actions that make it reach a density target with respect to socio-ecological constraints. A mathematical model describing the dynamic of this population is introduced. This model incorporates the effect of some regulatory actions on the dynamic of this population. We use mathematical viability theory, which provides a framework to study compatibility between dynamics and state constraints. The viability study shows when and how it is possible to regulate the pigeon population with respect to the constraints. Copyright © 2017 Elsevier Inc. All rights reserved.
The mathematics behind biological invasions
Lewis, Mark A; Potts, Jonathan R
2016-01-01
This book investigates the mathematical analysis of biological invasions. Unlike purely qualitative treatments of ecology, it draws on mathematical theory and methods, equipping the reader with sharp tools and rigorous methodology. Subjects include invasion dynamics, species interactions, population spread, long-distance dispersal, stochastic effects, risk analysis, and optimal responses to invaders. While based on the theory of dynamical systems, including partial differential equations and integrodifference equations, the book also draws on information theory, machine learning, Monte Carlo methods, optimal control, statistics, and stochastic processes. Applications to real biological invasions are included throughout. Ultimately, the book imparts a powerful principle: that by bringing ecology and mathematics together, researchers can uncover new understanding of, and effective response strategies to, biological invasions. It is suitable for graduate students and established researchers in mathematical ecolo...
An Optimal Operating Strategy for Battery Life Cycle Costs in Electric Vehicles
Directory of Open Access Journals (Sweden)
Yinghua Han
2014-01-01
Full Text Available Impact on petroleum based vehicles on the environment, cost, and availability of fuel has led to an increased interest in electric vehicle as a means of transportation. Battery is a major component in an electric vehicle. Economic viability of these vehicles depends on the availability of cost-effective batteries. This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization for battery. Assume that the deterioration of the battery is stochastic. Under the assumptions, the proposed operating strategy for battery is formulated as a nonlinear optimization problem considering reliability and failure number. And an explicit expression of the average cost rate is derived for battery lifetime. Results show that the proposed operating strategy enhances the availability and reliability at a low cost.
Integrated Optimization of Bus Line Fare and Operational Strategies Using Elastic Demand
Directory of Open Access Journals (Sweden)
Chunyan Tang
2017-01-01
Full Text Available An optimization approach for designing a transit service system is proposed. Its objective would be the maximization of total social welfare, by providing a profitable fare structure and tailoring operational strategies to passenger demand. These operational strategies include full route operation (FRO, limited stop, short turn, and a mix of the latter two strategies. The demand function is formulated to reflect the attributes of these strategies, in-vehicle crowding, and fare effects on demand variation. The fare is either a flat fare or a differential fare structure; the latter is based on trip distance and achieved service levels. This proposed methodology is applied to a case study of Dalian, China. The optimal results indicate that an optimal combination of operational strategies integrated with a differential fare structure results in the highest potential for increasing total social welfare, if the value of parameter ε related to additional service fee is low. When this value increases up to more than a threshold, strategies with a flat fare show greater benefits. If this value increases beyond yet another threshold, the use of skipped stop strategies is not recommended.
Design of Underwater Robot Lines Based on a Hybrid Automatic Optimization Strategy
Institute of Scientific and Technical Information of China (English)
Wenjing Lyu; Weilin Luo
2014-01-01
In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body’s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.
An Optimal Investment Strategy and Multiperiod Deposit Insurance Pricing Model for Commercial Banks
Directory of Open Access Journals (Sweden)
Grant E. Muller
2018-01-01
Full Text Available We employ the method of stochastic optimal control to derive the optimal investment strategy for maximizing an expected exponential utility of a commercial bank’s capital at some future date T>0. In addition, we derive a multiperiod deposit insurance (DI pricing model that incorporates the explicit solution of the optimal control problem and an asset value reset rule comparable to the typical practice of insolvency resolution by insuring agencies. By way of numerical simulations, we study the effects of changes in the DI coverage horizon, the risk associated with the asset portfolio of the bank, and the bank’s initial leverage level (deposit-to-asset ratio on the DI premium while the optimal investment strategy is followed.
