Bilevel programming problems theory, algorithms and applications to energy networks
Dempe, Stephan; Pérez-Valdés, Gerardo A; Kalashnykova, Nataliya; Kalashnikova, Nataliya
2015-01-01
This book describes recent theoretical findings relevant to bilevel programming in general, and in mixed-integer bilevel programming in particular. It describes recent applications in energy problems, such as the stochastic bilevel optimization approaches used in the natural gas industry. New algorithms for solving linear and mixed-integer bilevel programming problems are presented and explained.
Generalized Nash equilibrium problems, bilevel programming and mpec
Lalitha, CS
2017-01-01
The book discusses three classes of problems: the generalized Nash equilibrium problems, the bilevel problems and the mathematical programming with equilibrium constraints (MPEC). These problems interact through their mathematical analysis as well as their applications. The primary aim of the book is to present the modern tool of variational analysis and optimization, which are used to analyze these three classes of problems. All contributing authors are respected academicians, scientists and researchers from around the globe. These contributions are based on the lectures delivered by experts at CIMPA School, held at the University of Delhi, India, from 25 November–6 December 2013, and peer-reviewed by international experts. The book contains five chapters. Chapter 1 deals with nonsmooth, nonconvex bilevel optimization problems whose feasible set is described by using the graph of the solution set mapping of a parametric optimization problem. Chapter 2 describes a constraint qualification to MPECs considere...
Domí nguez, Luis F.; Pistikopoulos, Efstratios N.
2010-01-01
continuous multiparametric programming algorithm is then used to solve the reformulated convex inner problem. The second algorithm addresses the mixed-integer case of the bilevel programming problem where integer and continuous variables of the outer problem
A recurrent neural network for solving bilevel linear programming problem.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian
2014-04-01
In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.
Neural network for solving convex quadratic bilevel programming problems.
He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie
2014-03-01
In this paper, using the idea of successive approximation, we propose a neural network to solve convex quadratic bilevel programming problems (CQBPPs), which is modeled by a nonautonomous differential inclusion. Different from the existing neural network for CQBPP, the model has the least number of state variables and simple structure. Based on the theory of nonsmooth analysis, differential inclusions and Lyapunov-like method, the limit equilibrium points sequence of the proposed neural networks can approximately converge to an optimal solution of CQBPP under certain conditions. Finally, simulation results on two numerical examples and the portfolio selection problem show the effectiveness and performance of the proposed neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.
A novel approach based on preference-based index for interval bilevel linear programming problem
Aihong Ren; Yuping Wang; Xingsi Xue
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrain...
Domínguez, Luis F.
2010-12-01
This work introduces two algorithms for the solution of pure integer and mixed-integer bilevel programming problems by multiparametric programming techniques. The first algorithm addresses the integer case of the bilevel programming problem where integer variables of the outer optimization problem appear in linear or polynomial form in the inner problem. The algorithm employs global optimization techniques to convexify nonlinear terms generated by a reformulation linearization technique (RLT). A continuous multiparametric programming algorithm is then used to solve the reformulated convex inner problem. The second algorithm addresses the mixed-integer case of the bilevel programming problem where integer and continuous variables of the outer problem appear in linear or polynomial forms in the inner problem. The algorithm relies on the use of global multiparametric mixed-integer programming techniques at the inner optimization level. In both algorithms, the multiparametric solutions obtained are embedded in the outer problem to form a set of single-level (M)(I)(N)LP problems - which are then solved to global optimality using standard fixed-point (global) optimization methods. Numerical examples drawn from the open literature are presented to illustrate the proposed algorithms. © 2010 Elsevier Ltd.
A novel approach based on preference-based index for interval bilevel linear programming problem.
Ren, Aihong; Wang, Yuping; Xue, Xingsi
2017-01-01
This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation [Formula: see text]. Furthermore, the concept of a preference δ -optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
A novel approach based on preference-based index for interval bilevel linear programming problem
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Aihong Ren
2017-05-01
Full Text Available Abstract This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrained programming. With the consideration of different preferences of different decision makers, the concept of the preference level that the interval objective function is preferred to a target interval is defined based on the preference-based index. Then a preference-based deterministic bilevel programming problem is constructed in terms of the preference level and the order relation ⪯ m w $\\preceq_{mw}$ . Furthermore, the concept of a preference δ-optimal solution is given. Subsequently, the constructed deterministic nonlinear bilevel problem is solved with the help of estimation of distribution algorithm. Finally, several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
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Animesh Biswas
2016-04-01
Full Text Available This paper deals with fuzzy goal programming approach to solve fuzzy linear bilevel integer programming problems with fuzzy probabilistic constraints following Pareto distribution and Frechet distribution. In the proposed approach a new chance constrained programming methodology is developed from the view point of managing those probabilistic constraints in a hybrid fuzzy environment. A method of defuzzification of fuzzy numbers using ?-cut has been adopted to reduce the problem into a linear bilevel integer programming problem. The individual optimal value of the objective of each DM is found in isolation to construct the fuzzy membership goals. Finally, fuzzy goal programming approach is used to achieve maximum degree of each of the membership goals by minimizing under deviational variables in the decision making environment. To demonstrate the efficiency of the proposed approach, a numerical example is provided.
An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem
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Tao Zhang
2012-01-01
Full Text Available An improved particle swarm optimization (PSO algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP. For such problems, the proposed algorithm directly simulates the decision process of bilevel programming, which is different from most traditional algorithms designed for specific versions or based on specific assumptions. The BLMPP is transformed to solve multiobjective optimization problems in the upper level and the lower level interactively by an improved PSO. And a set of approximate Pareto optimal solutions for BLMPP is obtained using the elite strategy. This interactive procedure is repeated until the accurate Pareto optimal solutions of the original problem are found. Finally, some numerical examples are given to illustrate the feasibility of the proposed algorithm.
Aihong Ren
2016-01-01
This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solut...
Stability of multi-objective bi-level linear programming problems under fuzziness
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Abo-Sinna Mahmoud A.
2013-01-01
Full Text Available This paper deals with multi-objective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multi-objective bi-level linear programming problems. An algorithm for obtaining any subset of the parametric space, which has the same corresponding Pareto optimal solution, is presented. Also, this paper established the model for the supply-demand interaction in the age of electronic commerce (EC. First of all, the study uses the individual objectives of both parties as the foundation of the supply-demand interaction. Subsequently, it divides the interaction, in the age of electronic commerce, into the following two classifications: (i Market transactions, with the primary focus on the supply demand relationship in the marketplace; and (ii Information service, with the primary focus on the provider and the user of information service. By applying the bi-level programming technique of interaction process, the study will develop an analytical process to explain how supply-demand interaction achieves a compromise or why the process fails. Finally, a numerical example of information service is provided for the sake of illustration.
Chen, Zhong; Liu, June; Li, Xiong
2017-01-01
A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization problem by using scalar approach, and then the whole efficient set of the BLBOP is derived by the proposed two-stage ANN for exploring the induced set. In order to illustrate the proposed method, seven numerical examples are tested and compared with results in the classical literature. Finally, a practical problem is solved by the proposed algorithm. PMID:29312446
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Tao Zhang
2012-01-01
Full Text Available An elite quantum behaved particle swarm optimization (EQPSO algorithm is proposed, in which an elite strategy is exerted for the global best particle to prevent premature convergence of the swarm. The EQPSO algorithm is employed for solving bilevel multiobjective programming problem (BLMPP in this study, which has never been reported in other literatures. Finally, we use eight different test problems to measure and evaluate the proposed algorithm, including low dimension and high dimension BLMPPs, as well as attempt to solve the BLMPPs whose theoretical Pareto optimal front is not known. The experimental results show that the proposed algorithm is a feasible and efficient method for solving BLMPPs.
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Aihong Ren
2016-01-01
Full Text Available This paper is concerned with a class of fully fuzzy bilevel linear programming problems where all the coefficients and decision variables of both objective functions and the constraints are fuzzy numbers. A new approach based on deviation degree measures and a ranking function method is proposed to solve these problems. We first introduce concepts of the feasible region and the fuzzy optimal solution of a fully fuzzy bilevel linear programming problem. In order to obtain a fuzzy optimal solution of the problem, we apply deviation degree measures to deal with the fuzzy constraints and use a ranking function method of fuzzy numbers to rank the upper and lower level fuzzy objective functions. Then the fully fuzzy bilevel linear programming problem can be transformed into a deterministic bilevel programming problem. Considering the overall balance between improving objective function values and decreasing allowed deviation degrees, the computational procedure for finding a fuzzy optimal solution is proposed. Finally, a numerical example is provided to illustrate the proposed approach. The results indicate that the proposed approach gives a better optimal solution in comparison with the existing method.
A Bi-Level Programming Model for the Railway Express Cargo Service Network Design Problem
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Boliang Lin
2018-06-01
Full Text Available Service network design is fundamentally crucial for railway express cargo transportation. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and high expected operational incomes. Different configurations of these objectives will have different impacts on the quality of freight transportation services. In this paper, a bi-level programming model for the railway express cargo service network design problem is proposed. The upper-level model forms the optimal decisions in terms of the service characteristics, and the low-level model selects the service arcs for each commodity. The rail express cargo is strictly subject to the service commitment, the capacity restriction, flow balance constraints, and logical relationship constraints among the decisions variables. Moreover, linearization techniques are used to convert the lower-level model to a linear one so that it can be directly solved by a standard optimization solver. Finally, a real-world case study based on the Beijing–Guangzhou Railway Line is carried out to demonstrate the effectiveness and efficiency of the proposed solution approach.
Deb, Kalyanmoy; Sinha, Ankur
2010-01-01
Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.
A New Method for Solving Multiobjective Bilevel Programs
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Ying Ji
2017-01-01
Full Text Available We study a class of multiobjective bilevel programs with the weights of objectives being uncertain and assumed to belong to convex and compact set. To the best of our knowledge, there is no study about this class of problems. We use a worst-case weighted approach to solve this class of problems. Our “worst-case weighted multiobjective bilevel programs” model supposes that each player (leader or follower has a set of weights to their objectives and wishes to minimize their maximum weighted sum objective where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto optimum concept, which we call “robust-weighted Pareto optimum”; for the worst-case weighted multiobjective optimization with the weight set of each player given as a polytope, we show that a robust-weighted Pareto optimum can be obtained by solving mathematical programing with equilibrium constraints (MPEC. For an application, we illustrate the usefulness of the worst-case weighted multiobjective optimization to a supply chain risk management under demand uncertainty. By the comparison with the existing weighted approach, we show that our method is more robust and can be more efficiently applied to real-world problems.
Solving bi-level optimization problems in engineering design using kriging models
Xia, Yi; Liu, Xiaojie; Du, Gang
2018-05-01
Stackelberg game-theoretic approaches are applied extensively in engineering design to handle distributed collaboration decisions. Bi-level genetic algorithms (BLGAs) and response surfaces have been used to solve the corresponding bi-level programming models. However, the computational costs for BLGAs often increase rapidly with the complexity of lower-level programs, and optimal solution functions sometimes cannot be approximated by response surfaces. This article proposes a new method, namely the optimal solution function approximation by kriging model (OSFAKM), in which kriging models are used to approximate the optimal solution functions. A detailed example demonstrates that OSFAKM can obtain better solutions than BLGAs and response surface-based methods, and at the same time reduce the workload of computation remarkably. Five benchmark problems and a case study of the optimal design of a thin-walled pressure vessel are also presented to illustrate the feasibility and potential of the proposed method for bi-level optimization in engineering design.
An Evolutionary Approach for Bilevel Multi-objective Problems
Deb, Kalyanmoy; Sinha, Ankur
Evolutionary multi-objective optimization (EMO) algorithms have been extensively applied to find multiple near Pareto-optimal solutions over the past 15 years or so. However, EMO algorithms for solving bilevel multi-objective optimization problems have not received adequate attention yet. These problems appear in many applications in practice and involve two levels, each comprising of multiple conflicting objectives. These problems require every feasible upper-level solution to satisfy optimality of a lower-level optimization problem, thereby making them difficult to solve. In this paper, we discuss a recently proposed bilevel EMO procedure and show its working principle on a couple of test problems and on a business decision-making problem. This paper should motivate other EMO researchers to engage more into this important optimization task of practical importance.
A nonlinear bi-level programming approach for product portfolio management.
Ma, Shuang
2016-01-01
Product portfolio management (PPM) is a critical decision-making for companies across various industries in today's competitive environment. Traditional studies on PPM problem have been motivated toward engineering feasibilities and marketing which relatively pay less attention to other competitors' actions and the competitive relations, especially in mathematical optimization domain. The key challenge lies in that how to construct a mathematical optimization model to describe this Stackelberg game-based leader-follower PPM problem and the competitive relations between them. The primary work of this paper is the representation of a decision framework and the optimization model to leverage the PPM problem of leader and follower. A nonlinear, integer bi-level programming model is developed based on the decision framework. Furthermore, a bi-level nested genetic algorithm is put forward to solve this nonlinear bi-level programming model for leader-follower PPM problem. A case study of notebook computer product portfolio optimization is reported. Results and analyses reveal that the leader-follower bi-level optimization model is robust and can empower product portfolio optimization.
Chenlu Miao; Gang Du; Yi Xia; Danping Wang
2016-01-01
Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP) to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP), which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard pr...
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Azza Hassan Amer
2017-12-01
Full Text Available Geometric programming problem is a powerful tool for solving some special type nonlinear programming problems. In the last few years we have seen a very rapid development on solving multiobjective geometric programming problem. A few mathematical programming methods namely fuzzy programming, goal programming and weighting methods have been applied in the recent past to find the compromise solution. In this paper, -constraint method has been applied in bi-level multiobjective geometric programming problem to find the Pareto optimal solution at each level. The equivalent mathematical programming problems are formulated to find their corresponding value of the objective function based on the duality theorem at eash level. Here, we have developed a new algorithm for fuzzy programming technique to solve bi-level multiobjective geometric programming problems to find an optimal compromise solution. Finally the solution procedure of the fuzzy technique is illustrated by a numerical example
An application of data mining classification and bi-level programming for optimal credit allocation
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Seyed Mahdi Sadatrasou
2015-01-01
Full Text Available This paper investigates credit allocation policy making and its effect on economic development using bi-level programming. There are two challenging problems in bi-level credit allocation; at the first level government/public related institutes must allocate the credit strategically concerning sustainable development to regions and industrial sectors. At the second level, there are agent banks, which should allocate the credit tactically to individual applicants based on their own profitability and risk using their credit scoring models. There is a conflict of interest between these two stakeholders but the cooperation is inevitable. In this paper, a new bi-level programming formulation of the leader-follower game in association with sustainable development theory in the first level and data mining classifier at the second level is used to mathematically model the problem. The model is applied to a national development fund (NDF as a government related organization and one of its agent banks. A new algorithm called Bi-level Genetic fuzzy apriori Algorithm (BGFAA is introduced to solve the bilateral model. Experimental results are presented and compared with a unilateral policy making scenario by the leader. Findings show that although the objective functions of the leader are worse in the bilateral scenario but agent banks collaboration is attracted and guaranteed.
An Enhanced Memetic Algorithm for Single-Objective Bilevel Optimization Problems.
Islam, Md Monjurul; Singh, Hemant Kumar; Ray, Tapabrata; Sinha, Ankur
2017-01-01
Bilevel optimization, as the name reflects, deals with optimization at two interconnected hierarchical levels. The aim is to identify the optimum of an upper-level leader problem, subject to the optimality of a lower-level follower problem. Several problems from the domain of engineering, logistics, economics, and transportation have an inherent nested structure which requires them to be modeled as bilevel optimization problems. Increasing size and complexity of such problems has prompted active theoretical and practical interest in the design of efficient algorithms for bilevel optimization. Given the nested nature of bilevel problems, the computational effort (number of function evaluations) required to solve them is often quite high. In this article, we explore the use of a Memetic Algorithm (MA) to solve bilevel optimization problems. While MAs have been quite successful in solving single-level optimization problems, there have been relatively few studies exploring their potential for solving bilevel optimization problems. MAs essentially attempt to combine advantages of global and local search strategies to identify optimum solutions with low computational cost (function evaluations). The approach introduced in this article is a nested Bilevel Memetic Algorithm (BLMA). At both upper and lower levels, either a global or a local search method is used during different phases of the search. The performance of BLMA is presented on twenty-five standard test problems and two real-life applications. The results are compared with other established algorithms to demonstrate the efficacy of the proposed approach.
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Jiuping Xu
2012-01-01
Full Text Available The aim of this study is to deal with a minimum cost network flow problem (MCNFP in a large-scale construction project using a nonlinear multiobjective bilevel model with birandom variables. The main target of the upper level is to minimize both direct and transportation time costs. The target of the lower level is to minimize transportation costs. After an analysis of the birandom variables, an expectation multiobjective bilevel programming model with chance constraints is formulated to incorporate decision makers’ preferences. To solve the identified special conditions, an equivalent crisp model is proposed with an additional multiobjective bilevel particle swarm optimization (MOBLPSO developed to solve the model. The Shuibuya Hydropower Project is used as a real-world example to verify the proposed approach. Results and analysis are presented to highlight the performances of the MOBLPSO, which is very effective and efficient compared to a genetic algorithm and a simulated annealing algorithm.
A linear bi-level multi-objective program for optimal allocation of water resources.
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Ijaz Ahmad
Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.
Khanh, Phan Quoc; Plubtieng, Somyot; Sombut, Kamonrat
2014-01-01
The purpose of this paper is introduce several types of Levitin-Polyak well-posedness for bilevel vector equilibrium and optimization problems with equilibrium constraints. Base on criterion and characterizations for these types of Levitin-Polyak well-posedness we argue on diameters and Kuratowski’s, Hausdorff’s, or Istrǎtescus measures of noncompactness of approximate solution sets under suitable conditions, and we prove the Levitin-Polyak well-posedness for bilevel vector equilibrium and op...
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Chenlu Miao
2016-01-01
Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.
The Bilevel Design Problem for Communication Networks on Trains: Model, Algorithm, and Verification
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Yin Tian
2014-01-01
Full Text Available This paper proposes a novel method to solve the problem of train communication network design. Firstly, we put forward a general description of such problem. Then, taking advantage of the bilevel programming theory, we created the cost-reliability-delay model (CRD model that consisted of two parts: the physical topology part aimed at obtaining the networks with the maximum reliability under constrained cost, while the logical topology part focused on the communication paths yielding minimum delay based on the physical topology delivered from upper level. We also suggested a method to solve the CRD model, which combined the genetic algorithm and the Floyd-Warshall algorithm. Finally, we used a practical example to verify the accuracy and the effectiveness of the CRD model and further applied the novel method on a train with six carriages.
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Zeng, Qing; Zhang, Baohua; Fang, Jiakun
2017-01-01
as the generation capacities, while the lower-level is formulated as an optimal economic dispatch under the operational constraints given by the upper-level decision. To solve the bi-level multi-stage programming problem, a hybrid algorithm is proposed combining the modified binary particle swarm optimization (BPSO...... power systems. The system operation is optimized and embedded in the planning horizon. A bi-level multi-stage programming problem is formulated to minimize the investment cost plus the operational cost. The upper-level optimizes the expansion plan and determines the network topology as well......) and the interior point method (IPM). The BPSO is used for the upper-level sub-problem, and the IPM is adopted for the lower-level sub-problem. Numerical case studies have been carried out on the practical gas and electricity transmission network in western Denmark. Simulation results demonstrate the effectiveness...
Metaheuristics for bi-level optimization
2013-01-01
This book provides a complete background on metaheuristics to solve complex bi-level optimization problems (continuous/discrete, mono-objective/multi-objective) in a diverse range of application domains. Readers learn to solve large scale bi-level optimization problems by efficiently combining metaheuristics with complementary metaheuristics and mathematical programming approaches. Numerous real-world examples of problems demonstrate how metaheuristics are applied in such fields as networks, logistics and transportation, engineering design, finance and security.
Hawthorne, Bryant; Panchal, Jitesh H.
2014-07-01
A bilevel optimization formulation of policy design problems considering multiple objectives and incomplete preferences of the stakeholders is presented. The formulation is presented for Feed-in-Tariff (FIT) policy design for decentralized energy infrastructure. The upper-level problem is the policy designer's problem and the lower-level problem is a Nash equilibrium problem resulting from market interactions. The policy designer has two objectives: maximizing the quantity of energy generated and minimizing policy cost. The stakeholders decide on quantities while maximizing net present value and minimizing capital investment. The Nash equilibrium problem in the presence of incomplete preferences is formulated as a stochastic linear complementarity problem and solved using expected value formulation, expected residual minimization formulation, and the Monte Carlo technique. The primary contributions in this article are the mathematical formulation of the FIT policy, the extension of computational policy design problems to multiple objectives, and the consideration of incomplete preferences of stakeholders for policy design problems.
Fuzzy bilevel programming with multiple non-cooperative followers: model, algorithm and application
Ke, Hua; Huang, Hu; Ralescu, Dan A.; Wang, Lei
2016-04-01
In centralized decision problems, it is not complicated for decision-makers to make modelling technique selections under uncertainty. When a decentralized decision problem is considered, however, choosing appropriate models is no longer easy due to the difficulty in estimating the other decision-makers' inconclusive decision criteria. These decision criteria may vary with different decision-makers because of their special risk tolerances and management requirements. Considering the general differences among the decision-makers in decentralized systems, we propose a general framework of fuzzy bilevel programming including hybrid models (integrated with different modelling methods in different levels). Specially, we discuss two of these models which may have wide applications in many fields. Furthermore, we apply the proposed two models to formulate a pricing decision problem in a decentralized supply chain with fuzzy coefficients. In order to solve these models, a hybrid intelligent algorithm integrating fuzzy simulation, neural network and particle swarm optimization based on penalty function approach is designed. Some suggestions on the applications of these models are also presented.
Power Grid Construction Project Portfolio Optimization Based on Bi-level programming model
Zhao, Erdong; Li, Shangqi
2017-08-01
As the main body of power grid operation, county-level power supply enterprises undertake an important emission to guarantee the security of power grid operation and safeguard social power using order. The optimization of grid construction projects has been a key issue of power supply capacity and service level of grid enterprises. According to the actual situation of power grid construction project optimization of county-level power enterprises, on the basis of qualitative analysis of the projects, this paper builds a Bi-level programming model based on quantitative analysis. The upper layer of the model is the target restriction of the optimal portfolio; the lower layer of the model is enterprises’ financial restrictions on the size of the enterprise project portfolio. Finally, using a real example to illustrate operation proceeding and the optimization result of the model. Through qualitative analysis and quantitative analysis, the bi-level programming model improves the accuracy and normative standardization of power grid enterprises projects.
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Zhipeng Huang
2014-01-01
Full Text Available The passenger travel demands for intercity rail lines fluctuate obviously during different time periods, which makes the rail departments unable to establish an even train operation scheme. This paper considers an optimization problem for train operations which respond to passenger travel demands of different periods in intercity rail lines. A satisfactory function of passenger travelling is proposed by means of analyzing the passengers’ travel choice behavior and correlative influencing factors. On this basis, the paper formulates a bilevel programming model which maximizes interests of railway enterprises and travelling satisfaction of each passenger. The trains operation in different periods can be optimized through upper layer planning of the model, while considering the passenger flow distribution problem based on the Wardrop user equilibrium principle in the lower layer planning. Then, a genetic algorithm is designed according to model features for solving the upper laying. The Frank-Wolfe algorithm is used for solving the lower layer planning. Finally, a numerical example is provided to demonstrate the application of the method proposed in this paper.
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Xiao-feng Xu
2017-01-01
Full Text Available Collaborative logistics network resource allocation can effectively meet the needs of customers. It can realize the overall benefit maximization of the logistics network and ensure that collaborative logistics network runs orderly at the time of creating value. Therefore, this article is based on the relationship of collaborative logistics network supplier, the transit warehouse, and sellers, and we consider the uncertainty of time to establish a bilevel programming model with random constraints and propose a genetic simulated annealing hybrid intelligent algorithm to solve it. Numerical example shows that the method has stronger robustness and convergence; it can achieve collaborative logistics network resource allocation rationalization and optimization.
Networked Timetable Stability Improvement Based on a Bilevel Optimization Programming Model
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Xuelei Meng
2014-01-01
Full Text Available Train timetable stability is the possibility to recover the status of the trains to serve as arranged according to the original timetable when the trains are disturbed. To improve the train timetable stability from the network perspective, the bilevel programming model is constructed, in which the upper level programming is to optimize the timetable stability on the network level and the lower is to improve the timetable stability on the dispatching railway segments. Timetable stability on the network level is defined with the variances of the utilization coefficients of the section capacity and station capacity. Weights of stations and sections are decided by the capacity index number and the degrees. The lower level programming focuses on the buffer time distribution plan of the trains operating on the sections and stations, taking the operating rules of the trains as constraints. A novel particle swarm algorithm is proposed and designed for the bilevel programming model. The computing case proves the feasibility of the model and the efficiency of the algorithm. The method outlined in this paper can be embedded in the networked train operation dispatching system.
Directory of Open Access Journals (Sweden)
Chongfeng Ren
2018-04-01
Full Text Available Water competing conflict among water competing sectors from different levels should be taken under consideration during the optimization allocation of water resources. Furthermore, uncertainties are inevitable in the optimization allocation of water resources. In order to deal with the above problems, this study developed a fuzzy max–min decision bi-level fuzzy programming model. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, the net benefit and yield were regarded as the upper-level and lower-level objectives, respectively. Optimal water resource plans were obtained under different possibility levels of fuzzy parameters, which could deal with water competing conflict between the upper level and the lower level effectively. The obtained results are expected to make great contribution in helping local decision-makers to make decisions on dealing with the water competing conflict between the upper and lower level and the optimal use of water resources under uncertainty.
Fuzzy Bi-level Decision-Making Techniques: A Survey
Directory of Open Access Journals (Sweden)
Guangquan Zhang
2016-04-01
Full Text Available Bi-level decision-making techniques aim to deal with decentralized management problems that feature interactive decision entities distributed throughout a bi-level hierarchy. A challenge in handling bi-level decision problems is that various uncertainties naturally appear in decision-making process. Significant efforts have been devoted that fuzzy set techniques can be used to effectively deal with uncertain issues in bi-level decision-making, known as fuzzy bi-level decision-making techniques, and researchers have successfully gained experience in this area. It is thus vital that an instructive review of current trends in this area should be conducted, not only of the theoretical research but also the practical developments. This paper systematically reviews up-to-date fuzzy bi-level decisionmaking techniques, including models, approaches, algorithms and systems. It also clusters related technique developments into four main categories: basic fuzzy bi-level decision-making, fuzzy bi-level decision-making with multiple optima, fuzzy random bi-level decision-making, and the applications of bi-level decision-making techniques in different domains. By providing state-of-the-art knowledge, this survey paper will directly support researchers and practitioners in their understanding of developments in theoretical research results and applications in relation to fuzzy bi-level decision-making techniques.
Robust optimization methods for chance constrained, simulation-based, and bilevel problems
Yanikoglu, I.
2014-01-01
The objective of robust optimization is to find solutions that are immune to the uncertainty of the parameters in a mathematical optimization problem. It requires that the constraints of a given problem should be satisfied for all realizations of the uncertain parameters in a so-called uncertainty
Solution Algorithm for a New Bi-Level Discrete Network Design Problem
Directory of Open Access Journals (Sweden)
Qun Chen
2013-12-01
Full Text Available A new discrete network design problem (DNDP was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.
Song, Lei; Zhang, Bo
2017-07-01
Nowadays, the grid faces much more challenges caused by wind power and the accessing of electric vehicles (EVs). Based on the potentiality of coordinated dispatch, a model of wind-EVs coordinated dispatch was developed. Then, A bi-level particle swarm optimization algorithm for solving the model was proposed in this paper. The application of this algorithm to 10-unit test system carried out that coordinated dispatch can benefit the power system from the following aspects: (1) Reducing operating costs; (2) Improving the utilization of wind power; (3) Stabilizing the peak-valley difference.
Cai, Yanpeng; Rong, Qiangqiang; Yang, Zhifeng; Yue, Wencong; Tan, Qian
2018-02-01
In this research, an export coefficient based inexact fuzzy bi-level multi-objective programming (EC-IFBLMOP) model was developed through integrating export coefficient model (ECM), interval parameter programming (IPP) and fuzzy parameter programming (FPP) within a bi-level multi-objective programming framework. The proposed EC-IFBLMOP model can effectively deal with the multiple uncertainties expressed as discrete intervals and fuzzy membership functions. Also, the complexities in agricultural systems, such as the cooperation and gaming relationship between the decision makers at different levels, can be fully considered in the model. The developed model was then applied to identify the optimal land use patterns and BMP implementing levels for agricultural nonpoint source (NPS) pollution management in a subcatchment in the upper stream watershed of the Miyun Reservoir in north China. The results of the model showed that the desired optimal land use patterns and implementing levels of best management of practices (BMPs) would be obtained. It is the gaming result between the upper- and lower-level decision makers, when the allowable discharge amounts of NPS pollutants were limited. Moreover, results corresponding to different decision scenarios could provide a set of decision alternatives for the upper- and lower-level decision makers to identify the most appropriate management strategy. The model has a good applicability and can be effectively utilized for agricultural NPS pollution management.
Algorithms for Mathematical Programming with Emphasis on Bi-level Models
Energy Technology Data Exchange (ETDEWEB)
Goldfarb, Donald [Columbia University; Iyengar, Garud [Columbia University
2014-05-22
The research supported by this grant was focused primarily on first-order methods for solving large scale and structured convex optimization problems and convex relaxations of nonconvex problems. These include optimal gradient methods, operator and variable splitting methods, alternating direction augmented Lagrangian methods, and block coordinate descent methods.
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...
MILP Approach for Bilevel Transmission and Reactive Power Planning Considering Wind Curtailment
DEFF Research Database (Denmark)
Ugranli, Faruk; Karatepe, Engin; Nielsen, Arne Hejde
2017-01-01
In this study, two important planning problems in power systems that are transmission expansion and reactive power are formulated as a mixed-integer linear programming taking into account the bilevel structure due to the consideration of market clearing under several load-wind scenarios....... The objective of the proposed method is to minimize the installation cost of transmission lines, reactive power sources, and the annual operation costs of conventional generators corresponding to the curtailed wind energy while maintaining the reliable system operation. Lower level problems of the bilevel...... structure are designated for the market clearing which is formulated by using the linearized optimal power flow equations. In order to obtain mixed-integer linear programming formulation, the so-called lower level problems are represented by using primal-dual formulation. By using the proposed method, power...
Bilevel alarm monitoring multiplexer
International Nuclear Information System (INIS)
Johnson, C.S.
1977-06-01
This report describes the operation of the Bilevel Alarm Monitoring Multiplexer used in the Adaptive Intrusion Data System (AIDS) to transfer and control alarm signals being sent to the Nova 2 computer, the Memory Controlled Data Processor, and its own integral Display Panel. The multiplexer can handle 48 alarm channels and format the alarms into binary formats compatible with the destination of the alarm data
Bi-Level Optimization for Available Transfer Capability Evaluation in Deregulated Electricity Market
Directory of Open Access Journals (Sweden)
Beibei Wang
2015-11-01
Full Text Available Available transfer capability (ATC is the transfer capability remaining in the physical transmission network for further commercial activity over and above already committed uses which needs to be posted in the electricity market to facilitate competition. ATC evaluation is a complicated task including the determination of total transfer capability (TTC and existing transfer capability (ETC. In the deregulated electricity market, ETC is decided by the independent system operator’s (ISO’s economic dispatch (ED. TTC can then be obtained by a continuation power flow (CPF method or by an optimal power flow (OPF method, based on the given ED solutions as well as the ETC. In this paper, a bi-level optimization framework for the ATC evaluation is proposed in which ATC results can be obtained simultaneously with the ED and ETC results in the deregulated electricity market. In this bi-level optimization model, ATC evaluation is formulated as the upper level problem and the ISO’s ED is the lower level problem. The bi-level model is first converted to a mathematic program with equilibrium constraints (MPEC by recasting the lower level problem as its Karush-Kuhn-Tucher (KKT optimality condition. Then, the MPEC is transformed into a mixed-integer linear programming (MILP problem, which can be solved with the help of available optimization software. In addition, case studies on PJM 5-bus, IEEE 30-bus, and IEEE 118-bus systems are presented to demonstrate the proposed methodology.
Bilevel Fuzzy Chance Constrained Hospital Outpatient Appointment Scheduling Model
Directory of Open Access Journals (Sweden)
Xiaoyang Zhou
2016-01-01
Full Text Available Hospital outpatient departments operate by selling fixed period appointments for different treatments. The challenge being faced is to improve profit by determining the mix of full time and part time doctors and allocating appointments (which involves scheduling a combination of doctors, patients, and treatments to a time period in a department optimally. In this paper, a bilevel fuzzy chance constrained model is developed to solve the hospital outpatient appointment scheduling problem based on revenue management. In the model, the hospital, the leader in the hierarchy, decides the mix of the hired full time and part time doctors to maximize the total profit; each department, the follower in the hierarchy, makes the decision of the appointment scheduling to maximize its own profit while simultaneously minimizing surplus capacity. Doctor wage and demand are considered as fuzzy variables to better describe the real-life situation. Then we use chance operator to handle the model with fuzzy parameters and equivalently transform the appointment scheduling model into a crisp model. Moreover, interactive algorithm based on satisfaction is employed to convert the bilevel programming into a single level programming, in order to make it solvable. Finally, the numerical experiments were executed to demonstrate the efficiency and effectiveness of the proposed approaches.
A Compromise Programming Model for Highway Maintenance Resources Allocation Problem
Directory of Open Access Journals (Sweden)
Hui Xiong
2012-01-01
Full Text Available This paper formulates a bilevel compromise programming model for allocating resources between pavement and bridge deck maintenances. The first level of the model aims to solve the resource allocation problems for pavement management and bridge deck maintenance, without considering resource sharing between them. At the second level, the model uses the results from the first step as an input and generates the final solution to the resource-sharing problem. To solve the model, the paper applies genetic algorithms to search for the optimal solution. We use a combination of two digits to represent different maintenance types. Results of numerical examples show that the conditions of both pavements and bridge decks are improved significantly by applying compromise programming, rather than conventional methods. Resources are also utilized more efficiently when the proposed method is applied.
On generalized semi-infinite optimization and bilevel optimization
Stein, O.; Still, Georg J.
2000-01-01
The paper studies the connections and differences between bilevel problems (BL) and generalized semi-infinite problems (GSIP). Under natural assumptions (GSIP) can be seen as a special case of a (BL). We consider the so-called reduction approach for (BL) and (GSIP) leading to optimality conditions
DEFF Research Database (Denmark)
Rashidizaheh-Kermani, Homa; Vahedipour-Dahraie, Mostafa; Najafi, Hamid Reza
2017-01-01
are modeled via stochastic programming. Therefore, a two-level problem is formulated here, in which the aggregator makes decision in the upper level and the EV clients purchase energy to charge their EVs in the lower level. Then the obtained nonlinear bi-level framework is transformed into a single......This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggregator in a competitive environment. In this approach, the EV aggregator decides to participate in day-ahead (DA) and balancing markets and provides energy price offers to the EV owners in order...... is assessed in a realistic case study and the results show that the proposed model would be effective for an EV aggregator decision-making problem in a competitive environment....
DEFF Research Database (Denmark)
Martins, Bo; Forchhammer, Søren
1998-01-01
Presently, sequential tree coders are the best general purpose bilevel image coders and the best coders of halftoned images. The current ISO standard, Joint Bilevel Image Experts Group (JBIG), is a good example. A sequential tree coder encodes the data by feeding estimates of conditional...... is one order of magnitude slower than JBIG, obtains excellent and highly robust compression performance. A multipass free tree coding scheme produces superior compression results for all test images. A multipass free template coding scheme produces significantly better results than JBIG for difficult...... images such as halftones. By utilizing randomized subsampling in the template selection, the speed becomes acceptable for practical image coding...
Comparison of bi-level optimization frameworks for sizing and control of a hybrid electric vehicle
Silvas, E.; Bergshoeff, N.D.; Hofman, T.; Steinbuch, M.
2015-01-01
This paper discusses the integrated design problem related to determining the power specifications of the main subsystems (sizing) and the supervisory control (energy management). Different bi-level optimization methods, with the outer loop using algorithms as Genetic Algorithms, Sequential
Neutrosophic Integer Programming Problem
Directory of Open Access Journals (Sweden)
Mai Mohamed
2017-02-01
Full Text Available In this paper, we introduce the integer programming in neutrosophic environment, by considering coffecients of problem as a triangulare neutrosophic numbers. The degrees of acceptance, indeterminacy and rejection of objectives are simultaneously considered.
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.
Bilevel Traffic Evacuation Model and Algorithm Design for Large-Scale Activities
Directory of Open Access Journals (Sweden)
Danwen Bao
2017-01-01
Full Text Available This paper establishes a bilevel planning model with one master and multiple slaves to solve traffic evacuation problems. The minimum evacuation network saturation and shortest evacuation time are used as the objective functions for the upper- and lower-level models, respectively. The optimizing conditions of this model are also analyzed. An improved particle swarm optimization (PSO method is proposed by introducing an electromagnetism-like mechanism to solve the bilevel model and enhance its convergence efficiency. A case study is carried out using the Nanjing Olympic Sports Center. The results indicate that, for large-scale activities, the average evacuation time of the classic model is shorter but the road saturation distribution is more uneven. Thus, the overall evacuation efficiency of the network is not high. For induced emergencies, the evacuation time of the bilevel planning model is shortened. When the audience arrival rate is increased from 50% to 100%, the evacuation time is shortened from 22% to 35%, indicating that the optimization effect of the bilevel planning model is more effective compared to the classic model. Therefore, the model and algorithm presented in this paper can provide a theoretical basis for the traffic-induced evacuation decision making of large-scale activities.
Adolescent Assertiveness: Problems and Programs.
Reece, Randi S.; Wilborn, Bobbie L.
1980-01-01
Assertiveness training programs in the school setting provide a method to work with students with behavior problems. When students can manage their environments more effectively, they view the educational experience more positively and find that their present world and their transition to the adult world proceeds more productively. (Author)
Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification
Li, Yi; Song, Lingxiao; Wu, Xiang; He, Ran; Tan, Tieniu
2017-01-01
Makeup is widely used to improve facial attractiveness and is well accepted by the public. However, different makeup styles will result in significant facial appearance changes. It remains a challenging problem to match makeup and non-makeup face images. This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN). To alleviate the negative effects from makeup, we first generate non-makeup images from makeu...
A Hybrid Tabu Search Heuristic for a Bilevel Competitive Facility Location Model
Küçükaydın, Hande; Aras, Necati; Altınel, I. Kuban
We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff's gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.
Measurement problem in PROGRAM UNIVERSE
International Nuclear Information System (INIS)
Noyes, H.P.; Gefwert, C.
1984-12-01
We present a discrete theory that meets the measurement problem in a new way. We generate a growing universe of bit strings, labeled by 2 127 + 136 strings organized by some representation of the closed, four level, combinatorial hierarchy, of bit-length N 139 greater than or equal to 139. The rest of the strings for each label, which grow in both length and number, are called addresses. The generating algorithm, called PROGRAM UNIVERSE, starts from a random choice between the two symbols ''0'' and ''1'' and grows (a) by discriminating between two randomly chosen strings and adjoining a novel result to the universe, or when the string so generated is not novel, by (b) adjoining a randomly chosen bit at the growing end of each string. We obtain, by appropriate definitions and interpretations, stable ''particles'' which satisfy the usual relativistic kinematics and quantized angular momentum without being localizable in a continuum space-time. The labeling scheme is congruent with the ''standard model'' of quarks and leptons with three generations, but for the problem at hand, the implementation of this aspect of the theory is unimportant. What matters most is that (a) these complicated ''particles'' have the periodicities familiar from relativistic ''deBroglie waves'' and resolve in a discrete way the ''wave-particle dualism'' and (b) can be ''touched'' by our discrete equivalent of ''soft photons'' in such a way as to follow, macroscopically, the usual Rutherford scattering trajectories with the associated bound states. Thus our theory could provide a discrete description of ''measurement'' in a way that allows no conceptual barrier between the ''micro'' and the ''macro'' worlds, if we are willing to base our physics on counting and exclude the ambiguities associated with the unobservable ''continuum''. 27 refs
Directory of Open Access Journals (Sweden)
F. Misaghi
2017-06-01
Full Text Available In this paper, a novel framework is proposed to study impacts of regulatory incentive on distributed generation (DG investment in sub-transmission substations, as well as upgrading of upstream transmission substations. Both conventional and wind power technologies are considered here. Investment incentives are fuel cost, firm contracts, capacity payment and investment subsidy relating to wind power. The problem is modelled as a bi-level stochastic optimization problem, where the upper level consists of investor's decisions maximizing its own profit. Both market clearing and decision on upgrading of transmission substation aiming at minimizing the total cost are considered in the lower level. Due to non-convexity of the lower level and impossibility of converting to single level problem (i.e. mathematical programming with equilibrium constraints (MPEC, an algorithm combing enumeration and mathematical optimization is used to tackle with the non-convexity. For each upgrading strategy of substations, a stochastic MPEC, converted to a mixed integer linear programming (MILP is solved. The proposed model is examined on a six-bus and an actual network. Numerical studies confirm that the proposed model can be used for analysing investment behaviour of DGs and substation expansion.
Bivium as a Mixed Integer Programming Problem
DEFF Research Database (Denmark)
Borghoff, Julia; Knudsen, Lars Ramkilde; Stolpe, Mathias
2009-01-01
over $GF(2)$ into a combinatorial optimization problem. We convert the Boolean equation system into an equation system over $\\mathbb{R}$ and formulate the problem of finding a $0$-$1$-valued solution for the system as a mixed-integer programming problem. This enables us to make use of several...
Multiple Depots Vehicle Routing Problem in the Context of Total Urban Traffic Equilibrium
Chen, Dongxu; Yang, Zhongzhen
2017-01-01
A multidepot VRP is solved in the context of total urban traffic equilibrium. Under the total traffic equilibrium, the multidepot VRP is changed to GDAP (the problem of Grouping Customers + Estimating OD Traffic + Assigning traffic) and bilevel programming is used to model the problem, where the upper model determines the customers that each truck visits and adds the trucks’ trips to the initial OD (Origin/Destination) trips, and the lower model assigns the OD trips to road network. Feedback ...
Directory of Open Access Journals (Sweden)
AYAS, S.
2018-02-01
Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.
Directory of Open Access Journals (Sweden)
F. Nazari
2017-03-01
Full Text Available By increasing the use of distributed generation (DG in the distribution network operation, an entity called virtual power plant (VPP has been introduced to control, dispatch and aggregate the generation of DGs, enabling them to participate either in the electricity market or the distribution network operation. The participation of VPPs in the electricity market has made challenges to fairly allocate payments and benefits between VPPs and distribution network operator (DNO. This paper presents a bilevel scheduling approach to model the energy transaction between VPPs and DNO. The upper level corresponds to the decision making of VPPs which bid their long- term contract prices so that their own profits are maximized and the lower level represents the DNO decision making to supply electricity demand of the network by minimizing its overall cost. The proposed bilevel scheduling approach is transformed to a single level optimizing problem using its Karush-Kuhn-Tucker (KKT optimality conditions. Several scenarios are applied to scrutinize the effectiveness and usefulness of the proposed model.
Employee assistance program treats personal problems.
Bednarek, R J; Featherston, H J
1984-03-01
Though the concept of employee assistance programs (EAPs) is widely accepted throughout business and industry, few hospitals have established similar channels for dealing with workers whose personal problems cause work-related problems. Among the reasons for the health care profession's lack of involvement in this area are: lack of information about costs and benefits of EAPs; the hospital's multidisciplinary environment in which standards of employee competence and behavior are set by persons from many disciplines; hospital working hours; and health care workers' attitudes about their vulnerability to illness. St. Benedict's Hospital, Ogden, UT, however, has confronted the question of how to demonstrate Christian concern for its employees. St. Benedict's EAP, the Helping Hand, which was created in 1979, combines progressive disciplinary action with the opportunity for early intervention in and treatment of employees' personal problems. When a worker with personal problems is referred to the EAP coordinator, he or she is matched with the appropriate community or hospital resource for treatment. Supervisors are trained to identify employee problems and to focus on employee job performance rather than on attempting to diagnose the problem. St. Benedict's records during the program's first three years illustrate the human benefits as well as the cost savings of an EAP. Of 92 hospital employees who took part in the EAP, 72 improved their situations or resolved their problems. The hospital's turnover rates declined from 36 percent to 20 percent, and approximately $40,800 in turnover and replacement costs were saved.