Strategy Feedback in an E-learning Tool for Mathematical Exercises
Jeuring, J.T.; Pasman, W.
2007-01-01
Exercises in mathematics are often solved using a standard procedure, such as for example solving a system of linear equations by subtracting equations from top to bottom, and then substituting variables from bottom to top. Students have to practice such procedural skills: they have to learn how
Althauser, Krista L.
2018-01-01
Using a Mixed Methods approach, this study investigated changes in levels of self-efficacy among elementary preservice teachers following a semester course on teaching elementary students' mathematics. Participants in this study included 347 preservice elementary teachers at a mid-size regional university who had just completed an elementary…
Multi-objective optimal strategy for generating and bidding in the power market
International Nuclear Information System (INIS)
Peng Chunhua; Sun Huijuan; Guo Jianfeng; Liu Gang
2012-01-01
Highlights: ► A new benefit/risk/emission comprehensive generation optimization model is established. ► A hybrid multi-objective differential evolution optimization algorithm is designed. ► Fuzzy set theory and entropy weighting method are employed to extract the general best solution. ► The proposed approach of generating and bidding is efficient for maximizing profit and minimizing both risk and emissions. - Abstract: Based on the coordinated interaction between units output and electricity market prices, the benefit/risk/emission comprehensive generation optimization model with objectives of maximal profit and minimal bidding risk and emissions is established. A hybrid multi-objective differential evolution optimization algorithm, which successfully integrates Pareto non-dominated sorting with differential evolution algorithm and improves individual crowding distance mechanism and mutation strategy to avoid premature and unevenly search, is designed to achieve Pareto optimal set of this model. Moreover, fuzzy set theory and entropy weighting method are employed to extract one of the Pareto optimal solutions as the general best solution. Several optimization runs have been carried out on different cases of generation bidding and scheduling. The results confirm the potential and effectiveness of the proposed approach in solving the multi-objective optimization problem of generation bidding and scheduling. In addition, the comparison with the classical optimization algorithms demonstrates the superiorities of the proposed algorithm such as integrality of Pareto front, well-distributed Pareto-optimal solutions, high search speed.
Directory of Open Access Journals (Sweden)
Davood Mahmoodzadeh
2016-05-01
Full Text Available Groundwater in coastal areas is an essential source of freshwater that warrants protection from seawater intrusion as a priority based on an optimal management plan. Proper optimal management strategies can be developed using a variety of decision-making models. The present study aims to investigate the impacts of environmental changes on groundwater resources. For this purpose, a combined simulation-optimization model is employed that incorporates the SUTRA numerical model and the evolutionaty method of ant colony optimization. The fresh groundwater lens in Kish Island is used as a case study and different scenarios are considered for the likely enviromental changes. Results indicate that while variations in recharge rate form an important factor in the fresh groundwater lens, land-surface inundation due to rises in seawater level, especially in low-lying lands, is the major factor affecting the lens. Furthermore, impacts of environmental changes when effected into the Kish Island aquifer optimization management plan have led to a reduction of more than 20% in the allowable water extraction, indicating the high sensitivity of groundwater resources management plans in small islands to such variations.
International Nuclear Information System (INIS)
Jian, Linni; Zhu, Xinyu; Shao, Ziyun; Niu, Shuangxia; Chan, C.C.
2014-01-01
Highlights: • A scenario of vehicle-to-grid implementation within regional smart grid is discussed and mathematically formulated. • A double-layer optimal charging strategy for plug-in electric vehicles is proposed. • The proposed double-layer optimal charging algorithm aims to minimize power grid’s load variance. • The performance of proposed double-layer optimal charging algorithm is evaluated through comparative study. - Abstract: As an emerging new electrical load, plug-in electric vehicles (PEVs)’ impact on the power grid has drawn increasing attention worldwide. An optimal scenario is that by digging the potential of PEVs as a moveable energy storage device, they may not harm the power grid by, for example, triggering extreme surges in demand at rush hours, conversely, the large-scale penetration of PEVs could benefit the grid through flattening the power load curve, hence, increase the stability, security and operating economy of the grid. This has become a hot issue which is known as vehicle-to-grid (V2G) technology within the framework of smart grid. In this paper, a scenario of V2G implementation within regional smart grids is discussed. Then, the problem is mathematically formulated. It is essentially an optimization problem, and the objective is to minimize the overall load variance. With the increase of the scale of PEVs and charging posts involved, the computational complexity will become tremendously high. Therefore, a double-layer optimal charging (DLOC) strategy is proposed to solve this problem. The comparative study demonstrates that the proposed DLOC algorithm can effectively solve the problem of tremendously high computational complexity arising from the large-scaled PEVs and charging posts involved
Directory of Open Access Journals (Sweden)
Mun-Kyeom Kim
2017-09-01
Full Text Available This study introduces a frequency regulation strategy to enable the participation of wind turbines with permanent magnet synchronous generators (PMSGs. The optimal strategy focuses on developing the frequency support capability of PMSGs connected to the power system. Active power control is performed using maximum power point tracking (MPPT and de-loaded control to supply the required power reserve following a disturbance. A kinetic energy (KE reserve control is developed to enhance the frequency regulation capability of wind turbines. The coordination with the de-loaded control prevents instability in the PMSG wind system due to excessive KE discharge. A KE optimization method that maximizes the sum of the KE reserves at wind farms is also adopted to determine the de-loaded power reference for each PMSG wind turbine using the particle swarm optimization (PSO algorithm. To validate the effectiveness of the proposed optimal control and operation strategy, three different case studies are conducted using the PSCAD/EMTDC simulation tool. The results demonstrate that the optimal strategy enhances the frequency support contribution from PMSG wind turbines.
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2010-01-01
markets in some ways, is chosen as the studied power system in this paper. Two kinds of BESS, based on polysulfide-bromine (PSB) and vanadium redox (VRB) battery technologies, are studies in the paper. Simulation results show, that the proposed optimal operation strategy is an effective measure to achieve......Since the hourly spot market price is available one day ahead, the price could be transferred to the consumers and they may have some motivations to install an energy storage system in order to save their energy costs. This paper presents an optimal operation strategy for a battery energy storage...
Energy evaluation of optimal control strategies for central VWV chiller systems
International Nuclear Information System (INIS)
Jin Xinqiao; Du Zhimin; Xiao Xiaokun
2007-01-01
Under various conditions, the actual load of the heating, ventilation and air conditioning (HVAC) systems is less than it is originally designed in most operation periods. To save energy and to optimize the controls for chilling systems, the performance of variable water volume (VWV) systems and characteristics of control systems are analyzed, and three strategies are presented and tested based on simulation in this paper. Energy evaluation for the three strategies shows that they can save energy to some extent, and there is potential remained. To minimize the energy consumption of chilling system, the setpoints of controls of supply chilled water temperature and supply head of secondary pump should be optimized simultaneously
Distributed Strategy for Optimal Dispatch of Unbalanced Three-Phase Islanded Microgrids
DEFF Research Database (Denmark)
Vergara Barrios, Pedro Pablo; Rey-López, Juan Manuel; Shaker, Hamid Reza
2018-01-01
This paper presents a distributed strategy for the optimal dispatch of islanded microgrids, modeled as unbalanced three-phase electrical distribution systems (EDS). To set the dispatch of the distributed generation (DG) units, an optimal generation problem is stated and solved distributively based......-phase microgrid. According to the obtained results, the proposed strategy achieves a lower cost solution when compared with a centralized approach based on a static droop framework, with a considerable reduction on the communication system complexity. Additionally, it corrects the mismatch between generation...
Convexity of Ruin Probability and Optimal Dividend Strategies for a General Lévy Process
Directory of Open Access Journals (Sweden)
Chuancun Yin
2015-01-01
Full Text Available We consider the optimal dividends problem for a company whose cash reserves follow a general Lévy process with certain positive jumps and arbitrary negative jumps. The objective is to find a policy which maximizes the expected discounted dividends until the time of ruin. Under appropriate conditions, we use some recent results in the theory of potential analysis of subordinators to obtain the convexity properties of probability of ruin. We present conditions under which the optimal dividend strategy, among all admissible ones, takes the form of a barrier strategy.