θ-convex nonlinear programming problems
International Nuclear Information System (INIS)
Emam, T.
2008-01-01
A class of sets and a class of functions called θ-convex sets and θ-convex functions are introduced by relaxing the definitions of convex sets and operator θ on the sets and domain of definition of the functions. The optimally results for θ-convex programming problems are established.
[Possibilities of bi-level positive pressure ventilation in chronic hypoventilation].
Saaresranta, Tarja; Anttalainen, Ulla; Polo, Olli
2011-01-01
During the last decade, noninvasive bi-level positive pressure ventilation has enabled respiratory support in inpatient wards and at home. In many cases, a bi-level airway pressure ventilator can be used to avoid artificial airway and respirator therapy, and may shorten hospital stay and save costs. The treatment alleviates the patient's dyspnea and fatigue, whereby the quality of life improves, and in certain situations also the life span increases. The implementation of bi-level positive pressure ventilation by the physician requires knowledge of the basics of respiratory physiology and familiarization with the bi-level airway pressure ventilator.
Bilevel thresholding of sliced image of sludge floc.
Chu, C P; Lee, D J
2004-02-15
This work examined the feasibility of employing various thresholding algorithms to determining the optimal bilevel thresholding value for estimating the geometric parameters of sludge flocs from the microtome sliced images and from the confocal laser scanning microscope images. Morphological information extracted from images depends on the bilevel thresholding value. According to the evaluation on the luminescence-inverted images and fractal curves (quadric Koch curve and Sierpinski carpet), Otsu's method yields more stable performance than other histogram-based algorithms and is chosen to obtain the porosity. The maximum convex perimeter method, however, can probe the shapes and spatial distribution of the pores among the biomass granules in real sludge flocs. A combined algorithm is recommended for probing the sludge floc structure.
Bayesian Group Bridge for Bi-level Variable Selection.
Mallick, Himel; Yi, Nengjun
2017-06-01
A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.
Menu-Driven Solver Of Linear-Programming Problems
Viterna, L. A.; Ferencz, D.
1992-01-01
Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).
Programming languages for business problem solving
Wang, Shouhong
2007-01-01
It has become crucial for managers to be computer literate in today's business environment. It is also important that those entering the field acquire the fundamental theories of information systems, the essential practical skills in computer applications, and the desire for life-long learning in information technology. Programming Languages for Business Problem Solving presents a working knowledge of the major programming languages, including COBOL, C++, Java, HTML, JavaScript, VB.NET, VBA, ASP.NET, Perl, PHP, XML, and SQL, used in the current business computing environment. The book examin
Continuous reformulations for zero-one programming problems
Marianna De Santis; Francesco Rinaldi
2010-01-01
In this work, we study continuous reformulations of zero-one programming problems. We prove that, under suitable conditions, the optimal solutions of a zero-one programming problem can be obtained by solving a specific continuous problem.
Bi-level image compression with tree coding
DEFF Research Database (Denmark)
Martins, Bo; Forchhammer, Søren
1996-01-01
Presently, tree coders are the best bi-level image coders. The current ISO standard, JBIG, is a good example. By organising code length calculations properly a vast number of possible models (trees) can be investigated within reasonable time prior to generating code. Three general-purpose coders...... are constructed by this principle. A multi-pass free tree coding scheme produces superior compression results for all test images. A multi-pass fast free template coding scheme produces much better results than JBIG for difficult images, such as halftonings. Rissanen's algorithm `Context' is presented in a new...
Lossy/lossless coding of bi-level images
DEFF Research Database (Denmark)
Martins, Bo; Forchhammer, Søren
1997-01-01
Summary form only given. We present improvements to a general type of lossless, lossy, and refinement coding of bi-level images (Martins and Forchhammer, 1996). Loss is introduced by flipping pixels. The pixels are coded using arithmetic coding of conditional probabilities obtained using a template...... as is known from JBIG and proposed in JBIG-2 (Martins and Forchhammer). Our new state-of-the-art results are obtained using the more general free tree instead of a template. Also we introduce multiple refinement template coding. The lossy algorithm is analogous to the greedy `rate...
Multi-objective convex programming problem arising in multivariate ...
African Journals Online (AJOL)
user
Multi-objective convex programming problem arising in ... However, although the consideration of multiple objectives may seem a novel concept, virtually any nontrivial ..... Solving multiobjective programming problems by discrete optimization.
Personalized Age Progression with Bi-Level Aging Dictionary Learning.
Shu, Xiangbo; Tang, Jinhui; Li, Zechao; Lai, Hanjiang; Zhang, Liyan; Yan, Shuicheng
2018-04-01
Age progression is defined as aesthetically re-rendering the aging face at any future age for an individual face. In this work, we aim to automatically render aging faces in a personalized way. Basically, for each age group, we learn an aging dictionary to reveal its aging characteristics (e.g., wrinkles), where the dictionary bases corresponding to the same index yet from two neighboring aging dictionaries form a particular aging pattern cross these two age groups, and a linear combination of all these patterns expresses a particular personalized aging process. Moreover, two factors are taken into consideration in the dictionary learning process. First, beyond the aging dictionaries, each person may have extra personalized facial characteristics, e.g., mole, which are invariant in the aging process. Second, it is challenging or even impossible to collect faces of all age groups for a particular person, yet much easier and more practical to get face pairs from neighboring age groups. To this end, we propose a novel Bi-level Dictionary Learning based Personalized Age Progression (BDL-PAP) method. Here, bi-level dictionary learning is formulated to learn the aging dictionaries based on face pairs from neighboring age groups. Extensive experiments well demonstrate the advantages of the proposed BDL-PAP over other state-of-the-arts in term of personalized age progression, as well as the performance gain for cross-age face verification by synthesizing aging faces.
International Nuclear Information System (INIS)
Chen, Yizhong; He, Li; Li, Jing; Cheng, Xi; Lu, Hongwei
2016-01-01
Highlights: • Detailed model developed for power generation and pollutants mitigation. • Dynamic integration of bi-level programming with uncertainty analyses. • Application of the novel bi-level model for EPS in Fengtai District. • Development of renewable energy under different probability levels. - Abstract: In this study, an IBSOM (inexact bi-level simulation–optimization model) is developed for conjunctive regional renewable energy planning and air pollution control for EPS (electric power systems) under uncertainty. The IBSOM integrates techniques of CFMTVW (combined forecasting model with time-varying weights), ILP (interval linear programming), MIP (mixed integer programming), CCP (chance-constrained programming), as well as BLP (bi-level programming) into a general framework. In the IBSOM, uncertainties expressed as interval and stochastic parameters within multi-period and multi-option contexts can be effectively tackled. In addition, a leader-follower decision strategy is incorporated into the optimization process where two non-competitive objectives are sequentially proposed, with the environmental sector dominating the upper-level objective (leader’s one) and the energy sector providing the lower-level objective (follower’s one). To solve the proposed model, an improved bi-level interactive solution algorithm based on satisfactory degree is introduced into the decision-making process for balancing to what extent the constraints are met and the objective reaches its optima. Then, the IBSOM is applied to a real-world case study of EPS in Fengtai District, Beijing, China. Interval solutions associated with renewable energy development, electricity generation, facility-expansion scheme, as well as pollutants mitigation can be obtained under different system-violation risk. Results indicate that a higher violation risk would lead to a decreased strictness of the constraints or an expanded decision space, which results in the decreased system
Research program with no ''measurement problem''
International Nuclear Information System (INIS)
Noyes, H.P.; Gefwert, C.; Manthey, M.J.
1985-07-01
The ''measurement problem'' of contemporary physics is met by recognizing that the physicist participates when constructing and when applying the theory consisting of the formulated formal and measurement criteria (the expressions and rules) providing the necessary conditions which allow him to compute and measure facts, yet retains objectivity by requiring that these criteria, rules and facts be in corroborative equilibrium. We construct the particulate states of quantum physics by a recursive program which incorporates the non-determinism born of communication between asynchronous processes over a shared memory. Their quantum numbers and coupling constants arise from the construction via the unique 4-level combinatorial hierarchy. The construction defines indivisible quantum events with the requisite supraluminal correlations, yet does not allow supraluminal communication. Measurement criteria incorporate c, h-bar, and m/sub p/ or (not ''and'') G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact
Contribution of Fuzzy Minimal Cost Flow Problem by Possibility Programming
S. Fanati Rashidi; A. A. Noora
2010-01-01
Using the concept of possibility proposed by zadeh, luhandjula ([4,8]) and buckley ([1]) have proposed the possibility programming. The formulation of buckley results in nonlinear programming problems. Negi [6]re-formulated the approach of Buckley by the use of trapezoidal fuzzy numbers and reduced the problem into fuzzy linear programming problem. Shih and Lee ([7]) used the Negi approach to solve a minimum cost flow problem, whit fuzzy costs and the upper and lower bound. ...
Library of problem-oriented programs for solving problems of atomic and nuclear physics
International Nuclear Information System (INIS)
Kharitonov, Yu.I.
1976-01-01
The Data Centre of the Leningrad Institute of Nuclear Physics (LIYaF) is working on the establishment of a library of problem-oriented computer programs for solving problems of atomic and nuclear physics. This paper lists and describes briefly the programs presently available to the Data Centre. The descriptions include the program code numbers, the program language, the translator for which the program is designed, and the program scope
A Dynamic Programming Algorithm for the k-Haplotyping Problem
Institute of Scientific and Technical Information of China (English)
Zhen-ping Li; Ling-yun Wu; Yu-ying Zhao; Xiang-sun Zhang
2006-01-01
The Minimum Fragments Removal (MFR) problem is one of the haplotyping problems: given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the k-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the k-MFR problem for both the gapless and gap cases.
K-Minimax Stochastic Programming Problems
Nedeva, C.
2007-10-01
The purpose of this paper is a discussion of a numerical procedure based on the simplex method for stochastic optimization problems with partially known distribution functions. The convergence of this procedure is proved by the condition on dual problems.
Jin, S W; Li, Y P; Nie, S
2018-05-15
In this study, an interval chance-constrained bi-level programming (ICBP) method is developed for air quality management of municipal energy system under uncertainty. ICBP can deal with uncertainties presented as interval values and probability distributions as well as examine the risk of violating constraints. Besides, a leader-follower decision strategy is incorporated into the optimization process where two decision makers with different goals and preferences are involved. To solve the proposed model, a bi-level interactive algorithm based on satisfactory degree is introduced into the decision-making processes. Then, an ICBP based energy and environmental systems (ICBP-EES) model is formulated for Beijing, in which air quality index (AQI) is used for evaluating the integrated air quality of multiple pollutants. Result analysis can help different stakeholders adjust their tolerances to achieve the overall satisfaction of EES planning for the study city. Results reveal that natural gas is the main source for electricity-generation and heating that could lead to a potentially increment of imported energy for Beijing in future. Results also disclose that PM 10 is the major contributor to AQI. These findings can help decision makers to identify desired alternatives for EES planning and provide useful information for regional air quality management under uncertainty. Copyright © 2018 Elsevier B.V. All rights reserved.
Su, Mei; Huai, De; Cao, Juan; Ning, Ding; Xue, Rong; Xu, Meijie; Huang, Mao; Zhang, Xilong
2018-03-01
Although bilevel positive airway pressure (Bilevel PAP) therapy is usually used for overlap syndrome (OS), there is still a portion of OS patients in whom Bilevel PAP therapy could not simultaneously eliminate residual apnea events and hypercapnia. The current study was expected to explore whether auto-trilevel positive airway pressure (auto-trilevel PAP) therapy with auto-adjusting end expiratory positive airway pressure (EEPAP) can serve as a better alternative for these patients. From January of 2014 to June of 2016, 32 hypercapnic OS patients with stable chronic obstructive pulmonary diseases (COPD) and moderate-to-severe obstructive sleep apnea syndrome (OSAS) were recruited. Three variable modes of positive airway pressure (PAP) from the ventilator (Prisma25ST, Weinmann Inc., Germany) were applicated for 8 h per night. We performed the design of each mode at each night with an interval of two nights with no PAP treatment as a washout period among different modes. In Bilevel-1 mode (Bilevel-1), the expiratory positive airway pressure (EPAP) delivered from Bilevel PAP was always set as the lowest PAP for abolishment of snoring. For each patient, the inspiratory positive airway pressure (IPAP) was constantly set the same as the minimal pressure for keeping end-tidal CO 2 (ETCO 2 ) ≤45 mmHg for all three modes. However, the EPAP issued by Bilevel PAP in Bilevel-2 mode (Bilevel-2) was kept 3 cmH 2 O higher than that in Bilevel-1. In auto-trilevel mode (auto-trilevel) with auto-trilevel PAP, the initial part of EPAP was fixed at the same PAP as that in Bilevel-1 while the EEPAP was automatically regulated to rise at a range of ≤4 cmH 2 O based on nasal airflow wave changes. Comparisons were made for parameters before and during or following treatment as well as among different PAP therapy modes. The following parameters were compared such as nocturnal apnea hypopnea index (AHI), minimal SpO 2 (minSpO 2 ), arousal index, sleep structure and efficiency
M. ZANGIABADI; H. R. MALEKI
2007-01-01
In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters based on those for multiobjective linear programming problems. Then by using the concept of comparison of fuzzy numbers, we transform a linear programming problem with fuzzy parameters to a multiobjective linear programming problem. To this end, w...
Contribution of Fuzzy Minimal Cost Flow Problem by Possibility Programming
Directory of Open Access Journals (Sweden)
S. Fanati Rashidi
2010-06-01
Full Text Available Using the concept of possibility proposed by zadeh, luhandjula ([4,8] and buckley ([1] have proposed the possibility programming. The formulation of buckley results in nonlinear programming problems. Negi [6]re-formulated the approach of Buckley by the use of trapezoidal fuzzy numbers and reduced the problem into fuzzy linear programming problem. Shih and Lee ([7] used the Negi approach to solve a minimum cost flow problem, whit fuzzy costs and the upper and lower bound. In this paper we shall consider the general form of this problem where all of the parameters and variables are fuzzy and also a model for solving is proposed
Language Program Evaluation: Decisions, Problems, and Solutions.
Brown, James Dean
1995-01-01
Discusses the evaluation of second and foreign language programs, focusing on whether such evaluations should be summative or formative; use outside experts or program staff; emphasize qualitative or quantitative data; and concentrate on the process or the product. An annotated bibliography discusses six important works in the field. (78…
Bi-Level Integrated System Synthesis (BLISS) for Concurrent and Distributed Processing
Sobieszczanski-Sobieski, Jaroslaw; Altus, Troy D.; Phillips, Matthew; Sandusky, Robert
2002-01-01
The paper introduces a new version of the Bi-Level Integrated System Synthesis (BLISS) methods intended for optimization of engineering systems conducted by distributed specialty groups working concurrently and using a multiprocessor computing environment. The method decomposes the overall optimization task into subtasks associated with disciplines or subsystems where the local design variables are numerous and a single, system-level optimization whose design variables are relatively few. The subtasks are fully autonomous as to their inner operations and decision making. Their purpose is to eliminate the local design variables and generate a wide spectrum of feasible designs whose behavior is represented by Response Surfaces to be accessed by a system-level optimization. It is shown that, if the problem is convex, the solution of the decomposed problem is the same as that obtained without decomposition. A simplified example of an aircraft design shows the method working as intended. The paper includes a discussion of the method merits and demerits and recommendations for further research.
Constraint-based scheduling applying constraint programming to scheduling problems
Baptiste, Philippe; Nuijten, Wim
2001-01-01
Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...
Multiple Depots Vehicle Routing Problem in the Context of Total Urban Traffic Equilibrium
Directory of Open Access Journals (Sweden)
Dongxu Chen
2017-01-01
Full Text Available A multidepot VRP is solved in the context of total urban traffic equilibrium. Under the total traffic equilibrium, the multidepot VRP is changed to GDAP (the problem of Grouping Customers + Estimating OD Traffic + Assigning traffic and bilevel programming is used to model the problem, where the upper model determines the customers that each truck visits and adds the trucks’ trips to the initial OD (Origin/Destination trips, and the lower model assigns the OD trips to road network. Feedback between upper model and lower model is iterated through OD trips; thus total traffic equilibrium can be simulated.
A Quasi-Feed-In-Tariff policy formulation in micro-grids: A bi-level multi-period approach
International Nuclear Information System (INIS)
Taha, Ahmad F.; Hachem, Nadim A.; Panchal, Jitesh H.
2014-01-01
A Quasi-Feed-In-Tariff (QFIT) policy formulation is presented for micro-grids that integrates renewable energy generation considering Policy Makers' and Generation Companies' (GENCOs) objectives assuming a bi-level multi-period formulation that integrates physical characteristics of the power-grid. The upper-level problem corresponds to the PM, whereas the lower-level decisions are made by GENCOs. We consider that some GENCOs are green energy producers, while others are black energy producers. Policy makers incentivize green energy producers to generate energy through the payment of optimal time-varying subsidy price. The policy maker's main objective is to maximize an overall social welfare that includes factors such as demand surplus, energy cost, renewable energy subsidy price, and environmental standards. The lower-level problem corresponding to the GENCOs is based on maximizing the players' profits. The proposed QFIT policy differs from the FIT policy in the sense that the subsidy price-based contracts offered to green energy producers dynamically change over time, depending on the physical properties of the grid, demand, and energy price fluctuations. The integrated problem solves for time-varying subsidy price and equilibrium energy quantities that optimize the system welfare under different grid and system conditions. - Highlights: • We present a bi-level optimization problem formulation for Quasi-Feed-In-Tariff (QFIT) policy. • QFIT dictates that subsidy prices dynamically vary over time depending on conditions. • Power grid's physical characteristics affect optimal subsidy prices and energy generation. • To maximize welfare, policy makers ought to increase subsidy prices during the peak-load
Improve Problem Solving Skills through Adapting Programming Tools
Shaykhian, Linda H.; Shaykhian, Gholam Ali
2007-01-01
There are numerous ways for engineers and students to become better problem-solvers. The use of command line and visual programming tools can help to model a problem and formulate a solution through visualization. The analysis of problem attributes and constraints provide insight into the scope and complexity of the problem. The visualization aspect of the problem-solving approach tends to make students and engineers more systematic in their thought process and help them catch errors before proceeding too far in the wrong direction. The problem-solver identifies and defines important terms, variables, rules, and procedures required for solving a problem. Every step required to construct the problem solution can be defined in program commands that produce intermediate output. This paper advocates improved problem solving skills through using a programming tool. MatLab created by MathWorks, is an interactive numerical computing environment and programming language. It is a matrix-based system that easily lends itself to matrix manipulation, and plotting of functions and data. MatLab can be used as an interactive command line or a sequence of commands that can be saved in a file as a script or named functions. Prior programming experience is not required to use MatLab commands. The GNU Octave, part of the GNU project, a free computer program for performing numerical computations, is comparable to MatLab. MatLab visual and command programming are presented here.
Refinement from a control problem to program
DEFF Research Database (Denmark)
Schenke, Michael; Ravn, Anders P.
1996-01-01
The distinguishing feature of the presented refinement approach is that it links formalisms from a top level requirements notation down to programs together in a mathematically coherent development trajectory. The approach uses Duration Calculus, a real-time interval logic, to specifyrequirements...
An Approach for Solving Linear Fractional Programming Problems
Andrew Oyakhobo Odior
2012-01-01
Linear fractional programming problems are useful tools in production planning, financial and corporate planning, health care and hospital planning and as such have attracted considerable research interest. The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebr...
Problem solving and Program design using the TI-92
Ir.ing. Ton Marée; ir Martijn van Dongen
2000-01-01
This textbook is intended for a basic course in problem solving and program design needed by scientists and engineers using the TI-92. The TI-92 is an extremely powerful problem solving tool that can help you manage complicated problems quickly. We assume no prior knowledge of computers or
Mathematical programming and game theory for decision making
Bapat, R B; Das, A K; Parthasarathy, T
2008-01-01
This edited book presents recent developments and state-of-the-art review in various areas of mathematical programming and game theory. It is a peer-reviewed research monograph under the ISI Platinum Jubilee Series on Statistical Science and Interdisciplinary Research. This volume provides a panoramic view of theory and the applications of the methods of mathematical programming to problems in statistics, finance, games and electrical networks. It also provides an important as well as timely overview of research trends and focuses on the exciting areas like support vector machines, bilevel pro
WHO Polio Eradication Program: Problems and Solutions
Directory of Open Access Journals (Sweden)
S. M. Kharit
2016-01-01
Full Text Available In 2013 WHO re-evaluated its main goals of the polio eradication program. A modernization program was accepted with regard to the National vaccination calendars worldwide which includes a step-by-step refusal from the living polio vaccine (OPV and a total transition to the inactivated polio vaccine (IPV starting in 2019. Because of the total eradication of the polio type 2 virus, as an intermediate step the 3-valence OPV was substituted with the 2-valence OPV, which does not contain the type 2 polio virus, in April 2016. The aim of the article is to present the history of polio prevention and to state the reasons for the adoption of 3rd edition of the Global Polio Eradication Initiative. The new approaches were defined for eradication of wild polio virus type 1 and vaccine related strains. A new strategy for global switch to inactivated polio vaccine by 2019 was suggested.
THE TRAVELLING SALESMAN PROBLEM IN THE ENGINEERING EDUCATION PROGRAMMING CURRICULUM
Yevgeny Gayev; Vadim Kalmikov
2017-01-01
Objective: To make students familiar with the famous Traveling Salesman Problem (TSP) and suggest the latter to become a common exercise in engineering programming curriculum provided the students master computer science in the easy programming environment MATLAB. Methods: easy programming in MATLAB makes true such modern educational approach as “discovery based” methodology. Results: a MATLAB TSP-program oriented to Ukrainian map is suggested that allows to pictorially demonstrate the proces...
Measurement problem in Program Universe. Revision
International Nuclear Information System (INIS)
Noyes, H.P.; Gefwert, C.; Manthey, M.J.
1985-07-01
The ''measurement problem'' of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not ''and'') G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact. 15 refs
Measurement problem in Program Universe. Revision
Noyes, H. P.; Gefwert, C.; Manthey, M. J.