Convexity of Ruin Probability and Optimal Dividend Strategies for a General Lévy Process
Yuen, Kam Chuen; Shen, Ying
2015-01-01
We consider the optimal dividends problem for a company whose cash reserves follow a general Lévy process with certain positive jumps and arbitrary negative jumps. The objective is to find a policy which maximizes the expected discounted dividends until the time of ruin. Under appropriate conditions, we use some recent results in the theory of potential analysis of subordinators to obtain the convexity properties of probability of ruin. We present conditions under which the optimal dividend strategy, among all admissible ones, takes the form of a barrier strategy. PMID:26351655
Evolution strategies and multi-objective optimization of permanent magnet motor
DEFF Research Database (Denmark)
Andersen, Søren Bøgh; Santos, Ilmar
2012-01-01
When designing a permanent magnet motor, several geometry and material parameters are to be defined. This is not an easy task, as material properties and magnetic fields are highly non-linear and the design of a motor is therefore often an iterative process. From an engineering point of view, we...... of evolution strategies, ES to effectively design and optimize parameters of permanent magnet motors. Single as well as multi-objective optimization procedures are carried out. A modified way of creating the strategy parameters for the ES algorithm is also proposed and has together with the standard ES...
Directory of Open Access Journals (Sweden)
Li MingChu
2017-01-01
Full Text Available The terrorist’s coordinated attack is becoming an increasing threat to western countries. By monitoring potential terrorists, security agencies are able to detect and destroy terrorist plots at their planning stage. Therefore, an optimal monitoring strategy for the domestic security agency becomes necessary. However, previous study about monitoring strategy generation fails to consider the information leakage, due to hackers and insider threat. Such leakage events may lead to failure of watching potential terrorists and destroying the plot, and cause a huge risk to public security. This paper makes two major contributions. Firstly, we develop a new Stackelberg game model for the security agency to generate optimal monitoring strategy with the consideration of information leakage. Secondly, we provide a double-oracle framework DO-TPDIL for calculation effectively. The experimental result shows that our approach can obtain robust strategies against information leakage with high feasibility and efficiency.
The Development and Empirical Validation of an E-based Supply Chain Strategy Optimization Model
DEFF Research Database (Denmark)
Kotzab, Herbert; Skjoldager, Niels; Vinum, Thorkil
2003-01-01
Examines the formulation of supply chain strategies in complex environments. Argues that current state‐of‐the‐art e‐business and supply chain management, combined into the concept of e‐SCM, as well as the use of transaction cost theory, network theory and resource‐based theory, altogether can...... be used to form a model for analyzing supply chains with the purpose of reducing the uncertainty of formulating supply chain strategies. Presents e‐supply chain strategy optimization model (e‐SOM) as a way to analyze supply chains in a structured manner as regards strategic preferences for supply chain...... design, relations and resources in the chains with the ultimate purpose of enabling the formulation of optimal, executable strategies for specific supply chains. Uses research results for a specific supply chain to validate the usefulness of the model....
International Nuclear Information System (INIS)
Kim, Heungseob; Kim, Pansoo
2017-01-01
To maximize the reliability of a system, the traditional reliability–redundancy allocation problem (RRAP) determines the component reliability and level of redundancy for each subsystem. This paper proposes an advanced RRAP that also considers the optimal redundancy strategy, either active or cold standby. In addition, new examples are presented for it. Furthermore, the exact reliability function for a cold standby redundant subsystem with an imperfect detector/switch is suggested, and is expected to replace the previous approximating model that has been used in most related studies. A parallel genetic algorithm for solving the RRAP as a mixed-integer nonlinear programming model is presented, and its performance is compared with those of previous studies by using numerical examples on three benchmark problems. - Highlights: • Optimal strategy is proposed to solve reliability redundancy allocation problem. • The redundancy strategy uses parallel genetic algorithm. • Improved reliability function for a cold standby subsystem is suggested. • Proposed redundancy strategy enhances the system reliability.