1985-07-01
The measurement problem of contemporary physics is in our view an artifact of its philosophical and mathematical underpinnings. We describe a new philosophical view of theory formation, rooted in Wittgenstein, and Bishop's and Martin-Loef's constructivity, which obviates such discussions. We present an unfinished, but very encouraging, theory which is compatible with this philosophical framework. The theory is based on the concepts of counting and combinatorics in the framework provided by the combinatorial hierarchy, a unique hierarchy of bit strings which interact by an operation called discrimination. Measurement criteria incorporate c, h-bar and m/sub p/ or (not and) G. The resulting theory is discrete throughout, contains no infinities, and, as far as we have developed it, is in agreement with quantum mechanical and cosmological fact.
An extension of the directed search domain algorithm to bilevel optimization
Wang, Kaiqiang; Utyuzhnikov, Sergey V.
2017-08-01
A method is developed for generating a well-distributed Pareto set for the upper level in bilevel multiobjective optimization. The approach is based on the Directed Search Domain (DSD) algorithm, which is a classical approach for generation of a quasi-evenly distributed Pareto set in multiobjective optimization. The approach contains a double-layer optimizer designed in a specific way under the framework of the DSD method. The double-layer optimizer is based on bilevel single-objective optimization and aims to find a unique optimal Pareto solution rather than generate the whole Pareto frontier on the lower level in order to improve the optimization efficiency. The proposed bilevel DSD approach is verified on several test cases, and a relevant comparison against another classical approach is made. It is shown that the approach can generate a quasi-evenly distributed Pareto set for the upper level with relatively low time consumption.
THE TRAVELLING SALESMAN PROBLEM IN THE ENGINEERING EDUCATION PROGRAMMING CURRICULUM
Directory of Open Access Journals (Sweden)
Yevgeny Gayev
2017-11-01
Full Text Available Objective: To make students familiar with the famous Traveling Salesman Problem (TSP and suggest the latter to become a common exercise in engineering programming curriculum provided the students master computer science in the easy programming environment MATLAB. Methods: easy programming in MATLAB makes true such modern educational approach as “discovery based” methodology. Results: a MATLAB TSP-program oriented to Ukrainian map is suggested that allows to pictorially demonstrate the process of optimal route search with an option to decelerate or accelerate the demonstration. The program is guessed to be useful both for learning the TSP as one of fundamental logistics problems and as an intriguing programming curriculum excersize. Several sub-programs according to key stone Computer Science Curriculum have also been suggested. This lies in line with recent “discovery based” learning methodology. Discussion: we explain how to create this program for visual discrete optimization, suggest required subprograms belonging to key stone programming algorithms including rather modern graphical user interface (GUI, how to use this MATLAB TSP-program for demonstration the drastical grows of solution time required. Conclusions: easy programming being realized in MATLAB makes dificult curriculum problems attractive to students; it focuses them to main problem’ features, laws and algorithms implementing the “discovery based” methodology in such a way.
Formulated linear programming problems from game theory and its ...
African Journals Online (AJOL)
Formulated linear programming problems from game theory and its computer implementation using Tora package. ... Game theory, a branch of operations research examines the various concepts of decision ... AJOL African Journals Online.
Linear Programming and Its Application to Pattern Recognition Problems
Omalley, M. J.
1973-01-01
Linear programming and linear programming like techniques as applied to pattern recognition problems are discussed. Three relatively recent research articles on such applications are summarized. The main results of each paper are described, indicating the theoretical tools needed to obtain them. A synopsis of the author's comments is presented with regard to the applicability or non-applicability of his methods to particular problems, including computational results wherever given.
Dynamic Programming Approaches for the Traveling Salesman Problem with Drone
Bouman, Paul; Agatz, Niels; Schmidt, Marie
2017-01-01
markdownabstractA promising new delivery model involves the use of a delivery truck that collaborates with a drone to make deliveries. Effectively combining a drone and a truck gives rise to a new planning problem that is known as the Traveling Salesman Problem with Drone (TSP-D). This paper presents an exact solution approach for the TSP-D based on dynamic programming and present experimental results of different dynamic programming based heuristics. Our numerical experiments show that our a...
Emotion Oriented Programming: Computational Abstractions for AI Problem Solving
Darty , Kevin; Sabouret , Nicolas
2012-01-01
International audience; In this paper, we present a programming paradigm for AI problem solving based on computational concepts drawn from Affective Computing. It is believed that emotions participate in human adaptability and reactivity, in behaviour selection and in complex and dynamic environments. We propose to define a mechanism inspired from this observation for general AI problem solving. To this purpose, we synthesize emotions as programming abstractions that represent the perception ...
Logo Programming, Problem Solving, and Knowledge-Based Instruction.
Swan, Karen; Black, John B.
The research reported in this paper was designed to investigate the hypothesis that computer programming may support the teaching and learning of problem solving, but that to do so, problem solving must be explicitly taught. Three studies involved students in several grades: 4th, 6th, 8th, 11th, and 12th. Findings collectively show that five…
An approach for solving linear fractional programming problems ...
African Journals Online (AJOL)
The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebraically using the concept of duality ...
Some Competition Programming Problems as the Beginning of Artificial Intelligence
Boris MELNIKOV; Elena MELNIKOVA
2007-01-01
We consider in this paper some programming competition problems (which are near to some problems of ACM competitions) of the following subjects: we can make their solution using both Prolog and a classical procedure-oriented language. Moreover, the considered problems are selected that their solution in Prolog and in a classical procedure-oriented language are similar - i.e., in other words, they use the same working mechanism, the same approach to constructing recursive functions etc. Howeve...
Using Problem Solving to Teach a Programming Language.
Milbrandt, George
1995-01-01
Computer studies courses should incorporate as many computer concepts and programming language experiences as possible. A gradual increase in problem difficulty will help the student to understand various computer concepts, and the programming language's syntax and structure. A sidebar provides two examples of how to establish a learning…
Directory of Open Access Journals (Sweden)
Yan Bao
2018-01-01
Full Text Available Fast charging stations enable the high-powered rapid recharging of electric vehicles. However, these stations also face challenges due to power fluctuations, high peak loads, and low load factors, affecting the reliable and economic operation of charging stations and distribution networks. This paper introduces a battery energy storage system (BESS for charging load control, which is a more user-friendly approach and is more robust to perturbations. With the goals of peak-shaving, total electricity cost reduction, and minimization of variation in the state-of-charge (SOC range, a BESS-based bi-level optimization strategy for the charging load regulation of fast charging stations is proposed in this paper. At the first level, a day-ahead optimization strategy generates the optimal planned load curve and the deviation band to be used as a reference for ensuring multiple control objectives through linear programming, and even for avoiding control failure caused by insufficient BESS energy. Based on this day-ahead optimal plan, at a second level, real-time rolling optimization converts the control process to a multistage decision-making problem. The predictive control-based real-time rolling optimization strategy in the proposed model was used to achieve the above control objectives and maintain battery life. Finally, through a horizontal comparison of two control approaches in each case study, and a longitudinal comparison of the control robustness against different degrees of load disturbances in three cases, the results indicated that the proposed control strategy was able to significantly improve the charging load characteristics, even with large disturbances. Meanwhile, the proposed approach ensures the least amount of variation in the range of battery SOC and reduces the total electricity cost, which will be of a considerable benefit to station operators.
Linear decomposition approach for a class of nonconvex programming problems.
Shen, Peiping; Wang, Chunfeng
2017-01-01
This paper presents a linear decomposition approach for a class of nonconvex programming problems by dividing the input space into polynomially many grids. It shows that under certain assumptions the original problem can be transformed and decomposed into a polynomial number of equivalent linear programming subproblems. Based on solving a series of liner programming subproblems corresponding to those grid points we can obtain the near-optimal solution of the original problem. Compared to existing results in the literature, the proposed algorithm does not require the assumptions of quasi-concavity and differentiability of the objective function, and it differs significantly giving an interesting approach to solving the problem with a reduced running time.
A "feasible direction" search for Lineal Programming problem solving
Directory of Open Access Journals (Sweden)
Jaime U Malpica Angarita
2003-07-01
Full Text Available The study presents an approach to solve linear programming problems with no artificial variables. A primal linear minimization problem is standard form and its associated dual linear maximization problem are used. Initially, the dual (or a partial dual program is solved by a "feasible direction" search, where the Karush-Kuhn-Tucker conditions help to verify its optimality and then its feasibility. The "feasible direction" search exploits the characteristics of the convex polyhedron (or prototype formed by the dual program constraints to find a starting point and then follows line segments, whose directions are found in afine subspaces defined by boundary hyperplanes of polyhedral faces, to find next points up to the (an optimal one. Them, the remaining dual constraints not satisfaced at that optimal dual point, if there are any, are handled as nonbasic variables of the primal program, which is to be solved by such "feasible direction" search.
Bonus algorithm for large scale stochastic nonlinear programming problems
Diwekar, Urmila
2015-01-01
This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these ...
EZLP: An Interactive Computer Program for Solving Linear Programming Problems. Final Report.
Jarvis, John J.; And Others
Designed for student use in solving linear programming problems, the interactive computer program described (EZLP) permits the student to input the linear programming model in exactly the same manner in which it would be written on paper. This report includes a brief review of the development of EZLP; narrative descriptions of program features,…
An Improvement for Fuzzy Stochastic Goal Programming Problems
Directory of Open Access Journals (Sweden)
Shu-Cheng Lin
2017-01-01
Full Text Available We examined the solution process for linear programming problems under a fuzzy and random environment to transform fuzzy stochastic goal programming problems into standard linear programming problems. A previous paper that revised the solution process with the lower-side attainment index motivated our work. In this paper, we worked on a revision for both-side attainment index to amend its definition and theorems. Two previous examples were used to examine and demonstrate our improvement over previous results. Our findings not only improve the previous paper with both-side attainment index, but also provide a theoretical extension from lower-side attainment index to the both-side attainment index.
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...
Needs and Problems of Posbindu Program: Community Health Volunteers Perspective
Putri, S. T.; Andriyani, S.
2018-01-01
Posbindu is a form of public participation to conduct early detection and monitoring of risk factors for non-communicable diseases(NCD), and where it was carried out in as an integrated manner, routine and periodic event. This paper aims to investigates the needs and problems on Posbindu Program based on community health volunteers(CHVs) perspective. This study used descriptive qualitative method by open ended questions. Content analysis using to explicating the result. There are 3 theme finding about elderly needs in Posbindu; medical care, support group community, and health education. We found four theme problems which in Posbindu program: low motivation from elderly, Inadequate of facilities, physical disability, failed communication. To be effective in Posbindu program, all the stakeholders have reached consensus on the Posbindu program as elderly need. CHVs need given wide knowledge about early detection, daily care, control disease continuously so that the elderly keep feeling the advantages of coming to the Posbindu.
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
Energy Technology Data Exchange (ETDEWEB)
Hamadameen, Abdulqader Othman [Optimization, Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia); Zainuddin, Zaitul Marlizawati [Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia)
2014-06-19
This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.
Geometric Programming Approach to an Interactive Fuzzy Inventory Problem
Directory of Open Access Journals (Sweden)
Nirmal Kumar Mandal
2011-01-01
Full Text Available An interactive multiobjective fuzzy inventory problem with two resource constraints is presented in this paper. The cost parameters and index parameters, the storage space, the budgetary cost, and the objective and constraint goals are imprecise in nature. These parameters and objective goals are quantified by linear/nonlinear membership functions. A compromise solution is obtained by geometric programming method. If the decision maker is not satisfied with this result, he/she may try to update the current solution to his/her satisfactory solution. In this way we implement man-machine interactive procedure to solve the problem through geometric programming method.
A goal programming procedure for solving fuzzy multiobjective fractional linear programming problems
Directory of Open Access Journals (Sweden)
Tunjo Perić
2014-12-01
Full Text Available This paper presents a modification of Pal, Moitra and Maulik's goal programming procedure for fuzzy multiobjective linear fractional programming problem solving. The proposed modification of the method allows simpler solving of economic multiple objective fractional linear programming (MOFLP problems, enabling the obtained solutions to express the preferences of the decision maker defined by the objective function weights. The proposed method is tested on the production planning example.
Managing problem employees: a model program and practical guide.
Miller, Laurence
2010-01-01
This article presents a model program for managing problem employees that includes a description ofthe basic types of problem employees and employee problems, as well as practical recommendations for. (1) selection and screening, (2) education and training, (3) coaching and counseling, (4) discipline, (5) psychological fitness-for-duty evaluations, (6) mental health services, (7) termination, and (8) leadership and administrative strategies. Throughout, the emphasis on balancing the need for order and productivity in the workplace with fairness and concern for employee health and well-being.
Quantum algorithms for the ordered search problem via semidefinite programming
International Nuclear Information System (INIS)
Childs, Andrew M.; Landahl, Andrew J.; Parrilo, Pablo A.
2007-01-01
One of the most basic computational problems is the task of finding a desired item in an ordered list of N items. While the best classical algorithm for this problem uses log 2 N queries to the list, a quantum computer can solve the problem using a constant factor fewer queries. However, the precise value of this constant is unknown. By characterizing a class of quantum query algorithms for the ordered search problem in terms of a semidefinite program, we find quantum algorithms for small instances of the ordered search problem. Extending these algorithms to arbitrarily large instances using recursion, we show that there is an exact quantum ordered search algorithm using 4 log 605 N≅0.433 log 2 N queries, which improves upon the previously best known exact algorithm
A property of assignment type mixed integer linear programming problems
Benders, J.F.; van Nunen, J.A.E.E.
1982-01-01
In this paper we will proof that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linear programming relaxation of some types of mixed integer linear assignment problems. Since in these cases the number of splitted assignments is
Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems
Directory of Open Access Journals (Sweden)
Xinbo Zhang
2014-01-01
Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.
INTRODUCTION OF UNIVERSAL HEALTH PROGRAM IN GEORGIA: PROBLEMS AND PERSPECTIVES.
Verulava, T; Jorbenadze, R; Barkalaia, T
2017-01-01
Since 2013, Georgia enacted Universal Healthcare (UHC) program. Inclusion of uninsured population in the UHC program will have a positive impact on their financial accessibility to the health services. The study aims to analyze the referral rate of the beneficiaries to the health service providers before introduction and after application of the UHC program, particularly, how much it increased the recently uninsured population referral to primary health care units, and also to study the level of satisfaction with the UHC program. Research was conducted by qualitative and quantitative methods. The target groups' (program beneficiaries, physicians, personnel of the Social Service Agency) opinions were identified by means of face-to-face interviews. Enactment of the UHC programs significantly raised the population refferal to the family physicians, and the specialists. Insignificantly, but also increased the frequency of laboratory and diagnostic services. Despite the serious positive changes caused by UHC program implementation there still remain the problems in the primary healthcare system. Also, it is desirable to raise the financial availability of those medical services, which may cause catastrophic costs. In this respect, such medical services must be involved in the universal healthcare program and been expanded their scale. For the purpose of effective usage of the limited funds allocated for health care services provision, the private health insurance companies should be involved in UHC programs. This, together with the reduction of health care costs will increase a competition in the medical market, and enhance the quality of health service.
Solving seismological problems using sgraph program: II-waveform modeling
International Nuclear Information System (INIS)
Abdelwahed, Mohamed F.
2012-01-01
One of the seismological programs to manipulate seismic data is SGRAPH program. It consists of integrated tools to perform advanced seismological techniques. SGRAPH is considered a new system for maintaining and analyze seismic waveform data in a stand-alone Windows-based application that manipulate a wide range of data formats. SGRAPH was described in detail in the first part of this paper. In this part, I discuss the advanced techniques including in the program and its applications in seismology. Because of the numerous tools included in the program, only SGRAPH is sufficient to perform the basic waveform analysis and to solve advanced seismological problems. In the first part of this paper, the application of the source parameters estimation and hypocentral location was given. Here, I discuss SGRAPH waveform modeling tools. This paper exhibits examples of how to apply the SGRAPH tools to perform waveform modeling for estimating the focal mechanism and crustal structure of local earthquakes.
Stochastic programming problems with generalized integrated chance constraints
Czech Academy of Sciences Publication Activity Database
Branda, Martin
2012-01-01
Roč. 61, č. 8 (2012), s. 949-968 ISSN 0233-1934 R&D Projects: GA ČR GAP402/10/1610 Grant - others:SVV(CZ) 261315/2010 Institutional support: RVO:67985556 Keywords : chance constraints * integrated chance constraints * penalty functions * sample approximations * blending problem Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.707, year: 2012 http://library.utia.cas.cz/separaty/2012/E/branda-stochastic programming problems with generalized integrated.pdf
Optimality Conditions for Nondifferentiable Multiobjective Semi-Infinite Programming Problems
Directory of Open Access Journals (Sweden)
D. Barilla
2016-01-01
Full Text Available We have considered a multiobjective semi-infinite programming problem with a feasible set defined by inequality constraints. First we studied a Fritz-John type necessary condition. Then, we introduced two constraint qualifications and derive the weak and strong Karush-Kuhn-Tucker (KKT in brief types necessary conditions for an efficient solution of the considered problem. Finally an extension of a Caristi-Ferrara-Stefanescu result for the (Φ,ρ-invexity is proved, and some sufficient conditions are presented under this weak assumption. All results are given in terms of Clark subdifferential.
Lossless, Near-Lossless, and Refinement Coding of Bi-level Images
DEFF Research Database (Denmark)
Martins, Bo; Forchhammer, Søren Otto
1997-01-01
We present general and unified algorithms for lossy/lossless codingof bi-level images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template.For better compression, the more general....... Introducing only a small amount of loss in halftoned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG......-2, an emerging international standard for lossless/lossy compression of bi-level images....
Lossless, Near-Lossless, and Refinement Coding of Bi-level Images
DEFF Research Database (Denmark)
Martins, Bo; Forchhammer, Søren Otto
1999-01-01
We present general and unified algorithms for lossy/lossless coding of bi-level images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template.For better compression, the more general...... to the specialized soft pattern matching techniques which work better for text. Template based refinement coding is applied for lossy-to-lossless refinement. Introducing only a small amount of loss in halftoned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless......, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG2, an emerging international standard for lossless/lossy compression of bi-level images....
Some problems in the acceptability of implementing radiation protection programs
International Nuclear Information System (INIS)
Neill, R.H.
1997-01-01
The three fundamentals that radiation protection programs are based upon are; 1) establishing a quantitative correlation between radiation exposure and biological effects in people; 2) determining a level of acceptable risk of exposure; and 3) establishing systems to measure the radiation dose to insure compliance with the regulations or criteria. The paper discusses the interrelationship of these fundamentals, difficulties in obtaining a consensus of acceptable risk and gives some examples of problems in identifying the most critical population-at-risk and in measuring dose. Despite such problems, it is recommended that we proceed with the existing conservative structure of radiation protection programs based upon a linear no threshold model for low radiation doses to insure public acceptability of various potential radiation risks. Voluntary compliance as well as regulatory requirements should continue to be pursued to maintain minimal exposure to ionizing radiation. (author)
Relieving the Impact of Transit Signal Priority on Passenger Cars through a Bilevel Model
Directory of Open Access Journals (Sweden)
Ding Wang
2017-01-01
Full Text Available Transit signal priority (TSP is an effective control strategy to improve transit operations on the urban network. However, the TSP may sacrifice the right-of-way of vehicles from side streets which have only few transit vehicles; therefore, how to minimize the negative impact of TSP strategy on the side streets is an important issue to be addressed. Concerning the typical mixed-traffic flow pattern and heavy transit volume in China, a bilevel model is proposed in this paper: the upper-level model focused on minimizing the vehicle delay in the nonpriority direction while ensuring acceptable delay variation in transit priority direction, and the lower-level model aimed at minimizing the average passenger delay in the entire intersection. The parameters which will affect the efficiency of the bilevel model have been analyzed based on a hypothetical intersection. Finally, a real-world intersection has been studied, and the average vehicle delay in the nonpriority direction decreased 11.28 s and 22.54 s (under different delay variation constraint compared to the models that only minimize average passenger delay, while the vehicle delay in the priority direction increased only 1.37 s and 2.87 s; the results proved the practical applicability and efficiency of the proposed bilevel model.
A bilevel model for electricity retailers' participation in a demand response market environment
International Nuclear Information System (INIS)
Zugno, Marco; Morales, Juan Miguel; Pinson, Pierre; Madsen, Henrik
2013-01-01
Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility. - Highlights: ► We model the game between electricity retailers and consumers under dynamic pricing. ► The retailer cuts procurement costs by shifting demand in time via price-incentive. ► Imbalance costs for the retailer taper
Shen, Peiping; Zhang, Tongli; Wang, Chunfeng
2017-01-01
This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.
An outer approximation method for the road network design problem.
Asadi Bagloee, Saeed; Sarvi, Majid
2018-01-01
Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.
Motivating programming students by Problem Based Learning and LEGO robots
DEFF Research Database (Denmark)
Lykke, Marianne; Coto Chotto, Mayela; Mora, Sonia
2014-01-01
. For this reason the school is focusing on different teaching methods to help their students master these skills. This paper introduces an experimental, controlled comparison study of three learning designs, involving a problem based learning (PBL) approach in connection with the use of LEGO Mindstorms to improve...... students programming skills and motivation for learning in an introductory programming course. The paper reports the results related with one of the components of the study - the experiential qualities of the three learning designs. The data were collected through a questionnaire survey with 229 students...... from three groups exposed to different learning designs and through six qualitative walk-alongs collecting data from these groups by informal interviews and observations. Findings from the three studies were discussed in three focus group interviews with 10 students from the three experimental groups....
Solving cyclical nurse scheduling problem using preemptive goal programming
Sundari, V. E.; Mardiyati, S.
2017-07-01
Nurse scheduling system in a hospital is being modeled as a preemptive goal programming problem that is solved by using LINGO software with the objective function to minimize deviation variable at each goal. The scheduling is done cyclically, so every nurse is treated fairly since they have the same work shift portion with the other nurses. By paying attention to the hospital's rules regarding nursing work shift cyclically, it can be obtained that numbers of nurse needed in every ward are 18 nurses and the numbers of scheduling periods are 18 periods where every period consists of 21 days.
Directory of Open Access Journals (Sweden)
Ricardo Tera Akamine
2014-06-01
Bi-level positive airway pressure treatment at spontaneous/timed mode showed an improvement in snoring, apneas, and Epworth sleepiness scale decreased from 20 to 10. This case illustrates the beneficial effects of Bi-level positive airway pressure support in central sleep apnea syndrome of a patient with myotonic dystrophy type 1.
Kassa, Semu Mitiku; Tsegay, Teklay Hailay
2017-08-01
Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of problems. In this paper, we investigate a tri-level programming problem with quadratic fractional objective functions at each of the three levels. A solution algorithm has been proposed by applying fuzzy goal programming approach and by reformulating the fractional constraints to equivalent but non-fractional non-linear constraints. Based on the transformed formulation, an iterative procedure is developed that can yield a satisfactory solution to the tri-level problem. The numerical results on various illustrative examples demonstrated that the proposed algorithm is very much promising and it can also be used to solve larger-sized as well as n-level problems of similar structure.
The transportation management division institutional program: Networking and problem solving
International Nuclear Information System (INIS)
McGinnis, K.A.; Peterson, J.M.
1989-06-01
The US Department of Energy (DOE) has several programs related to transportation. While these programs may have differing missions and legislative authority, the required activities are frequently similar. To ensure a DOE-wide perspective in developing transportation policies and procedures, a DOE Transportation Institutional Task Force (Task Force) has been formed, which is the primary focus of this paper. The Task Force, composed of representatives from each of the major DOE transportation programs, meets periodically to exchange experiences and insights on institutional issues related to Departmental shipping. The primary purpose of the group is to identify opportunities for productive interactions with the transportation community, including interested and affected members of the public. This paper will also focus sharply on the networking of DOE with the State, Tribal, and local officials in fostering better understanding and in solving problems. An example of such activity is the DOE's cooperative agreement with the Energy Task Force of the Urban Consortium. A major effort is to encourage cooperative action in identifying, addressing, and resolving issues that could impede the transportation of radioactive materials
Theoretical and algorithmic advances in multi-parametric programming and control
Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar
2012-01-01
This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
Theoretical and algorithmic advances in multi-parametric programming and control
Pistikopoulos, Efstratios N.
2012-04-21
This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
A program package for solving linear optimization problems
International Nuclear Information System (INIS)
Horikami, Kunihiko; Fujimura, Toichiro; Nakahara, Yasuaki
1980-09-01
Seven computer programs for the solution of linear, integer and quadratic programming (four programs for linear programming, one for integer programming and two for quadratic programming) have been prepared and tested on FACOM M200 computer, and auxiliary programs have been written to make it easy to use the optimization program package. The characteristics of each program are explained and the detailed input/output descriptions are given in order to let users know how to use them. (author)
Problem area descriptions : motor vehicle crashes - data analysis and IVI program analysis
In general, the IVI program focuses on the more significant safety problem categories as : indicated by statistical analyses of crash data. However, other factors were considered in setting : program priorities and schedules. For some problem areas, ...
Directory of Open Access Journals (Sweden)
Renata Melo e Silva de Oliveira
2015-03-01
Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests. With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs. The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.
Carlucci, Annalisa; Ceriana, Piero; Mancini, Marco; Cirio, Serena; Pierucci, Paola; D'Artavilla Lupo, Nadia; Gadaleta, Felice; Morrone, Elisa; Fanfulla, Francesco
2015-09-15
Ventilation with continuous positive airway pressure (CPAP) is the gold standard therapy for obstructive sleep apnea (OSA). However, it was recently suggested that a novel mode of ventilation, Bilevel-auto, could be equally effective in treating patients unable to tolerate CPAP. The aim of this study was to investigate the ability of Bilevel-auto to treat OSA patients whose nocturnal ventilatory disturbances are not completely corrected by CPAP. We enrolled 66 consecutive OSA patients, not responsive to (group A) or intolerant of (group B) CPAP treatment, after a full night of manual CPAP titration in a laboratory. Full polysomnography data and daytime sleepiness score were compared for each group in the three different conditions: basal, during CPAP, and during Bilevel-auto. The apnea-hypopnea index decreased significantly during CPAP in both groups; however, in the group A, there was a further significant improvement during Bilevel-auto. The same trend was observed for oxygenation indices, while the distribution and the efficiency of sleep did not differ following the switch from CPAP to Bilevel-auto. This study confirmed the role of Bilevel-auto as an effective therapeutic alternative to CPAP in patients intolerant of this latter mode of ventilation. Moreover, extending the use of Bilevel-auto to those OSA patients not responsive to CPAP, we showed a significantly better correction of nocturnal respiratory disturbances. © 2015 American Academy of Sleep Medicine.
Bricolage Programming and Problem Solving Ability in Young Children : an Exploratory Study
Rose, Simon
2016-01-01
Visual programming environments, such as Scratch, are increasingly being used by schools to teach problem solving and computational thinking skills. However, academic research is divided on the effect that visual programming has on problem solving in a computational context. This paper focuses on the role of bricolage programming in this debate; a bottom-up programming approach that arises when using block-style programming interfaces. Bricolage programming was a term originally used to descr...
A Linear Programming Reformulation of the Standard Quadratic Optimization Problem
de Klerk, E.; Pasechnik, D.V.
2005-01-01
The problem of minimizing a quadratic form over the standard simplex is known as the standard quadratic optimization problem (SQO).It is NPhard, and contains the maximum stable set problem in graphs as a special case.In this note we show that the SQO problem may be reformulated as an (exponentially
Weather is the main driver in both plant use of nutrients and fate and transport of nutrients in the environment. In previous work, we evaluated a green tax for control of agricultural nutrients in a bi-level optimization framework that linked deterministic models. In this study,...
DEFF Research Database (Denmark)
Boroojeni, Kianoosh; Amini, M. Hadi; Nejadpak, Arash
2016-01-01
In this paper, we present a bilevel control framework to achieve a highly-reliable smart distribution network with large-scale penetration of distributed renewable resources (DRRs). We assume that the power distribution network consists of several residential/commercial communities. In the first ...
Lachhwani, Kailash; Poonia, Mahaveer Prasad
2012-08-01
In this paper, we show a procedure for solving multilevel fractional programming problems in a large hierarchical decentralized organization using fuzzy goal programming approach. In the proposed method, the tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels as well as the control vectors of the higher level decision makers are respectively defined by determining individual optimal solutions of each of the level decision makers. A possible relaxation of the higher level decision is considered for avoiding decision deadlock due to the conflicting nature of objective functions. Then, fuzzy goal programming approach is used for achieving the highest degree of each of the membership goal by minimizing negative deviational variables. We also provide sensitivity analysis with variation of tolerance values on decision vectors to show how the solution is sensitive to the change of tolerance values with the help of a numerical example.
Tunjo Perić; Željko Mandić
2017-01-01
This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method) in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained resul...
Teaching Introductory Programming to IS Students: Java Problems and Pitfalls
Pendergast, Mark O.
2006-01-01
This paper examines the impact the use of the Java programming language has had on the way our students learn to program and the success they achieve. The importance of a properly constructed first course in programming cannot be overstated. A course well experienced will leave students with good programming habits, the ability to learn on their…
Nourifar, Raheleh; Mahdavi, Iraj; Mahdavi-Amiri, Nezam; Paydar, Mohammad Mahdi
2017-09-01
Decentralized supply chain management is found to be significantly relevant in today's competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem's convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy approach and chance constraint approach. Ultimately, a numerical example is constructed and worked through to demonstrate applicability of the optimization model. A sensitivity analysis is also made.
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.
34 CFR 356.11 - What types of problems may be researched under the fellowship program?
2010-07-01
... 34 Education 2 2010-07-01 2010-07-01 false What types of problems may be researched under the... (Continued) OFFICE OF SPECIAL EDUCATION AND REHABILITATIVE SERVICES, DEPARTMENT OF EDUCATION DISABILITY AND... Program? § 356.11 What types of problems may be researched under the fellowship program? Problems...
Zörnig, Peter
2015-08-01
We present integer programming models for some variants of the farthest string problem. The number of variables and constraints is substantially less than that of the integer linear programming models known in the literature. Moreover, the solution of the linear programming-relaxation contains only a small proportion of noninteger values, which considerably simplifies the rounding process. Numerical tests have shown excellent results, especially when a small set of long sequences is given.
COYOTE: a finite element computer program for nonlinear heat conduction problems
International Nuclear Information System (INIS)
Gartling, D.K.
1978-06-01
COYOTE is a finite element computer program designed for the solution of two-dimensional, nonlinear heat conduction problems. The theoretical and mathematical basis used to develop the code is described. Program capabilities and complete user instructions are presented. Several example problems are described in detail to demonstrate the use of the program
Sitek, Paweł; Wikarek, Jarosław
2016-01-01
This paper proposes a hybrid programming framework for modeling and solving of constraint satisfaction problems (CSPs) and constraint optimization problems (COPs). Two paradigms, CLP (constraint logic programming) and MP (mathematical programming), are integrated in the framework. The integration is supplemented with the original method of problem transformation, used in the framework as a presolving method. The transformation substantially reduces the feasible solution space. The framework a...
de Klerk, E.; Sotirov, R.
2007-01-01
We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard,
CSR, Inc., Washington, DC.
This handbook is for administrators of programs in higher education settings which deal with alcohol and other drug (AOD) related problems. Chapter 1, "Defining the Problem, Issues, and Trends" examines the problem from various perspectives and presents the latest statistics on the extent of AOD use on campuses, specific problems affecting…
Bi-Level Decentralized Active Power Control for Large-Scale Wind Farm Cluster
DEFF Research Database (Denmark)
Huang, Shengli; Wu, Qiuwei; Guo, Yifei
2018-01-01
This paper presents a bi-level decentralized active power control (DAPC) for a large-scale wind farm cluster, consisting of several wind farms for better active power dispatch. In the upper level, a distributed active power control scheme based on the distributed consensus is designed to achieve...... fair active power sharing among multiple wind farms, which generates the power reference for each wind farm. A distributed estimator is used to estimate the total available power of all wind farms. In the lower level, a centralized control scheme based on the Model Predictive Control (MPC) is proposed...... to regulate active power outputs of all wind turbines (WTs) within a wind farm, which reduces the fatigue loads of WTs while tracking the power reference obtained from the upper level control. A wind farm cluster with 8 wind farms and totally 160 WTs, was used to test the control performance of the proposed...
A Bilevel Model for Participation of a Storage System in Energy and Reserve Markets
DEFF Research Database (Denmark)
Nasrolahpour, Ehsan; Kazempour, Jalal; Zareipour, Hamidreza
2017-01-01
We develop a decision-making tool based on a bilevel complementarity model for a merchant price-maker energy storage system to determine the most beneficial trading actions in pool-based markets, including day-ahead (as joint energy and reserve markets) and balancing settlements. The uncertainty...... of net load deviation in real-time is incorporated into the model using a set of scenarios generated from the available forecast in the day-ahead. The objective of this energy storage system is to maximize its expected profit. The day-ahead products of energy storage system include energy as well...... system into clearing process of multiple markets and enables such a facility to possibly affect the outcomes of those markets to its own benefit through strategic price and quantity offers. The validity of the proposed approach is evaluated using a numerical study....
Bilevel Optimization for Scene Segmentation of LiDAR Point Cloud
Directory of Open Access Journals (Sweden)
LI Minglei
2018-02-01
Full Text Available The segmentation of point clouds obtained by light detection and ranging (LiDAR systems is a critical step for many tasks,such as data organization,reconstruction and information extraction.In this paper,we propose a bilevel progressive optimization algorithm based on the local differentiability.First,we define the topological relation and distance metric of points in the framework of Riemannian geometry,and in the point-based level using k-means method generates over-segmentation results,e.g.super voxels.Then these voxels are formulated as nodes which consist a minimal spanning tree.High level features are extracted from voxel structures,and a graph-based optimization method is designed to yield the final adaptive segmentation results.The implementation experiments on real data demonstrate that our method is efficient and superior to state-of-the-art methods.
AutoBD: Automated Bi-Level Description for Scalable Fine-Grained Visual Categorization.
Yao, Hantao; Zhang, Shiliang; Yan, Chenggang; Zhang, Yongdong; Li, Jintao; Tian, Qi
Compared with traditional image classification, fine-grained visual categorization is a more challenging task, because it targets to classify objects belonging to the same species, e.g. , classify hundreds of birds or cars. In the past several years, researchers have made many achievements on this topic. However, most of them are heavily dependent on the artificial annotations, e.g., bounding boxes, part annotations, and so on . The requirement of artificial annotations largely hinders the scalability and application. Motivated to release such dependence, this paper proposes a robust and discriminative visual description named Automated Bi-level Description (AutoBD). "Bi-level" denotes two complementary part-level and object-level visual descriptions, respectively. AutoBD is "automated," because it only requires the image-level labels of training images and does not need any annotations for testing images. Compared with the part annotations labeled by the human, the image-level labels can be easily acquired, which thus makes AutoBD suitable for large-scale visual categorization. Specifically, the part-level description is extracted by identifying the local region saliently representing the visual distinctiveness. The object-level description is extracted from object bounding boxes generated with a co-localization algorithm. Although only using the image-level labels, AutoBD outperforms the recent studies on two public benchmark, i.e. , classification accuracy achieves 81.6% on CUB-200-2011 and 88.9% on Car-196, respectively. On the large-scale Birdsnap data set, AutoBD achieves the accuracy of 68%, which is currently the best performance to the best of our knowledge.Compared with traditional image classification, fine-grained visual categorization is a more challenging task, because it targets to classify objects belonging to the same species, e.g. , classify hundreds of birds or cars. In the past several years, researchers have made many achievements on this topic
A Low-Carbon-Based Bilevel Optimization Model for Public Transit Network
Directory of Open Access Journals (Sweden)
Xu Sun
2013-01-01
Full Text Available To satisfy the demand of low-carbon transportation, this paper studies the optimization of public transit network based on the concept of low carbon. Taking travel time, operation cost, energy consumption, pollutant emission, and traffic efficiency as the optimization objectives, a bilevel model is proposed in order to maximize the benefits of both travelers and operators and minimize the environmental cost. Then the model is solved with the differential evolution (DE algorithm and applied to a real network of Baoji city. The results show that the model can not only ensure the benefits of travelers and operators, but can also reduce pollutant emission and energy consumption caused by the operations of buses, which reflects the concept of low carbon.
Portfolio selection problem: a comparison of fuzzy goal programming and linear physical programming
Directory of Open Access Journals (Sweden)
Fusun Kucukbay
2016-04-01
Full Text Available Investors have limited budget and they try to maximize their return with minimum risk. Therefore this study aims to deal with the portfolio selection problem. In the study two criteria are considered which are expected return, and risk. In this respect, linear physical programming (LPP technique is applied on Bist 100 stocks to be able to find out the optimum portfolio. The analysis covers the period April 2009- March 2015. This period is divided into two; April 2009-March 2014 and April 2014 – March 2015. April 2009-March 2014 period is used as data to find an optimal solution. April 2014-March 2015 period is used to test the real performance of portfolios. The performance of the obtained portfolio is compared with that obtained from fuzzy goal programming (FGP. Then the performances of both method, LPP and FGP are compared with BIST 100 in terms of their Sharpe Indexes. The findings reveal that LPP for portfolio selection problem is a good alternative to FGP.
Specific problems of beginners at study of programming and possibilities of their solution
Procházková, Petra
2017-01-01
This thesis deals with the problems of beginners in the study of programming at University of Economics in Prague, Faculty of Informatics and Statistics. This applies particularly to students who are studying the subject Programming in Java.
Dynamic Programming Approaches for the Traveling Salesman Problem with Drone
P. Bouman (Paul); N.A.H. Agatz (Niels); M.E. Schmidt (Marie)
2017-01-01
markdownabstractA promising new delivery model involves the use of a delivery truck that collaborates with a drone to make deliveries. Effectively combining a drone and a truck gives rise to a new planning problem that is known as the Traveling Salesman Problem with Drone (TSP-D). This paper
Dynamic Programming Approaches for the Traveling Salesman Problem with Drone
P. Bouman (Paul); N.A.H. Agatz (Niels); M.E. Schmidt (Marie)
2017-01-01
markdownabstractA promising new delivery model involves the use of a delivery truck that collaborates with a drone to make deliveries. Effectively combining a truck and a drone gives rise to a new planning problem that is known as the Traveling Salesman Problem with Drone (TSP-D). This paper
Directory of Open Access Journals (Sweden)
Tunjo Perić
2017-09-01
Full Text Available This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained results indicate a high efficiency of the applied methods in solving the problem.
Zhao, Yingfeng; Liu, Sanyang
2016-01-01
We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.
Ferreira, Juliana C; Chipman, Daniel W; Hill, Nicholas S; Kacmarek, Robert M
2009-08-01
Noninvasive positive-pressure ventilation (NPPV) modes are currently available on bilevel and ICU ventilators. However, little data comparing the performance of the NPPV modes on these ventilators are available. In an experimental bench study, the ability of nine ICU ventilators to function in the presence of leaks was compared with a bilevel ventilator using the IngMar ASL5000 lung simulator (IngMar Medical; Pittsburgh, PA) set at a compliance of 60 mL/cm H(2)O, an inspiratory resistance of 10 cm H(2)O/L/s, an expiratory resistance of 20 cm H(2)O/ L/s, and a respiratory rate of 15 breaths/min. All of the ventilators were set at 12 cm H(2)O pressure support and 5 cm H(2)O positive end-expiratory pressure. The data were collected at baseline and at three customized leaks. At baseline, all of the ventilators were able to deliver adequate tidal volumes, to maintain airway pressure, and to synchronize with the simulator, without missed efforts or auto-triggering. As the leak was increased, all of the ventilators (except the Vision [Respironics; Murrysville, PA] and Servo I [Maquet; Solna, Sweden]) needed adjustment of sensitivity or cycling criteria to maintain adequate ventilation, and some transitioned to backup ventilation. Significant differences in triggering and cycling were observed between the Servo I and the Vision ventilators. The Vision and Servo I were the only ventilators that required no adjustments as they adapted to increasing leaks. There were differences in performance between these two ventilators, although the clinical significance of these differences is unclear. Clinicians should be aware that in the presence of leaks, most ICU ventilators require adjustments to maintain an adequate tidal volume.
A novel bi-level meta-analysis approach: applied to biological pathway analysis.
Nguyen, Tin; Tagett, Rebecca; Donato, Michele; Mitrea, Cristina; Draghici, Sorin
2016-02-01
The accumulation of high-throughput data in public repositories creates a pressing need for integrative analysis of multiple datasets from independent experiments. However, study heterogeneity, study bias, outliers and the lack of power of available methods present real challenge in integrating genomic data. One practical drawback of many P-value-based meta-analysis methods, including Fisher's, Stouffer's, minP and maxP, is that they are sensitive to outliers. Another drawback is that, because they perform just one statistical test for each individual experiment, they may not fully exploit the potentially large number of samples within each study. We propose a novel bi-level meta-analysis approach that employs the additive method and the Central Limit Theorem within each individual experiment and also across multiple experiments. We prove that the bi-level framework is robust against bias, less sensitive to outliers than other methods, and more sensitive to small changes in signal. For comparative analysis, we demonstrate that the intra-experiment analysis has more power than the equivalent statistical test performed on a single large experiment. For pathway analysis, we compare the proposed framework versus classical meta-analysis approaches (Fisher's, Stouffer's and the additive method) as well as against a dedicated pathway meta-analysis package (MetaPath), using 1252 samples from 21 datasets related to three human diseases, acute myeloid leukemia (9 datasets), type II diabetes (5 datasets) and Alzheimer's disease (7 datasets). Our framework outperforms its competitors to correctly identify pathways relevant to the phenotypes. The framework is sufficiently general to be applied to any type of statistical meta-analysis. The R scripts are available on demand from the authors. sorin@wayne.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e
TRUMP3-JR: a finite difference computer program for nonlinear heat conduction problems
International Nuclear Information System (INIS)
Ikushima, Takeshi
1984-02-01
Computer program TRUMP3-JR is a revised version of TRUMP3 which is a finite difference computer program used for the solution of multi-dimensional nonlinear heat conduction problems. Pre- and post-processings for input data generation and graphical representations of calculation results of TRUMP3 are avaiable in TRUMP3-JR. The calculation equations, program descriptions and user's instruction are presented. A sample problem is described to demonstrate the use of the program. (author)
Improvement of DC Optimal Power Flow Problem Based on Nodal Approximation of Transmission Losses
Directory of Open Access Journals (Sweden)
M. R. Baghayipour
2012-03-01
3-\tIts formulation is simple and easy to understand. Moreover, it can simply be realized in the form of Lagrange representation, makes it possible to be considered as some constraints in the body of any bi-level optimization problem, with its internal level including the OPF problem satisfaction.
Dijkstra's interpretation of the approach to solving a problem of program correctness
Directory of Open Access Journals (Sweden)
Markoski Branko
2010-01-01
Full Text Available Proving the program correctness and designing the correct programs are two connected theoretical problems, which are of great practical importance. The first is solved within program analysis, and the second one in program synthesis, although intertwining of these two processes is often due to connection between the analysis and synthesis of programs. Nevertheless, having in mind the automated methods of proving correctness and methods of automatic program synthesis, the difference is easy to tell. This paper presents denotative interpretation of programming calculation explaining semantics by formulae φ and ψ, in such a way that they can be used for defining state sets for program P.
SOLUTION OF A MULTIVARIATE STRATIFIED SAMPLING PROBLEM THROUGH CHEBYSHEV GOAL PROGRAMMING
Directory of Open Access Journals (Sweden)
Mohd. Vaseem Ismail
2010-12-01
Full Text Available In this paper, we consider the problem of minimizing the variances for the various characters with fixed (given budget. Each convex objective function is first linearised at its minimal point where it meets the linear cost constraint. The resulting multiobjective linear programming problem is then solved by Chebyshev goal programming. A numerical example is given to illustrate the procedure.
Stacked Deck: An Effective, School-Based Program for the Prevention of Problem Gambling
Williams, Robert J.; Wood, Robert T.; Currie, Shawn R.
2010-01-01
School-based prevention programs are an important component of problem gambling prevention, but empirically effective programs are lacking. Stacked Deck is a set of 5-6 interactive lessons that teach about the history of gambling; the true odds and "house edge"; gambling fallacies; signs, risk factors, and causes of problem gambling; and…
Developing Student Programming and Problem-Solving Skills with Visual Basic
Siegle, Del
2009-01-01
Although most computer users will never need to write a computer program, many students enjoy the challenge of creating one. Computer programming enhances students' problem solving by forcing students to break a problem into its component pieces and reassemble it in a generic format that can be understood by a nonsentient entity. It promotes…
Sensitivity analysis of linear programming problem through a recurrent neural network
Das, Raja
2017-11-01
In this paper we study the recurrent neural network for solving linear programming problems. To achieve optimality in accuracy and also in computational effort, an algorithm is presented. We investigate the sensitivity analysis of linear programming problem through the neural network. A detailed example is also presented to demonstrate the performance of the recurrent neural network.