The topography of the environment alters the optimal search strategy for active particles
Volpe, Giorgio; Volpe, Giovanni
2017-10-01
In environments with scarce resources, adopting the right search strategy can make the difference between succeeding and failing, even between life and death. At different scales, this applies to molecular encounters in the cell cytoplasm, to animals looking for food or mates in natural landscapes, to rescuers during search and rescue operations in disaster zones, and to genetic computer algorithms exploring parameter spaces. When looking for sparse targets in a homogeneous environment, a combination of ballistic and diffusive steps is considered optimal; in particular, more ballistic Lévy flights with exponent α≤1 are generally believed to optimize the search process. However, most search spaces present complex topographies. What is the best search strategy in these more realistic scenarios? Here, we show that the topography of the environment significantly alters the optimal search strategy toward less ballistic and more Brownian strategies. We consider an active particle performing a blind cruise search for nonregenerating sparse targets in a 2D space with steps drawn from a Lévy distribution with the exponent varying from α=1 to α=2 (Brownian). We show that, when boundaries, barriers, and obstacles are present, the optimal search strategy depends on the topography of the environment, with α assuming intermediate values in the whole range under consideration. We interpret these findings using simple scaling arguments and discuss their robustness to varying searcher's size. Our results are relevant for search problems at different length scales from animal and human foraging to microswimmers' taxis to biochemical rates of reaction.
Directory of Open Access Journals (Sweden)
Santanu Biswas
Full Text Available Visceral leishmaniasis (VL is a deadly neglected tropical disease that poses a serious problem in various countries all over the world. Implementation of various intervention strategies fail in controlling the spread of this disease due to issues of parasite drug resistance and resistance of sandfly vectors to insecticide sprays. Due to this, policy makers need to develop novel strategies or resort to a combination of multiple intervention strategies to control the spread of the disease. To address this issue, we propose an extensive SIR-type model for anthroponotic visceral leishmaniasis transmission with seasonal fluctuations modeled in the form of periodic sandfly biting rate. Fitting the model for real data reported in South Sudan, we estimate the model parameters and compare the model predictions with known VL cases. Using optimal control theory, we study the effects of popular control strategies namely, drug-based treatment of symptomatic and PKDL-infected individuals, insecticide treated bednets and spray of insecticides on the dynamics of infected human and vector populations. We propose that the strategies remain ineffective in curbing the disease individually, as opposed to the use of optimal combinations of the mentioned strategies. Testing the model for different optimal combinations while considering periodic seasonal fluctuations, we find that the optimal combination of treatment of individuals and insecticide sprays perform well in controlling the disease for the time period of intervention introduced. Performing a cost-effective analysis we identify that the same strategy also proves to be efficacious and cost-effective. Finally, we suggest that our model would be helpful for policy makers to predict the best intervention strategies for specific time periods and their appropriate implementation for elimination of visceral leishmaniasis.
Li MingChu; Yang Zekun; Lu Kun; Guo Cheng
2017-01-01
The terrorist’s coordinated attack is becoming an increasing threat to western countries. By monitoring potential terrorists, security agencies are able to detect and destroy terrorist plots at their planning stage. Therefore, an optimal monitoring strategy for the domestic security agency becomes necessary. However, previous study about monitoring strategy generation fails to consider the information leakage, due to hackers and insider threat. Such leakage events may lead to failure of watch...
International Nuclear Information System (INIS)
Porteus, E.