Fundamental solution of the problem of linear programming and method of its determination
Petrunin, S. V.
1978-01-01
The idea of a fundamental solution to a problem in linear programming is introduced. A method of determining the fundamental solution and of applying this method to the solution of a problem in linear programming is proposed. Numerical examples are cited.
Zhang, Li; Wang, Lei; He, Jian-Jun
2009-09-01
A novel design of monolithically integrated diplexers and triplexers for fiber-to-the-home applications is presented. A bilevel etched asymmetrical 2 x 2 optical coupler is analyzed for efficient couplings of both upstream and downstream signals. The design of the diplexer is extended to a triplexer by adding an etched diffraction grating as an additional downstream demultiplexing element. The total size of the integrated diplexer and triplexer is smaller than 500 microm x 500 microm.
The Coin Problem and Pseudorandomness for Branching Programs
DEFF Research Database (Denmark)
Brody, Joshua; Verbin, Elad
2010-01-01
in the model of emph{read-once width-$w$ branching programs}. We prove that in order to succeed in this model, $beta$ must be at least $1/ (log n)^{Theta(w)}$. For constant $w$ this is tight by considering the recursive tribes function, and for other values of $w$ this is nearly tight by considering other read...... be distinguished by small-width read-once branching programs. We suggest one application for this kind of theorems: we prove that Nisan's Generator fools width-$w$ read-once emph{regular} branching programs, using seed length $O(w^4 log n log log n + log n log (1/eps))$. For $w=eps=Theta(1)$, this seed length...
Optimal Design of Gradient Materials and Bi-Level Optimization of Topology Using Targets (BOTT)
Garland, Anthony
of gradient material designs. A macroscopic gradient can be achieved by varying the microstructure or the mesostructures of an object. The mesostructure interpretation allows for more design freedom since the mesostructures can be tuned to have non-isotropic material properties. A new algorithm called Bi-level Optimization of Topology using Targets (BOTT) seeks to find the best distribution of mesostructure designs throughout a single object in order to minimize an objective value. On the macro level, the BOTT algorithm optimizes the macro topology and gradient material properties within the object. The BOTT algorithm optimizes the material gradient by finding the best constitutive matrix at each location with the object. In order to enhance the likelihood that a mesostructure can be generated with the same equivalent constitutive matrix, the variability of the constitutive matrix is constrained to be an orthotropic material. The stiffness in the X and Y directions (of the base coordinate system) can change in addition to rotating the orthotropic material to align with the loading at each region. Second, the BOTT algorithm designs mesostructures with macroscopic properties equal to the target properties found in step one while at the same time the algorithm seeks to minimize material usage in each mesostructure. The mesostructure algorithm maximizes the strain energy of the mesostructures unit cell when a pseudo strain is applied to the cell. A set of experiments reveals the fundamental relationship between target cell density and the strain (or pseudo strain) applied to a unit cell and the output effective properties of the mesostructure. At low density, a few mesostructure unit cell design are possible, while at higher density the mesostructure unit cell designs have many possibilities. Therefore, at low densities the effective properties of the mesostructure are a step function of the applied pseudo strain. At high densities, the effective properties of the
Energy Technology Data Exchange (ETDEWEB)
Blumstein, Carl (Univ. of California, Energy Institute (United States))
2009-07-01
This paper addresses the nexus between the evaluation of energy-efficiency programs and incentive payments based on performance for program administrators in California. The paper describes problems that arise when evaluators are asked to measure program performance by answering the counterfactual question, what would have happened in the absence of the program? Then some ways of addressing these problems are examined. Key conclusions are that 1) program evaluation cannot precisely and accurately determine the counterfactual, there will always be substantial uncertainty, 2) given the current state of knowledge, the decision to tie all of the incentive to program outcomes is misguided, and 3) incentive programs should be regularly reviewed and revised so that they can be adapted to new conditions.
Energy Technology Data Exchange (ETDEWEB)
Blumstein, Carl, E-mail: blumstei@berkeley.ed [University of California Energy Institute, 2547 Channing Way, Berkeley, CA 94720 (United States)
2010-10-15
This paper addresses the nexus between evaluation of energy-efficiency programs and incentive payments based on performance for program administrators in California. The paper describes the problems that arise when evaluators are asked to measure program performance by answering the counterfactual question-what would have happened in the absence of the program? Then the paper examines some ways of addressing these problems. Key conclusions are (1) program evaluation cannot precisely and accurately determine the counterfactual, there will always be substantial uncertainty, (2) given the current state of knowledge, the decision to tie all incentives to program outcomes is misguided, and (3) incentive programs should be regularly reviewed and revised so that they can be adapted to new conditions.
Energy Technology Data Exchange (ETDEWEB)
Blumstein, Carl [University of California Energy Institute, 2547 Channing Way, Berkeley, CA 94720 (United States)
2010-10-15
This paper addresses the nexus between evaluation of energy-efficiency programs and incentive payments based on performance for program administrators in California. The paper describes the problems that arise when evaluators are asked to measure program performance by answering the counterfactual question - what would have happened in the absence of the program? Then the paper examines some ways of addressing these problems. Key conclusions are (1) program evaluation cannot precisely and accurately determine the counterfactual, there will always be substantial uncertainty, (2) given the current state of knowledge, the decision to tie all incentives to program outcomes is misguided, and (3) incentive programs should be regularly reviewed and revised so that they can be adapted to new conditions. (author)
International Nuclear Information System (INIS)
Blumstein, Carl
2010-01-01
This paper addresses the nexus between evaluation of energy-efficiency programs and incentive payments based on performance for program administrators in California. The paper describes the problems that arise when evaluators are asked to measure program performance by answering the counterfactual question-what would have happened in the absence of the program? Then the paper examines some ways of addressing these problems. Key conclusions are (1) program evaluation cannot precisely and accurately determine the counterfactual, there will always be substantial uncertainty, (2) given the current state of knowledge, the decision to tie all incentives to program outcomes is misguided, and (3) incentive programs should be regularly reviewed and revised so that they can be adapted to new conditions.
Fietze, Ingo; Blau, Alexander; Glos, Martin; Theres, Heinz; Baumann, Gert; Penzel, Thomas
2008-08-01
Nocturnal positive pressure ventilation (PPV) has been shown to be effective in patients with impaired left ventricular ejection fraction (LVEF) and Cheyne-Stokes respiration (CSR). We investigated the effect of a bi-level PPV and adaptive servo ventilation on LVEF, CSR, and quantitative sleep quality. Thirty-seven patients (New York heart association [NYHA] II-III) with LVEFCSR were investigated by electrocardiography (ECG), echocardiography and polysomnography. The CSR index (CSRI) was 32.3+/-16.2/h. Patients were randomly treated with bi-level PPV using the standard spontaneous/timed (S/T) mode or with adaptive servo ventilation mode (AutoSetCS). After 6 weeks, 30 patients underwent control investigations with ECG, echocardiography, and polysomnography. The CSRI decreased significantly to 13.6+/-13.4/h. LVEF increased significantly after 6 weeks of ventilation (from 25.1+/-8.5 to 28.8+/-9.8%, plevel PPV and adaptive servo ventilation: the CSRI decreased more in the AutoSetCS group while the LVEF increased more in the bi-level PPV group. Administration of PPV can successfully attenuate CSA. Reduced CSA may be associated with improved LVEF; however, this may depend on the mode of PPV. Changed LVEF is evident even in the absence of significant changes in blood pressure.
Integer programming for the generalized high school timetabling problem
DEFF Research Database (Denmark)
Kristiansen, Simon; Sørensen, Matias; Stidsen, Thomas Riis
2015-01-01
, the XHSTT format serves as a common ground for researchers within this area. This paper describes the first exact method capable of handling an arbitrary instance of the XHSTT format. The method is based on a mixed-integer linear programming (MIP) model, which is solved in two steps with a commercial...
Using metrics in stability of stochastic programming problems
Czech Academy of Sciences Publication Activity Database
Houda, Michal
2005-01-01
Roč. 13, č. 1 (2005), s. 128-134 ISSN 0572-3043 R&D Projects: GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : stochastic programming * quantitative stability * Wasserstein metrics * Kolmogorov metrics * simulation study Subject RIV: BB - Applied Statistics, Operational Research
Method for solving fully fuzzy linear programming problems using deviation degree measure
Institute of Scientific and Technical Information of China (English)
Haifang Cheng; Weilai Huang; Jianhu Cai
2013-01-01
A new ful y fuzzy linear programming (FFLP) prob-lem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crispδ-parametric linear programming (LP) problem. Giving the value of deviation degree in each constraint, the δ-fuzzy optimal so-lution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict: to improve the va-lues of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to il ustrate the proposed method.
A new neural network model for solving random interval linear programming problems.
Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza
2017-05-01
This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.
DESIGN OF EDUCATIONAL PROBLEMS ON LINEAR PROGRAMMING USING SYSTEMS OF COMPUTER MATHEMATICS
Directory of Open Access Journals (Sweden)
Volodymyr M. Mykhalevych
2013-11-01
Full Text Available From a perspective of the theory of educational problems a problem of substitution in the conditions of ICT use of one discipline by an educational problem of another discipline is represented. Through the example of mathematical problems of linear programming it is showed that a student’s method of operation in the course of an educational problem solving is determinant in the identification of an educational problem in relation to a specific discipline: linear programming, informatics, mathematical modeling, methods of optimization, automatic control theory, calculus etc. It is substantiated the necessity of linear programming educational problems renovation with the purpose of making students free of bulky similar arithmetic calculations and notes which often becomes a barrier to a deeper understanding of key ideas taken as a basis of algorithms used by them.
Chen, Chiu-Jung; Liu, Pei-Lin
2007-01-01
This study evaluated the effects of a personalized computer-assisted mathematics problem-solving program on the performance and attitude of Taiwanese fourth grade students. The purpose of this study was to determine whether the personalized computer-assisted program improved student performance and attitude over the nonpersonalized program.…
How Does Early Feedback in an Online Programming Course Change Problem Solving?
Ebrahimi, Alireza
2012-01-01
How does early feedback change the programming problem solving in an online environment and help students choose correct approaches? This study was conducted in a sample of students learning programming in an online course entitled Introduction to C++ and OOP (Object Oriented Programming) using the ANGEL learning management system platform. My…
Depandent samples in empirical estimation of stochastic programming problems
Czech Academy of Sciences Publication Activity Database
Kaňková, Vlasta; Houda, Michal
2006-01-01
Roč. 35, 2/3 (2006), s. 271-279 ISSN 1026-597X R&D Projects: GA ČR GA402/04/1294; GA ČR GD402/03/H057; GA ČR GA402/05/0115 Institutional research plan: CEZ:AV0Z10750506 Keywords : stochastic programming * stability * probability metrics * Wasserstein metric * Kolmogorov metric * simulations Subject RIV: BB - Applied Statistics , Operational Research
Probabilistic Quadratic Programming Problems with Some Fuzzy Parameters
Directory of Open Access Journals (Sweden)
S. K. Barik
2012-01-01
making problem by using some specified random variables and fuzzy numbers. In the present paper, randomness is characterized by Weibull random variables and fuzziness is characterized by triangular and trapezoidal fuzzy number. A defuzzification method has been introduced for finding the crisp values of the fuzzy numbers using the proportional probability density function associated with the membership functions of these fuzzy numbers. An equivalent deterministic crisp model has been established in order to solve the proposed model. Finally, a numerical example is presented to illustrate the solution procedure.
An introduction to fuzzy linear programming problems theory, methods and applications
Kaur, Jagdeep
2016-01-01
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
Directory of Open Access Journals (Sweden)
Weihua Jin
2013-01-01
Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com [Laboratoire de Probabilités et Modèles Aléatoires, CNRS, UMR 7599, Université Paris Diderot (France)
2016-12-15
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
International Nuclear Information System (INIS)
Pham, Huyên; Wei, Xiaoli
2016-01-01
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
Directory of Open Access Journals (Sweden)
M.S. Osman
2018-03-01
Full Text Available In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997. In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.
Bruhn, Peter; Geyer-Schulz, Andreas
2002-01-01
In this paper, we introduce genetic programming over context-free languages with linear constraints for combinatorial optimization, apply this method to several variants of the multidimensional knapsack problem, and discuss its performance relative to Michalewicz's genetic algorithm with penalty functions. With respect to Michalewicz's approach, we demonstrate that genetic programming over context-free languages with linear constraints improves convergence. A final result is that genetic programming over context-free languages with linear constraints is ideally suited to modeling complementarities between items in a knapsack problem: The more complementarities in the problem, the stronger the performance in comparison to its competitors.
Nonlinear programming for classification problems in machine learning
Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio
2016-10-01
We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.
Vocal problems among teachers: evaluation of a preventive voice program.
Bovo, Roberto; Galceran, Marta; Petruccelli, Joseph; Hatzopoulos, Stavros
2007-11-01
Vocal education programs for teachers may prevent the emergence of vocal disorders; however, only a few studies have tried to evaluate the effectiveness of these preventive programs, particularly in the long term. Two hundred and sixty-four subjects, mostly kindergarten and primary school female teachers, participated in a course on voice care, including a theoretical seminar (120 minutes) and a short voice group therapy (180 minutes, small groups of 20 subjects). For 3 months, they had to either attend the vocal ergonomics norms and, as psychological reinforcement, they had to make out a daily report of vocal abuse, or to follow the given exercises for a more efficient vocal technique, reporting on whether the time scheduled was respected or not. The effectiveness of the course was assessed in a group of 21 female teachers through a randomized controlled study. Evaluation comprehended stroboscopy, perceptual and electro-acoustical voice analysis, Voice Handicap Index, and a course benefit questionnaire. A group of 20 teachers matched for age, working years, hoarseness grade, and vocal demand served as a control group. At 3 months evaluation, participants demonstrated amelioration in the global dysphonia rates (P=0.0003), jitter (P=0.0001), shimmer (P=0.0001), MPT (P=0.0001), and VHI (P=0.0001). Twelve months after the course, the positive effects remained, although they were slightly reduced. In conclusion, a course inclusive of two lectures, a short group voice therapy, home-controlled voice exercises, and hygiene, represents a feasible and cost-effective primary prevention of voice disorders in a homogeneous and well-motivated population of teachers.
Yazdanbakhsh, Ardavan
2018-04-27
Several pioneering life cycle assessment (LCA) studies have been conducted in the past to assess the environmental impact of specific methods for managing mineral construction and demolition waste (MCDW), such as recycling the waste for use in concrete. Those studies focus on comparing the use of recycled MCDW and that of virgin components to produce materials or systems that serve specified functions. Often, the approaches adopted by the studies do not account for the potential environmental consequence of avoiding the existing or alternative waste management practices. The present work focuses on how product systems need to be defined in recycling LCA studies and what processes need to be within the system boundaries. A bi-level LCA framework is presented for modelling alternative waste management approaches in which the impacts are measured and compared at two scales of strategy and decision-making. Different functional units are defined for each level, all of which correspond to the same flow of MCDW in a cascade of product systems. For the sole purpose of demonstrating how the framework is implemented an illustrative example is presented, based on real data and a number of simplifying assumptions, which compares the impacts of a number of potential MCDW management strategies in New York City. Copyright © 2018 Elsevier Ltd. All rights reserved.
Mixed Waste Integrated Program -- Problem-oriented technology development
International Nuclear Information System (INIS)
Hart, P.W.; Wolf, S.W.; Berry, J.B.
1994-01-01
The Mixed Waste Integrated Program (MWIP) is responding to the need for DOE mixed waste treatment technologies that meet these dual regulatory requirements. MWIP is developing emerging and innovative treatment technologies to determine process feasibility. Technology demonstrations will be used to determine whether processes are superior to existing technologies in reducing risk, minimizing life-cycle cost, and improving process performance. Technology development is ongoing in technical areas required to process mixed waste: materials handling, chemical/physical treatment, waste destruction, off-gas treatment, final forms, and process monitoring/control. MWIP is currently developing a suite of technologies to process heterogeneous waste. One robust process is the fixed-hearth plasma-arc process that is being developed to treat a wide variety of contaminated materials with minimal characterization. Additional processes encompass steam reforming, including treatment of waste under the debris rule. Advanced off-gas systems are also being developed. Vitrification technologies are being demonstrated for the treatment of homogeneous wastes such as incinerator ash and sludge. An alternative to conventional evaporation for liquid removal--freeze crystallization--is being investigated. Since mercury is present in numerous waste streams, mercury removal technologies are being developed
Neutron dosimetry program at Mound - problems and solutions
International Nuclear Information System (INIS)
Winegardner, M.K.
1991-01-01
The Mound personnel neutron dosimetry program utilizes TLD albedo technology. The neutron dosimeter design incorporates a two-element spectrometer for site-specific neutron quality determination and empirical application of field neutron calibration factors. Design elements feature two Li(6)F (TLD- 600) chips for neutron detection and one Li(7)F (TLD-700) chip for gamma compensation of the TLD- 600 chips. One TLD-600 chip is Cadmium shielded on the front side of the dosimeter, the other is Cadmium shielded from the back side. Tin filters are placed opposite of the Cadmium shield on each of the TLD-600 chips and on both sides of the TLD-700 chip for symmetrically equivalent gamma absorption characteristics. Neutron quality determination is accomplished by the albedo neutron-to- incident thermal neutron response ratio above the Cadmium cutoff. This front Cadmium shielded-to-back Cadmium shielded response ratio, compensated for the presence of gamma radiation, provides the basis for neutron energy calibration via the albedo response curve
Sensitivity analysis of efficient solution in vector MINMAX boolean programming problem
Directory of Open Access Journals (Sweden)
Vladimir A. Emelichev
2002-11-01
Full Text Available We consider a multiple criterion Boolean programming problem with MINMAX partial criteria. The extreme level of independent perturbations of partial criteria parameters such that efficient (Pareto optimal solution preserves optimality was obtained.
Fuzzy Multi Objective Linear Programming Problem with Imprecise Aspiration Level and Parameters
Directory of Open Access Journals (Sweden)
Zahra Shahraki
2015-07-01
Full Text Available This paper considers the multi-objective linear programming problems with fuzzygoal for each of the objective functions and constraints. Most existing works deal withlinear membership functions for fuzzy goals. In this paper, exponential membershipfunction is used.
Directory of Open Access Journals (Sweden)
Hideki Katagiri
2017-10-01
Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
NEWBOX: A computer program for parameter estimation in diffusion problems
International Nuclear Information System (INIS)
Nestor, C.W. Jr.; Godbee, H.W.; Joy, D.S.
1989-01-01
In the analysis of experiments to determine amounts of material transferred form 1 medium to another (e.g., the escape of chemically hazardous and radioactive materials from solids), there are at least 3 important considerations. These are (1) is the transport amenable to treatment by established mass transport theory; (2) do methods exist to find estimates of the parameters which will give a best fit, in some sense, to the experimental data; and (3) what computational procedures are available for evaluating the theoretical expressions. The authors have made the assumption that established mass transport theory is an adequate model for the situations under study. Since the solutions of the diffusion equation are usually nonlinear in some parameters (diffusion coefficient, reaction rate constants, etc.), use of a method of parameter adjustment involving first partial derivatives can be complicated and prone to errors in the computation of the derivatives. In addition, the parameters must satisfy certain constraints; for example, the diffusion coefficient must remain positive. For these reasons, a variant of the constrained simplex method of M. J. Box has been used to estimate parameters. It is similar, but not identical, to the downhill simplex method of Nelder and Mead. In general, they calculate the fraction of material transferred as a function of time from expressions obtained by the inversion of the Laplace transform of the fraction transferred, rather than by taking derivatives of a calculated concentration profile. With the above approaches to the 3 considerations listed at the outset, they developed a computer program NEWBOX, usable on a personal computer, to calculate the fractional release of material from 4 different geometrical shapes (semi-infinite medium, finite slab, finite circular cylinder, and sphere), accounting for several different boundary conditions
An optimal maintenance policy for machine replacement problem using dynamic programming
Mohsen Sadegh Amalnik; Morteza Pourgharibshahi
2017-01-01
In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling inc...
The role of metacognitive skills in solving object-oriented programming problems: a case study
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Marietjie Havenga
2015-07-01
Full Text Available This article reports on the role of metacognitive skills when solving object-oriented programming problems as part of a case study. The research was constructivist-based within an interpretivist approach to explore how four students constructed their own thinking when solving programming problems. A qualitative methodology was employed. Both concept-driven coding and data-driven coding were applied. Two main issues emerged from the findings. Participating students had fragmented knowledge of the object-oriented approach and shortcomings regarding the implementation thereof, and they experienced problems with metacognitive control during all the steps of program development. Based on the findings the use of metacognitive critical control points (MCCPs is proposed to be used as a mechanism to facilitate students in their programming efforts and to prevent loss of control during program development.
An Integer Programming Formulation of the Minimum Common String Partition Problem.
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S M Ferdous
Full Text Available We consider the problem of finding a minimum common string partition (MCSP of two strings, which is an NP-hard problem. The MCSP problem is closely related to genome comparison and rearrangement, an important field in Computational Biology. In this paper, we map the MCSP problem into a graph applying a prior technique and using this graph, we develop an Integer Linear Programming (ILP formulation for the problem. We implement the ILP formulation and compare the results with the state-of-the-art algorithms from the literature. The experimental results are found to be promising.
Directory of Open Access Journals (Sweden)
Jingtao Shi
2013-01-01
Full Text Available This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.
A Smooth Newton Method for Nonlinear Programming Problems with Inequality Constraints
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Vasile Moraru
2012-02-01
Full Text Available The paper presents a reformulation of the Karush-Kuhn-Tucker (KKT system associated nonlinear programming problem into an equivalent system of smooth equations. Classical Newton method is applied to solve the system of equations. The superlinear convergence of the primal sequence, generated by proposed method, is proved. The preliminary numerical results with a problems test set are presented.
Analysis of Learning Behavior in a Flipped Programing Classroom Adopting Problem-Solving Strategies
Chiang, Tosti Hsu-Cheng
2017-01-01
Programing is difficult for beginners because they need to learn the new language of computers. Developing software, especially complex software, is bound to result in problems, frustration, and the need to think in new ways. Identifying the learning behavior behind programing by way of empirical studies can help beginners learn more easily. In…
Allinjawi, Arwa A.; Al-Nuaim, Hana A.; Krause, Paul
2014-01-01
Students often face difficulties while learning object-oriented programming (OOP) concepts. Many papers have presented various assessment methods for diagnosing learning problems to improve the teaching of programming in computer science (CS) higher education. The research presented in this article illustrates that although max-min composition is…
International Nuclear Information System (INIS)
Fiore, J.J.; Turi, G.P.
1988-01-01
The Formerly Utilized Sites Remedial Action Program (FUSRAP) was established in 1974 to identify, evaluate, and as appropriate, conduct remedial actions at sites used in the early years of nuclear energy development by the Manhattan Engineer District and the Atomic Energy Commission (AEC). This program currently has 29 sites and is evaluating 350 other sites for possible inclusion in the program. Another remedial action program in the Department of Energy's (DOE) Division of Facility and Site Decommissioning Projects is the Surplus Facilities Management Program (SFMP). The SFMP involves the safe management, decontamination and disposal of surplus DOE contaminated facilities which were not related to defense activities. There are currently 33 projects at 15 different sites in the program. These two programs have made steady progress over the last 10 or so years in cleaning up sites so that they can be reused or released for unrestricted use. Work has been completed at 8 of the FUSRAP sites and three of the SFMP sites
CASKETSS-HEAT: a finite difference computer program for nonlinear heat conduction problems
International Nuclear Information System (INIS)
Ikushima, Takeshi
1988-12-01
A heat conduction program CASKETSS-HEAT has been developed. CASKETSS-HEAT is a finite difference computer program used for the solution of multi-dimensional nonlinear heat conduction problems. Main features of CASKETSS-HEAT are as follows. (1) One, two and three-dimensional geometries for heat conduction calculation are available. (2) Convection and radiation heat transfer of boundry can be specified. (3) Phase change and chemical change can be treated. (4) Finned surface heat transfer can be treated easily. (5) Data memory allocation in the program is variable according to problem size. (6) The program is a compatible heat transfer analysis program to the stress analysis program SAP4 and SAP5. (7) Pre- and post-processing for input data generation and graphic representation of calculation results are available. In the paper, brief illustration of calculation method, input data and sample calculation are presented. (author)
Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control
Energy Technology Data Exchange (ETDEWEB)
Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au [Macquarie University, Department of Mathematics (Australia); Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au [Flinders University, Flinders Mathematical Sciences Laboratory, School of Computer Science, Engineering and Mathematics (Australia)
2015-04-15
The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.
International Nuclear Information System (INIS)
Gartling, D.K.
1978-04-01
The theoretical background for the finite element computer program, NACHOS, is presented in detail. The NACHOS code is designed for the two-dimensional analysis of viscous incompressible fluid flows, including the effects of heat transfer. A general description of the fluid/thermal boundary value problems treated by the program is described. The finite element method and the associated numerical methods used in the NACHOS code are also presented. Instructions for use of the program are documented in SAND77-1334
Directory of Open Access Journals (Sweden)
Hassan Ismkhan
2014-01-01
Full Text Available The traveling salesman problem (TSP is one of the most famous problems. Many applications and programming tools have been developed to handle TSP. However, it seems to be essential to provide easy programming tools according to state-of-the-art algorithms. Therefore, we have collected and programmed new easy tools by the three object-oriented languages. In this paper, we present ADT (abstract data type of developed tools at first; then we analyze their performance by experiments. We also design a hybrid genetic algorithm (HGA by developed tools. Experimental results show that the proposed HGA is comparable with the recent state-of-the-art applications.
APPLYING ROBUST RANKING METHOD IN TWO PHASE FUZZY OPTIMIZATION LINEAR PROGRAMMING PROBLEMS (FOLPP
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Monalisha Pattnaik
2014-12-01
Full Text Available Background: This paper explores the solutions to the fuzzy optimization linear program problems (FOLPP where some parameters are fuzzy numbers. In practice, there are many problems in which all decision parameters are fuzzy numbers, and such problems are usually solved by either probabilistic programming or multi-objective programming methods. Methods: In this paper, using the concept of comparison of fuzzy numbers, a very effective method is introduced for solving these problems. This paper extends linear programming based problem in fuzzy environment. With the problem assumptions, the optimal solution can still be theoretically solved using the two phase simplex based method in fuzzy environment. To handle the fuzzy decision variables can be initially generated and then solved and improved sequentially using the fuzzy decision approach by introducing robust ranking technique. Results and conclusions: The model is illustrated with an application and a post optimal analysis approach is obtained. The proposed procedure was programmed with MATLAB (R2009a version software for plotting the four dimensional slice diagram to the application. Finally, numerical example is presented to illustrate the effectiveness of the theoretical results, and to gain additional managerial insights.
Developing a pedagogical problem solving view for mathematics teachers with two reflection programs
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Bracha KRAMARSKI
2009-10-01
Full Text Available The study investigated the effects of two reflection support programs on elementary school mathematics teachers’ pedagogical problem solving view. Sixty-two teachers participated in a professional development program. Thirty teachers were assigned to the self-questioning (S_Q training and thirty two teachers were assigned to the reflection discourse (R_D training. The S_Q program was based on the IMPROVE self-questioning approach which emphasizes systematic discussion along the phases of mathematical or pedagogical problem solving as student and teacher. The R_D program emphasized discussion of standard based teaching and learning principles. Findings indicated that systematic reflection support (S_Q is effective for developing mathematics PCK, and strengthening metacognitive knowledge of mathematics teachers, more than reflection discourse (R_D. No differences were found between the groups in developing beliefs about teaching mathematics in using problem solving view.
DEFF Research Database (Denmark)
Pour, Shahrzad M.; Drake, John H.; Ejlertsen, Lena Secher
2017-01-01
A railway signaling system is a complex and interdependent system which should ensure the safe operation of trains. We introduce and address a mixed integer optimisation model for the preventive signal maintenance crew scheduling problem in the Danish railway system. The problem contains many...... to feed as ‘warm start’ solutions to a Mixed Integer Programming (MIP) solver for further optimisation. We apply the CP/MIP framework to a section of the Danish rail network and benchmark our results against both direct application of a MIP solver and modelling the problem as a Constraint Optimisation...
A bulk queueing system under N-policy with bilevel service delay discipline and start-up time
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David C. R. Muh
1993-01-01
Full Text Available The author studies the queueing process in a single-server, bulk arrival and batch service queueing system with a compound Poisson input, bilevel service delay discipline, start-up time, and a fixed accumulation level with control operating policy. It is assumed that when the queue length falls below a predefined level r(≥1, the system, with server capacity R, immediately stops service until the queue length reaches or exceeds the second predefined accumulation level N(≥r. Two cases, with N≤R and N≥R, are studied.
Lima, Ricardo
2016-06-16
This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
Lima, Ricardo; Grossmann, Ignacio E.
2016-01-01
This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
Contal, Olivier; Vignaux, Laurence; Combescure, Christophe; Pepin, Jean-Louis; Jolliet, Philippe; Janssens, Jean-Paul
2012-02-01
Current bilevel positive-pressure ventilators for home noninvasive ventilation (NIV) provide physicians with software that records items important for patient monitoring, such as compliance, tidal volume (Vt), and leaks. However, to our knowledge, the validity of this information has not yet been independently assessed. Testing was done for seven home ventilators on a bench model adapted to simulate NIV and generate unintentional leaks (ie, other than of the mask exhalation valve). Five levels of leaks were simulated using a computer-driven solenoid valve (0-60 L/min) at different levels of inspiratory pressure (15 and 25 cm H(2)O) and at a fixed expiratory pressure (5 cm H(2)O), for a total of 10 conditions. Bench data were compared with results retrieved from ventilator software for leaks and Vt. For assessing leaks, three of the devices tested were highly reliable, with a small bias (0.3-0.9 L/min), narrow limits of agreement (LA), and high correlations (R(2), 0.993-0.997) when comparing ventilator software and bench results; conversely, for four ventilators, bias ranged from -6.0 L/min to -25.9 L/min, exceeding -10 L/min for two devices, with wide LA and lower correlations (R(2), 0.70-0.98). Bias for leaks increased markedly with the importance of leaks in three devices. Vt was underestimated by all devices, and bias (range, 66-236 mL) increased with higher insufflation pressures. Only two devices had a bias ventilation must be aware of differences in the estimation of leaks and Vt by ventilator software. Also, leaks are reported in different ways according to the device used.
A Kind of Nonlinear Programming Problem Based on Mixed Fuzzy Relation Equations Constraints
Li, Jinquan; Feng, Shuang; Mi, Honghai
In this work, a kind of nonlinear programming problem with non-differential objective function and under the constraints expressed by a system of mixed fuzzy relation equations is investigated. First, some properties of this kind of optimization problem are obtained. Then, a polynomial-time algorithm for this kind of optimization problem is proposed based on these properties. Furthermore, we show that this algorithm is optimal for the considered optimization problem in this paper. Finally, numerical examples are provided to illustrate our algorithms.
International Nuclear Information System (INIS)
Sergienko, I.V.; Golodnikov, A.N.
1984-01-01
This article applies the methods of decompositions, which are used to solve continuous linear problems, to integer and partially integer problems. The fall-vector method is used to solve the obtained coordinate problems. An algorithm of the fall-vector is described. The Kornai-Liptak decomposition principle is used to reduce the integer linear programming problem to integer linear programming problems of a smaller dimension and to a discrete coordinate problem with simple constraints
Directory of Open Access Journals (Sweden)
Yi-hua Zhong
2013-01-01
Full Text Available Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.
Crawford, J. L.; Rodney, G. A.
1989-01-01
This paper describes the NASA Space Shuttle Trend Analysis program. The four main areas of the program - problem/reliability, performance, supportability, and programmatic trending - are defined, along with motivation for these areas, the statistical methods used, and illustrative Space Shuttle applications. Also described is the NASA Safety, Reliability, Maintainability and Quality Assurance (SRM&QA) Management Information Center, used to focus management attention on key near-term launch concerns and long-range mission trend issues. Finally, the computer data bases used to support the program and future program enhancements are discussed.
IESIP - AN IMPROVED EXPLORATORY SEARCH TECHNIQUE FOR PURE INTEGER LINEAR PROGRAMMING PROBLEMS
Fogle, F. R.
1994-01-01
IESIP, an Improved Exploratory Search Technique for Pure Integer Linear Programming Problems, addresses the problem of optimizing an objective function of one or more variables subject to a set of confining functions or constraints by a method called discrete optimization or integer programming. Integer programming is based on a specific form of the general linear programming problem in which all variables in the objective function and all variables in the constraints are integers. While more difficult, integer programming is required for accuracy when modeling systems with small numbers of components such as the distribution of goods, machine scheduling, and production scheduling. IESIP establishes a new methodology for solving pure integer programming problems by utilizing a modified version of the univariate exploratory move developed by Robert Hooke and T.A. Jeeves. IESIP also takes some of its technique from the greedy procedure and the idea of unit neighborhoods. A rounding scheme uses the continuous solution found by traditional methods (simplex or other suitable technique) and creates a feasible integer starting point. The Hook and Jeeves exploratory search is modified to accommodate integers and constraints and is then employed to determine an optimal integer solution from the feasible starting solution. The user-friendly IESIP allows for rapid solution of problems up to 10 variables in size (limited by DOS allocation). Sample problems compare IESIP solutions with the traditional branch-and-bound approach. IESIP is written in Borland's TURBO Pascal for IBM PC series computers and compatibles running DOS. Source code and an executable are provided. The main memory requirement for execution is 25K. This program is available on a 5.25 inch 360K MS DOS format diskette. IESIP was developed in 1990. IBM is a trademark of International Business Machines. TURBO Pascal is registered by Borland International.
Problem Space Matters: Evaluation of a German Enrichment Program for Gifted Children.
Welter, Marisete M; Jaarsveld, Saskia; Lachmann, Thomas
2018-01-01
We studied the development of cognitive abilities related to intelligence and creativity ( N = 48, 6-10 years old), using a longitudinal design (over one school year), in order to evaluate an Enrichment Program for gifted primary school children initiated by the government of the German federal state of Rhineland-Palatinate ( Entdeckertag Rheinland Pfalz , Germany; ET; Day of Discoverers). A group of German primary school children ( N = 24), identified earlier as intellectually gifted and selected to join the ET program was compared to a gender-, class- and IQ- matched group of control children that did not participate in this program. All participants performed the Standard Progressive Matrices (SPM) test, which measures intelligence in well-defined problem space; the Creative Reasoning Task (CRT), which measures intelligence in ill-defined problem space; and the test of creative thinking-drawing production (TCT-DP), which measures creativity, also in ill-defined problem space. Results revealed that problem space matters: the ET program is effective only for the improvement of intelligence operating in well-defined problem space. An effect was found for intelligence as measured by SPM only, but neither for intelligence operating in ill-defined problem space (CRT) nor for creativity (TCT-DP). This suggests that, depending on the type of problem spaces presented, different cognitive abilities are elicited in the same child. Therefore, enrichment programs for gifted, but also for children attending traditional schools, should provide opportunities to develop cognitive abilities related to intelligence, operating in both well- and ill-defined problem spaces, and to creativity in a parallel, using an interactive approach.
Directory of Open Access Journals (Sweden)
Tunjo Perić
2017-01-01
Full Text Available This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1 Taylor’s polynomial linearization approximation, (2 the method of variable change, and (3 a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a using the optimal value of the objective functions as the decision makers’ aspirations, and (b the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Rauff Lind Christensen, Tue; Klose, Andreas; Andersen, Kim Allan
important aspects of supplier selection, an important application of the SSFCTP, this does not reflect the real life situation. First, transportation costs faced by many companies are in fact piecewise linear. Secondly, when suppliers offer discounts, either incremental or all-unit discounts, such savings......The Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem (SSFCMCTP) is a problem with versatile applications. This problem is a generalization of the Single-Sink, Fixed-Charge Transportation Problem (SSFCTP), which has a fixed-charge, linear cost structure. However, in at least two...... are neglected in the SSFCTP. The SSFCMCTP overcome this problem by incorporating a staircase cost structure in the cost function instead of the usual one used in SSFCTP. We present a dynamic programming algorithm for the resulting problem. To enhance the performance of the generic algorithm a number...
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Christensen, Tue; Andersen, Kim Allan; Klose, Andreas
2013-01-01
This paper considers a minimum-cost network flow problem in a bipartite graph with a single sink. The transportation costs exhibit a staircase cost structure because such types of transportation cost functions are often found in practice. We present a dynamic programming algorithm for solving...... this so-called single-sink, fixed-charge, multiple-choice transportation problem exactly. The method exploits heuristics and lower bounds to peg binary variables, improve bounds on flow variables, and reduce the state-space variable. In this way, the dynamic programming method is able to solve large...... instances with up to 10,000 nodes and 10 different transportation modes in a few seconds, much less time than required by a widely used mixed-integer programming solver and other methods proposed in the literature for this problem....
International Nuclear Information System (INIS)
2012-01-01
On October, 30 - November, 2 in State Scientific Center of the Russian Federation - Institute for Physics and Power Engineering named after A.I. Leypunsky a seminar Neutron-physical problems of nuclear power engineering - Neutronika-2012 took place. On the seminar the following problems were discussed: justification of neutron-physical characteristics of reactor facilities and innovation projects; constant support of neutron-physical calculations of nuclear power installations; numerical simulation during solving reactor physics problems; simulation of neutron-physical processes in reactor facilities by Monte Carlo method; development and verification of programs for reactor facilities neutron-physical calculations; algorithms and programs for solving nonstationary problems of neutron-physical calculation of nuclear reactors; analysis of integral and reactor experiments, experimental database; justification of nuclear and radiation safety of fuel cycle [ru
Khursheed, Khursheed; Imran, Muhammad; Ahmad, Naeem; O'Nils, Mattias
2012-06-01
Wireless Visual Sensor Network (WVSN) is an emerging field which combines image sensor, on board computation unit, communication component and energy source. Compared to the traditional wireless sensor network, which operates on one dimensional data, such as temperature, pressure values etc., WVSN operates on two dimensional data (images) which requires higher processing power and communication bandwidth. Normally, WVSNs are deployed in areas where installation of wired solutions is not feasible. The energy budget in these networks is limited to the batteries, because of the wireless nature of the application. Due to the limited availability of energy, the processing at Visual Sensor Nodes (VSN) and communication from VSN to server should consume as low energy as possible. Transmission of raw images wirelessly consumes a lot of energy and requires higher communication bandwidth. Data compression methods reduce data efficiently and hence will be effective in reducing communication cost in WVSN. In this paper, we have compared the compression efficiency and complexity of six well known bi-level image compression methods. The focus is to determine the compression algorithms which can efficiently compress bi-level images and their computational complexity is suitable for computational platform used in WVSNs. These results can be used as a road map for selection of compression methods for different sets of constraints in WVSN.
Energy Technology Data Exchange (ETDEWEB)
He, Li, E-mail: li.he@iseis.org [MOE Key Laboratory of Regional Energy Systems Optimization, S and C Academy of Energy and Environmental Research, North China Electric Power University, Beijing 102206 (China); Huang, G.H.; Lu, Hongwei [MOE Key Laboratory of Regional Energy Systems Optimization, S and C Academy of Energy and Environmental Research, North China Electric Power University, Beijing 102206 (China)
2011-10-15
Highlights: {yields} We used bilevel analysis to treat two objectives at different levels. {yields} The model can identify allocation schemes for waste flows. {yields} The model can support waste timing, sizing, and siting for facility expansions. {yields} The model can estimate minimized total management cost and GHG emissions. - Abstract: Recent studies indicated that municipal solid waste (MSW) is a major contributor to global warming due to extensive emissions of greenhouse gases (GHGs). However, most of them focused on investigating impacts of MSW on GHG emission amounts. This study presents two mixed integer bilevel decision-making models for integrated municipal solid waste management and GHG emissions control: MGU-MCL and MCU-MGL. The MGU-MCL model represents a top-down decision process, with the environmental sectors at the national level dominating the upper-level objective and the waste management sectors at the municipal level providing the lower-level objective. The MCU-MGL model implies a bottom-up decision process where municipality plays a leading role. Results from the models indicate that: the top-down decisions would reduce metric tonne carbon emissions (MTCEs) by about 59% yet increase about 8% of the total management cost; the bottom-up decisions would reduce MTCE emissions by about 13% but increase the total management cost very slightly; on-site monitoring and downscaled laboratory experiments are still required for reducing uncertainty in GHG emission rate from the landfill facility.
Chen, Yuqing; Cheng, Kewen; Zhou, Xin
2015-01-26
Pressure support ventilation from a bilevel device is a standard technique for non-invasive home ventilation. A bench study was designed to compare the performance and patient-ventilator synchronization of 7 bilevel ventilators, in the presence of system leaks. Ventilators were connected to a Hans Rudolph Series 1101 lung simulator (compliance, 50 mL/cmH2O; expiratory resistance, 20 cmH2O/L/s; respiratory rate, 15 breaths/min; inspiratory time, 1.0 s). All ventilators were set at 15 cmH2O pressure support and 5 cmH2O positive end-expiratory pressure. Tests were conducted at 2 system leaks (12-15 and 25-28 L/min). The performance characteristics and patient-ventilator asynchrony were assessed, including flow, airway pressure, time, and workload. The Breas Vivo30 could not synchronize with the simulator (frequent auto-triggering) at a leak of 25-28 L/min, but provided stable assisted ventilation when the leak was 12-15 L/min. Missed efforts and back-up ventilation occurred for the Weinmann VENTImotion and Airox Smartair Plus, requiring adjustment of trigger effort. All ventilators had a short trigger delay time (ventilators, possibly due to software algorithm differences. Adjusting the cycling criteria settings can alter the shape of the inspiratory phase and peak expiratory flow, and improve patient-ventilator synchrony.
Kassab, Salah Eldin; Hassan, Nahla; El-Araby, Shimaa; Salem, Abdel Halim; Alrebish, Saleh Ali; Al-Amro, Ahmed S.; Al-Shobaili, Hani A.; Hamdy, Hossam
2017-01-01
Purpose: There are no published instruments, which measure tutor motivation for conducting small group tutorials in problem-based learning programs. Therefore, we aimed to develop a motivation for tutoring questionnaire in problem-based learning (MTQ-PBL) and evaluate its construct validity. Methods: The questionnaire included 28 items representing four constructs: tutoring self-efficacy (15 items), tutoring interest (6 items), tutoring value (4 items), and tutoring effort (3 items). Tutor...
Stress-constrained truss topology optimization problems that can be solved by linear programming
DEFF Research Database (Denmark)
Stolpe, Mathias; Svanberg, Krister
2004-01-01
We consider the problem of simultaneously selecting the material and determining the area of each bar in a truss structure in such a way that the cost of the structure is minimized subject to stress constraints under a single load condition. We show that such problems can be solved by linear...... programming to give the global optimum, and that two different materials are always sufficient in an optimal structure....
Fuzzy solution of the linear programming problem with interval coefficients in the constraints
Dorota Kuchta
2005-01-01
A fuzzy concept of solving the linear programming problem with interval coefficients is proposed. For each optimism level of the decision maker (where the optimism concerns the certainty that no errors have been committed in the estimation of the interval coefficients and the belief that optimistic realisations of the interval coefficients will occur) another interval solution of the problem will be generated and the decision maker will be able to choose the final solution having a complete v...
Solving the Frequency Assignment Problem by Site Availability and Constraint Programming
Linhares, Andrea Carneiro; Torres-Moreno, Juan-Manuel; Peinl, Peter; Michelon, Philippe
2010-01-01
The efficient use of bandwidth for radio communications becomes more and more crucial when developing new information technologies and their applications. The core issues are addressed by the so-called Frequency Assignment Problems (FAP). Our work investigates static FAP, where an attempt is first made to configure a kernel of links. We study the problem based on the concepts and techniques of Constraint Programming and integrate the site availability concept. Numerical simulations conducted ...
An Improved Search Approach for Solving Non-Convex Mixed-Integer Non Linear Programming Problems
Sitopu, Joni Wilson; Mawengkang, Herman; Syafitri Lubis, Riri
2018-01-01
The nonlinear mathematical programming problem addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method, has been developed. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points. Successful implementation of these algorithms was achieved on various test problems.
Directory of Open Access Journals (Sweden)
Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.
2018-03-01
Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.