1982-01-01
The study of infinite-horizon nonstationary dynamic programs using the operator approach is continued. The point of view here differs slightly from that taken by others, in that Denardo's local income function is not used as a starting point. Infinite-horizon values are defined as limits of finite-horizon values, as the horizons get long. Two important conditions of an earlier paper are weakened, yet the optimality equations, the optimality criterion, and the existence of optimal ''structured'' strategies are still obtained
Risk-Averse Suppliers’ Optimal Pricing Strategies in a Two-Stage Supply Chain
Directory of Open Access Journals (Sweden)
Rui Shen
2013-01-01
Full Text Available Risk-averse suppliers’ optimal pricing strategies in two-stage supply chains under competitive environment are discussed. The suppliers in this paper focus more on losses as compared to profits, and they care their long-term relationship with their customers. We introduce for the suppliers a loss function, which covers both current loss and future loss. The optimal wholesale price is solved under situations of risk neutral, risk averse, and a combination of minimizing loss and controlling risk, respectively. Besides, some properties of and relations among these optimal wholesale prices are given as well. A numerical example is given to illustrate the performance of the proposed method.
Optimization of cooling strategy and seeding by FBRM analysis of batch crystallization
Zhang, Dejiang; Liu, Lande; Xu, Shijie; Du, Shichao; Dong, Weibing; Gong, Junbo
2018-03-01
A method is presented for optimizing the cooling strategy and seed loading simultaneously. Focused beam reflectance measurement (FBRM) was used to determine the approximating optimal cooling profile. Using these results in conjunction with constant growth rate assumption, modified Mullin-Nyvlt trajectory could be calculated. This trajectory could suppress secondary nucleation and has the potential to control product's polymorph distribution. Comparing with linear and two step cooling, modified Mullin-Nyvlt trajectory have a larger size distribution and a better morphology. Based on the calculating results, the optimized seed loading policy was also developed. This policy could be useful for guiding the batch crystallization process.
Optimized bolt tightening strategies for gasketed flanged pipe joints of different sizes
International Nuclear Information System (INIS)
Abid, Muhammad; Khan, Ayesha; Nash, David Hugh; Hussain, Masroor; Wajid, Hafiz Abdul
2016-01-01
Achieving a proper preload in the bolts of a gasketed bolted flanged pipe joint during joint assembly is considered important for its optimized performance. This paper presents results of detailed non-linear finite element analysis of an optimized bolt tightening strategy of different joint sizes for achieving proper preload close to the target stress values. Industrial guidelines are considered for applying recommended target stress values with TCM (torque control method) and SCM (stretch control method) using a customized optimization algorithm. Different joint components performance is observed and discussed in detail.
Volpato, Enilze de Souza Nogueira; Betini, Marluci; Puga, Maria Eduarda; Agarwal, Arnav; Cataneo, Antônio José Maria; Oliveira, Luciane Dias de; Bazan, Rodrigo; Braz, Leandro Gobbo; Pereira, José Eduardo Guimarães; El Dib, Regina
2018-01-15
A high-quality electronic search is essential for ensuring accuracy and comprehensiveness among the records retrieved when conducting systematic reviews. Therefore, we aimed to identify the most efficient method for searching in both MEDLINE (through PubMed) and EMBASE, covering search terms with variant spellings, direct and indirect orders, and associations with MeSH and EMTREE terms (or lack thereof). Experimental study. UNESP, Brazil. We selected and analyzed 37 search strategies that had specifically been developed for the field of anesthesiology. These search strategies were adapted in order to cover all potentially relevant search terms, with regard to variant spellings and direct and indirect orders, in the most efficient manner. When the strategies included variant spellings and direct and indirect orders, these adapted versions of the search strategies selected retrieved the same number of search results in MEDLINE (mean of 61.3%) and a higher number in EMBASE (mean of 63.9%) in the sample analyzed. The numbers of results retrieved through the searches analyzed here were not identical with and without associated use of MeSH and EMTREE terms. However, association of these terms from both controlled vocabularies retrieved a larger number of records than did the use of either one of them. In view of these results, we recommend that the search terms used should include both preferred and non-preferred terms (i.e. variant spellings and direct/indirect order of the same term) and associated MeSH and EMTREE terms, in order to develop highly-sensitive search strategies for systematic reviews.
Social Optimization and Pricing Policy in Cognitive Radio Networks with an Energy Saving Strategy
Directory of Open Access Journals (Sweden)
Shunfu Jin
2016-01-01
Full Text Available The rapid growth of wireless application results in an increase in demand for spectrum resource and communication energy. In this paper, we firstly introduce a novel energy saving strategy in cognitive radio networks (CRNs and then propose an appropriate pricing policy for secondary user (SU packets. We analyze the behavior of data packets in a discrete-time single-server priority queue under multiple-vacation discipline. With the help of a Quasi-Birth-Death (QBD process model, we obtain the joint distribution for the number of SU packets and the state of base station (BS via the Matrix-Geometric Solution method. We assess the average latency of SU packets and the energy saving ratio of system. According to a natural reward-cost structure, we study the individually optimal behavior and the socially optimal behavior of the energy saving strategy and use an optimization algorithm based on standard particle swarm optimization (SPSO method to search the socially optimal arrival rate of SU packets. By comparing the individually optimal behavior and the socially optimal behavior, we impose an appropriate admission fee to SU packets. Finally, we present numerical results to show the impacts of system parameters on the system performance and the pricing policy.
Optimal robust control strategy of a solid oxide fuel cell system
Wu, Xiaojuan; Gao, Danhui
2018-01-01
Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.
Two-objective on-line optimization of supervisory control strategy
Energy Technology Data Exchange (ETDEWEB)
Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal (Canada)
2004-09-01
The set points of supervisory control strategy are optimized with respect to energy use and thermal comfort for existing HVAC systems. The set point values of zone temperatures, supply duct static pressure, and supply air temperature are the problem variables, while energy use and thermal comfort are the objective functions. The HVAC system model includes all the individual component models developed and validated against the monitored data of an existing VAV system. It serves to calculate energy use during the optimization process, whereas the actual energy use is determined by using monitoring data and the appropriate validated component models. A comparison, done for one summer week, of actual and optimal energy use shows that the on-line implementation of a genetic algorithm optimization program to determine the optimal set points of supervisory control strategy could save energy by 19.5%, while satisfying the minimum zone airflow rates and the thermal comfort. The results also indicate that the application of the two-objective optimization problem can help control daily energy use or daily building thermal comfort, thus saving more energy than the application of the one-objective optimization problem. (Author)
2012-03-01
"With skip-stop rail transit operation, transit agencies can reduce their operating costs and fleet size, : and passengers can experience reduced in-transit travel times without extra track and technological : improvement. However, since skip-stop op...
Directory of Open Access Journals (Sweden)
Lee Vernon J
2009-12-01
Full Text Available Abstract Background Individual strategies in pandemic preparedness plans may not reduce the impact of an influenza pandemic. Methods We searched modeling publications through PubMed and associated references from 1990 to 30 September 2009. Inclusion criteria were modeling papers quantifying the effectiveness of combination strategies, both pharmaceutical and non-pharmaceutical. Results Nineteen modeling papers on combination strategies were selected. Four studies examined combination strategies on a global scale, 14 on single countries, and one on a small community. Stochastic individual-based modeling was used in nine studies, stochastic meta-population modeling in five, and deterministic compartmental modeling in another five. As part of combination strategies, vaccination was explored in eight studies, antiviral prophylaxis and/or treatment in 16, area or household quarantine in eight, case isolation in six, social distancing measures in 10 and air travel restriction in six studies. Two studies suggested a high probability of successful influenza epicenter containment with combination strategies under favorable conditions. During a pandemic, combination strategies delayed spread, reduced overall number of cases, and delayed and reduced peak attack rate more than individual strategies. Combination strategies remained effective at high reproductive numbers compared with single strategy. Global cooperative strategies, including redistribution of antiviral drugs, were effective in reducing the global impact and attack rates of pandemic influenza. Conclusion Combination strategies increase the effectiveness of individual strategies. They include pharmaceutical (antiviral agents, antibiotics and vaccines and non-pharmaceutical interventions (case isolation, quarantine, personal hygiene measures, social distancing and travel restriction. Local epidemiological and modeling studies are needed to validate efficacy and feasibility.
Directory of Open Access Journals (Sweden)
Pei-Yu Chen
2013-01-01
Full Text Available With more and more mobile device users, an increasingly important and critical issue is how to efficiently evaluate mobile network survivability. In this paper, a novel metric called Average Degree of Disconnectivity (Average DOD is proposed, in which the concept of probability is calculated by the contest success function. The DOD metric is used to evaluate the damage degree of the network, where the larger the value of the Average DOD, the more the damage degree of the network. A multiround network attack-defense scenario as a mathematical model is used to support network operators to predict all the strategies both cyber attacker and network defender would likely take. In addition, the Average DOD would be used to evaluate the damage degree of the network. In each round, the attacker could use the attack resources to launch attacks on the nodes of the target network. Meanwhile, the network defender could reallocate its existing resources to recover compromised nodes and allocate defense resources to protect the survival nodes of the network. In the approach to solving this problem, the “gradient method” and “game theory” are adopted to find the optimal resource allocation strategies for both the cyber attacker and mobile network defender.
1993-01-01
This Strategic Plan was developed by the Federal Coordinating Council for Science, Engineering, and Technology (FCCSET) through its Committee on Education and Human Resources (CEHR), with representatives from 16 Federal agencies. Based on two years of coordinated interagency effort, the Plan confirms the Federal Government's commitment to ensuring the health and well-being of science, mathematics, engineering, and technology education at all levels and in all sectors (i.e., elementary and secondary, undergraduate, graduate, public understanding of science, and technology education). The Plan represents the Federal Government's efforts to develop a five-year planning framework and associated milestones that focus Federal planning and the resources of the participating agencies toward achieving the requisite or expected level of mathematics and science competence by all students. The priority framework outlines the strategic objectives, implementation priorities, and components for the Strategic Plan and serves as a road map for the Plan. The Plan endorses a broad range of ongoing activities, including continued Federal support for graduate education as the backbone of our country's research and development enterprise. The Plan also identifies three tiers of program activities with goals that address issues in science, mathematics, engineering, and technology education meriting special attention. Within each tier, individual agency programs play important and often unique roles that strengthen the aggregate portfolio. The three tiers are presented in descending order of priority: (1) reforming the formal education system; (2) expanding participation and access; and (3) enabling activities.
De Lara, Michel
2006-05-01
In their 1990 paper Optimal reproductive efforts and the timing of reproduction of annual plants in randomly varying environments, Amir and Cohen considered stochastic environments consisting of i.i.d. sequences in an optimal allocation discrete-time model. We suppose here that the sequence of environmental factors is more generally described by a Markov chain. Moreover, we discuss the connection between the time interval of the discrete-time dynamic model and the ability of the plant to rebuild completely its vegetative body (from reserves). We formulate a stochastic optimization problem covering the so-called linear and logarithmic fitness (corresponding to variation within and between years), which yields optimal strategies. For "linear maximizers'', we analyse how optimal strategies depend upon the environmental variability type: constant, random stationary, random i.i.d., random monotonous. We provide general patterns in terms of targets and thresholds, including both determinate and indeterminate growth. We also provide a partial result on the comparison between ;"linear maximizers'' and "log maximizers''. Numerical simulations are provided, allowing to give a hint at the effect of different mathematical assumptions.
Directory of Open Access Journals (Sweden)
N. V. R. Naidu
2011-09-01
Full Text Available This paper deals with a critical evaluation of the Preventive Maintenance system in steel industry. This study helps in implementing Six Sigma solutions to reduce the down time of two critical machines i.e., Electric Arc Furnace (EAF and Billet Casting Machine (BCM. It is clear from the analysis of EAF and BCM respectively that, variations in output are quite possible because the machines output not only depend on maintenance time but also on several other variables. Further, the objective is to design a preventive maintenance programme on the same equipment situated in the plant using Six Sigma. The breakdown of these equipments could very well affect the production rate. For this, the mathematical models have been developed and these models are used to obtain the optimum preventive maintenance frequency for minimizing the down time and maximizing the profits.