Czech Academy of Sciences Publication Activity Database
Šmíd, Martin
2009-01-01
Roč. 165, č. 1 (2009), s. 29-45 ISSN 0254-5330 R&D Projects: GA ČR GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : multistage stochastic programming problems * approximation * discretization * Monte Carlo Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.961, year: 2009 http://library.utia.cas.cz/separaty/2008/E/smid-the expected loss in the discretization of multistage stochastic programming problems - estimation and convergence rate.pdf
Directory of Open Access Journals (Sweden)
Paweł Sitek
2016-01-01
Full Text Available This paper proposes a hybrid programming framework for modeling and solving of constraint satisfaction problems (CSPs and constraint optimization problems (COPs. Two paradigms, CLP (constraint logic programming and MP (mathematical programming, are integrated in the framework. The integration is supplemented with the original method of problem transformation, used in the framework as a presolving method. The transformation substantially reduces the feasible solution space. The framework automatically generates CSP and COP models based on current values of data instances, questions asked by a user, and set of predicates and facts of the problem being modeled, which altogether constitute a knowledge database for the given problem. This dynamic generation of dedicated models, based on the knowledge base, together with the parameters changing externally, for example, the user’s questions, is the implementation of the autonomous search concept. The models are solved using the internal or external solvers integrated with the framework. The architecture of the framework as well as its implementation outline is also included in the paper. The effectiveness of the framework regarding the modeling and solution search is assessed through the illustrative examples relating to scheduling problems with additional constrained resources.
Dohi, Tomotaka; Kasai, Takatoshi; Narui, Koji; Ishiwata, Sugao; Ohno, Minoru; Yamaguchi, Tetsu; Momomura, Shin-Ichi
2008-07-01
Cheyne-Stokes respiration with central sleep apnea (CSR-CSA) is associated with a poor prognosis in patients with heart failure (HF). However, some patients do not respond to continuous positive airway pressure (CPAP), so other therapeutic modalities should be considered, such as bi-level positive airway pressure (PAP), which also assists respiration and might be effective for such patients. The 20 patients with HF because of left ventricular systolic dysfunction were assessed: 8 had ischemic etiology, and all had severe CSA according to the apnea - hypopnea index (AHI) determined by polysomnography. All diagnosed patients underwent repeat polysomnography using CPAP. The AHI improved significantly in 11 (AHI or=15). Bi-level PAP titration significantly improved the AHI in the latter group. Those who were unresponsive to CPAP had significantly lower PaCO(2), higher plasma brain natriuretic peptide (BNP), longer mean duration of CSR and fewer obstructive episodes than CPAP responders. After 6 months of positive airway support with either CPAP (n=9) or bi-level PAP (n=7), BNP levels significantly decreased and left ventricular ejection fraction significantly increased. Bi-level PAP could be an effective alternative for patients with HF and pure CSR-CSA who are unresponsive to CPAP.
Thomas, Patricia E; LeFlore, Judy
2013-01-01
Infants born prematurely with respiratory distress syndrome are at high risk for complications from mechanical ventilation. Strategies are needed to minimize their days on the ventilator. The purpose of this study was to compare extubation success rates in infants treated with 2 different types of continuous positive airway pressure devices. A retrospective cohort study design was used. Data were retrieved from electronic medical records for patients in a large, metropolitan, level III neonatal intensive care unit. A sample of 194 premature infants with respiratory distress syndrome was selected, 124 of whom were treated with nasal intermittent positive pressure ventilation and 70 with bi-level variable flow nasal continuous positive airway pressure (bi-level nasal continuous positive airway pressure). Infants in both groups had high extubation success rates (79% of nasal intermittent positive pressure ventilation group and 77% of bi-level nasal continuous positive airway pressure group). Although infants in the bi-level nasal continuous positive airway pressure group were extubated sooner, there was no difference in duration of oxygen therapy between the 2 groups. Promoting early extubation and extubation success is a vital strategy to reduce complications of mechanical ventilation that adversely affect premature infants with respiratory distress syndrome.
QUANTITY DISCOUNTS IN SUPPLIER SELECTION PROBLEM BY USE OF FUZZY MULTI-CRITERIA PROGRAMMING
Directory of Open Access Journals (Sweden)
Tunjo Perić
2011-02-01
Full Text Available Supplier selection in supply chain is a multi-criteria problem that involves a number of quantitative and qualitative factors. This paper deals with a concrete problem of flour purchase by a company that manufactures bakery products and the purchasing price of flour depends on the quantity ordered. The criteria for supplier selection and quantities supplied by individual suppliers are: purchase costs, product quality and reliability of suppliers. The problem is solved using a model that combines revised weighting method and fuzzy multi-criteria linear programming (FMCLP. The paper highlights the efficiency of the proposed methodology in conditions when purchasing prices depend on order quantities.
An Augmented Lagrangian Method for a Class of Inverse Quadratic Programming Problems
International Nuclear Information System (INIS)
Zhang Jianzhong; Zhang Liwei
2010-01-01
We consider an inverse quadratic programming (QP) problem in which the parameters in the objective function of a given QP problem are adjusted as little as possible so that a known feasible solution becomes the optimal one. We formulate this problem as a minimization problem with a positive semidefinite cone constraint and its dual is a linearly constrained semismoothly differentiable (SC 1 ) convex programming problem with fewer variables than the original one. We demonstrate the global convergence of the augmented Lagrangian method for the dual problem and prove that the convergence rate of primal iterates, generated by the augmented Lagrange method, is proportional to 1/r, and the rate of multiplier iterates is proportional to 1/√r, where r is the penalty parameter in the augmented Lagrangian. As the objective function of the dual problem is a SC 1 function involving the projection operator onto the cone of symmetrically semi-definite matrices, the analysis requires extensive tools such as the singular value decomposition of matrices, an implicit function theorem for semismooth functions, and properties of the projection operator in the symmetric-matrix space. Furthermore, the semismooth Newton method with Armijo line search is applied to solve the subproblems in the augmented Lagrange approach, which is proven to have global convergence and local quadratic rate. Finally numerical results, implemented by the augmented Lagrangian method, are reported.
Solutions to estimation problems for scalar hamilton-jacobi equations using linear programming
Claudel, Christian G.; Chamoin, Timothee; Bayen, Alexandre M.
2014-01-01
This brief presents new convex formulations for solving estimation problems in systems modeled by scalar Hamilton-Jacobi (HJ) equations. Using a semi-analytic formula, we show that the constraints resulting from a HJ equation are convex, and can be written as a set of linear inequalities. We use this fact to pose various (and seemingly unrelated) estimation problems related to traffic flow-engineering as a set of linear programs. In particular, we solve data assimilation and data reconciliation problems for estimating the state of a system when the model and measurement constraints are incompatible. We also solve traffic estimation problems, such as travel time estimation or density estimation. For all these problems, a numerical implementation is performed using experimental data from the Mobile Century experiment. In the context of reproducible research, the code and data used to compute the results presented in this brief have been posted online and are accessible to regenerate the results. © 2013 IEEE.
A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.
Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa
2018-02-01
Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.
Constraint Programming Approach to the Problem of Generating Milton Babbitt's All-partition Arrays
DEFF Research Database (Denmark)
Tanaka, Tsubasa; Bemman, Brian; Meredith, David
2016-01-01
elements and corresponding to a distinct integer partition of 12. Constraint programming (CP) is a tool for solving such combinatorial and constraint satisfaction problems. In this paper, we use CP for the first time to formalize this problem in generating an all-partition array. Solving the whole...... of this problem is difficult and few known solutions exist. Therefore, we propose solving two sub-problems and joining these to form a complete solution. We conclude by presenting a solution found using this method. Our solution is the first we are aware of to be discovered automatically using a computer......Milton Babbitt (1916–2011) was a composer of twelve-tone serial music noted for creating the all-partition array. One part of the problem in generating an all-partition array requires finding a covering of a pitch-class matrix by a collection of sets, each forming a region containing 12 distinct...
Setyo, P.; Elly, J.
2018-05-01
To increase rice production in the Province of North Kalimantan, the provincial government has launched a Food Estate Program. The program is also a central government program in relation to government policies on food security. One of the food estate development areas is the Delta Kayan Food Estate of 50,000 hectares in Bulungan Regency, where about 30,000 hectares area is a tidal land with a very fertile alluvial soil type. This policy study aims to identify and analyze problems of increasing rice production through food estate development in North Kalimantan Province and formulate priority programs as recommendations for policy making in increasing rice production. The study has identified a number of problems of increasing rice production, such as land tenure, land suitability, water system, infrastructure, accessibility of production factors, institutional, and capacity of human resources. The Analytic Hierarchy Process was applied to develop priority programs, resulting in the three most important programs being water management, improving access to production factors, and improving the capacity of human resources. Action plans related to priority programs have also been identified.
A note on solving large-scale zero-one programming problems
Adema, Jos J.
1988-01-01
A heuristic for solving large-scale zero-one programming problems is provided. The heuristic is based on the modifications made by H. Crowder et al. (1983) to the standard branch-and-bound strategy. First, the initialization is modified. The modification is only useful if the objective function
Kalelioglu, Filiz; Gülbahar, Yasemin
2014-01-01
Computer programming is perceived as an important competence for the development of problem solving skills in addition to logical reasoning. Hence, its integration throughout all educational levels, as well as the early ages, is considered valuable and research studies are carried out to explore the phenomenon in more detail. In light of these…
Reganick, Karol A.
The Cooperative Training Program was implemented with 20 students having severe behavior problems, to augment a classroom employability curriculum. Educators and business managers at a local Perkins restaurant worked cooperatively to design a new curriculum and recruitment procedure to benefit both students and the business. A continuous and…
Multiobjective Two-Stage Stochastic Programming Problems with Interval Discrete Random Variables
Directory of Open Access Journals (Sweden)
S. K. Barik
2012-01-01
Full Text Available Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered for the model parameters. Further, the concepts of best optimum and worst optimum solution are analyzed in two-stage stochastic programming. To solve the stated problem, first we remove the randomness of the problem and formulate an equivalent deterministic linear programming model with multiobjective interval coefficients. Then the deterministic multiobjective model is solved using weighting method, where we apply the solution procedure of interval linear programming technique. We obtain the upper and lower bound of the objective function as the best and the worst value, respectively. It highlights the possible risk involved in the decision-making tool. A numerical example is presented to demonstrate the proposed solution procedure.
de Klerk, E.; Laurent, M.
2011-01-01
The Lasserre hierarchy of semidefinite programming approximations to convex polynomial optimization problems is known to converge finitely under some assumptions. [J. B. Lasserre, Convexity in semialgebraic geometry and polynomial optimization, SIAM J. Optim., 19 (2009), pp. 1995–2014]. We give a
A Note on the Dual of an Unconstrained (Generalized) Geometric Programming Problem
J.B.G. Frenk (Hans); G.J. Still
2005-01-01
textabstractIn this note we show that the strong duality theorem of an unconstrained (generalized) geometric programming problem as defined by Peterson (cf.[1]) is actually a special case of a Lagrangian duality result. Contrary to [1] we also consider the case that the set C is compact and
Comparison of Cursive Handwriting Instruction Programs among Students without Identified Problems
Shimel, Kristin; Candler, Catherine; Neville-Smith, Marsha
2009-01-01
The purpose of this study was to compare the effects of cursive handwriting programs in improving letter legibility and form in third-grade students without identified handwriting problems. Four months into the school year, cursive handwriting was assessed for a sample of convenience of 50 third-grade students. Subsequently, students received…
Visual, Algebraic and Mixed Strategies in Visually Presented Linear Programming Problems.
Shama, Gilli; Dreyfus, Tommy
1994-01-01
Identified and classified solution strategies of (n=49) 10th-grade students who were presented with linear programming problems in a predominantly visual setting in the form of a computerized game. Visual strategies were developed more frequently than either algebraic or mixed strategies. Appendix includes questionnaires. (Contains 11 references.)…
Swan, Karen; Black, John B.
The results of four research studies conducted with subjects ranging in age and ability from elementary to graduate school students demonstrate that Logo programming environments can be instrumental in the development of five particular problem solving strategies: (1) subgoals formation; (2) forward chaining; (3) systematic trial and error; (4)…
Enhancing creative problem solving in an integrated visual art and geometry program: A pilot study
Schoevers, E.M.; Kroesbergen, E.H.; Pitta-Pantazi, D.
2017-01-01
This article describes a new pedagogical method, an integrated visual art and geometry program, which has the aim to increase primary school students' creative problem solving and geometrical ability. This paper presents the rationale for integrating visual art and geometry education. Furthermore
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Vlček, Jan
1998-01-01
Roč. 5, č. 3 (1998), s. 219-247 ISSN 1070-5325 R&D Projects: GA ČR GA201/96/0918 Keywords : nonlinear programming * sparse problems * equality constraints * truncated Newton method * augmented Lagrangian function * indefinite systems * indefinite preconditioners * conjugate gradient method * residual smoothing Subject RIV: BA - General Mathematics Impact factor: 0.741, year: 1998
Directory of Open Access Journals (Sweden)
X. Zhao
2012-01-01
Full Text Available A combined interior point homotopy continuation method is proposed for solving general multiobjective programming problem. We prove the existence and convergence of a smooth homotopy path from almost any interior initial interior point to a solution of the KKT system under some basic assumptions.
Universal algorithms and programs for calculating the motion parameters in the two-body problem
Bakhshiyan, B. T.; Sukhanov, A. A.
1979-01-01
The algorithms and FORTRAN programs for computing positions and velocities, orbital elements and first and second partial derivatives in the two-body problem are presented. The algorithms are applicable for any value of eccentricity and are convenient for computing various navigation parameters.
Enhancing Problem-Solving Capabilities Using Object-Oriented Programming Language
Unuakhalu, Mike F.
2009-01-01
This study integrated object-oriented programming instruction with transfer training activities in everyday tasks, which might provide a mechanism that can be used for efficient problem solving. Specifically, a Visual BASIC embedded with everyday tasks group was compared to another group exposed to Visual BASIC instruction only. Subjects were 40…
The Effectiveness of Parents' Skills Training Program on Reducing Children's Behavior Problems
Directory of Open Access Journals (Sweden)
مریم نعمتاللهی
2015-12-01
Full Text Available Objectives: The aim of this research was to evaluate the effectiveness of parents' skill training program on reducing children's behavioral problems. Method: In an experimental study (pre-post-test, 4 primary schools were randomly selected from schools of Tehran. Two schools were randomly allocated into experimental group and two into control group. Experimental group (mothers of children aged 7-9 years received parents' skill training program for 8 weeks, two hours sessions. Parents' reports participating in the training program (n=30 mothers were compared with parents' reports of non-trained control group (n=31 mothers. Data were gathered using Child Behavior Checklist (CBCL and analyzed using covariance analyses. Results: There was a significant difference between the experimental and control group after the training. The experimental group reported a significant decrease in children's behavioral problems.
Directory of Open Access Journals (Sweden)
Samir Dey
2015-07-01
Full Text Available This paper proposes a new multi-objective intuitionistic fuzzy goal programming approach to solve a multi-objective nonlinear programming problem in context of a structural design. Here we describe some basic properties of intuitionistic fuzzy optimization. We have considered a multi-objective structural optimization problem with several mutually conflicting objectives. The design objective is to minimize weight of the structure and minimize the vertical deflection at loading point of a statistically loaded three-bar planar truss subjected to stress constraints on each of the truss members. This approach is used to solve the above structural optimization model based on arithmetic mean and compare with the solution by intuitionistic fuzzy goal programming approach. A numerical solution is given to illustrate our approach.
The Strengthening Families Program 10-14: influence on parent and youth problem-solving skill.
Semeniuk, Y; Brown, R L; Riesch, S K; Zywicki, M; Hopper, J; Henriques, J B
2010-06-01
The aim of this paper is to report the results of a preliminary examination of the efficacy of the Strengthening Families Program (SFP) 10-14 in improving parent and youth problem-solving skill. The Hypotheses in this paper include: (1) youth and parents who participated in SFP would have lower mean scores immediately (T2) and 6 months (T3) post intervention on indicators of hostile and negative problem-solving strategies; (2) higher mean scores on positive problem-solving strategies; and (3) youth who participated in SFP would have higher mean scores at T2 and at T3 on indicators of individual problem solving and problem-solving efficacy than youth in the comparison group. The dyads were recruited from elementary schools that had been stratified for race and assigned randomly to intervention or comparison conditions. Mean age of youth was 11 years (SD = 1.04). Fifty-seven dyads (34-intervention&23-control) were videotaped discussing a frequently occurring problem. The videotapes were analysed using the Iowa Family Interaction Rating Scale (IFIRS) and data were analysed using Dyadic Assessment Intervention Model. Most mean scores on the IFIRS did not change. One score changed as predicted: youth hostility decreased at T3. Two scores changed contrary to prediction: parent hostility increased T3 and parent positive problem solving decreased at T2. SFP demonstrated questionable efficacy for problem-solving skill in this study.
Domí nguez, Luis F.; Pistikopoulos, Efstratios N.
2012-01-01
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear
Directory of Open Access Journals (Sweden)
M. Abdul-Niby
2016-04-01
Full Text Available The Traveling Salesman Problem (TSP is an integer programming problem that falls into the category of NP-Hard problems. As the problem become larger, there is no guarantee that optimal tours will be found within reasonable computation time. Heuristics techniques, like genetic algorithm and simulating annealing, can solve TSP instances with different levels of accuracy. Choosing which algorithm to use in order to get a best solution is still considered as a hard choice. This paper suggests domain reduction as a tool to be combined with any meta-heuristic so that the obtained results will be almost the same. The hybrid approach of combining domain reduction with any meta-heuristic encountered the challenge of choosing an algorithm that matches the TSP instance in order to get the best results.
National Research Council Canada - National Science Library
Gottschalk, Laurence
2001-01-01
The primary purpose of this thesis is to investigate the problems of retaining qualified personnel in the Program Manager for Chemical Demilitarization organization through the end date of the program...
Pesquies, P. C.; Milhaud, C.; Nogues, C.; Klein, M.; Cailler, B.; Bost, R.
The need to acquire a better knowledge of the main biological problems induced by microgravity implies—in addition to human experimentation—the use of animal models, and primates seem to be particularly well adapted to this type of research. The major areas of investigation to be considered are the phospho-calcium metabolism and the metabolism of supporting tissues, the hydroelectrolytic metabolism, the cardiovascular function, awakeness, sleep-awakeness cycles, the physiology of equilibrium and the pathophysiology of space sickness. Considering this program, the Centre d'Etudes et de Recherches de Medecine Aerospatiale, under the sponsorship of the Centre National d'Etudes Spatiales, developed both a program of research on restrained primates for the French-U.S. space cooperation (Spacelab program) and for the French-Soviet space cooperation (Bio-cosmos program), and simulation of the effects of microgravity by head-down bedrest. Its major characteristics are discussed in the study.
CLUST-applied program package for solution of radiation problems in solid-state physics
International Nuclear Information System (INIS)
Sidorenko, A.D.
1983-01-01
A general structure is outlined of the CLUST applied program package for a system of equations describing nucleation and growth of dislocation loops and vacancies in metal exposed to a fast particle flux. The CLUST package represents a set of programs for solving the systems of ordinary differential equations of special type with entering the count results into the file. The count process is controlled by a special monitor, which essentially facilitates the user program checkout and increases the efficiency of using computer time. The output of the results and scanning of the file can be realized through the analog-digital printing device or the terminal. The package structure enables the programs to be easily rearranged for solving other problems with the total number of variables 500. Operation with the package in the BEhSM-6 computer is described and principles of package rearrangement are presented
Solving inverse problems with the unfolding program TRUEE: Examples in astroparticle physics
International Nuclear Information System (INIS)
Milke, N.; Doert, M.; Klepser, S.; Mazin, D.; Blobel, V.; Rhode, W.
2013-01-01
The unfolding program TRUEE is a software package for the numerical solution of inverse problems. The algorithm was first applied in the FORTRAN 77 program RUN. RUN is an event-based unfolding algorithm which makes use of the Tikhonov regularization. It has been tested and compared to different unfolding applications and stood out with notably stable results and reliable error estimation. TRUEE is a conversion of RUN to C++, which works within the powerful ROOT framework. The program has been extended for more user-friendliness and delivers unfolding results which are identical to RUN. Beside the simplicity of the installation of the software and the generation of graphics, there are new functions, which facilitate the choice of unfolding parameters and observables for the user. In this paper, we introduce the new unfolding program and present its performance by applying it to two exemplary data sets from astroparticle physics, taken with the MAGIC telescopes and the IceCube neutrino detector, respectively.
A linear programming approach to max-sum problem: a review.
Werner, Tomás
2007-07-01
The max-sum labeling problem, defined as maximizing a sum of binary (i.e., pairwise) functions of discrete variables, is a general NP-hard optimization problem with many applications, such as computing the MAP configuration of a Markov random field. We review a not widely known approach to the problem, developed by Ukrainian researchers Schlesinger et al. in 1976, and show how it contributes to recent results, most importantly, those on the convex combination of trees and tree-reweighted max-product. In particular, we review Schlesinger et al.'s upper bound on the max-sum criterion, its minimization by equivalent transformations, its relation to the constraint satisfaction problem, the fact that this minimization is dual to a linear programming relaxation of the original problem, and the three kinds of consistency necessary for optimality of the upper bound. We revisit problems with Boolean variables and supermodular problems. We describe two algorithms for decreasing the upper bound. We present an example application for structural image analysis.
Multi-objective genetic algorithm for solving N-version program design problem
International Nuclear Information System (INIS)
Yamachi, Hidemi; Tsujimura, Yasuhiro; Kambayashi, Yasushi; Yamamoto, Hisashi
2006-01-01
N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost
Multi-objective genetic algorithm for solving N-version program design problem
Energy Technology Data Exchange (ETDEWEB)
Yamachi, Hidemi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan) and Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamachi@nit.ac.jp; Tsujimura, Yasuhiro [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: tujimr@nit.ac.jp; Kambayashi, Yasushi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: yasushi@nit.ac.jp; Yamamoto, Hisashi [Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamamoto@cc.tmit.ac.jp
2006-09-15
N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost.
The Effect of TMPT Program on Pre-School Children's Social Problem Solving Skills
Gur, Cagla; Kocak, Nurcan
2018-01-01
Purpose: Starting Thinking Training at an early age is important. However, few studies were found regarding Thinking Training programs for pre-school children and the contributions of these programs to children's social problem-solving. In this context, the TMPT Program was developed for pre-school children and the effect of the program on 5-6…
International Nuclear Information System (INIS)
Tavakkoli-Moghaddam, R.
1999-01-01
This paper present unequal-sized facilities layout solutions generated by a genetic search program. named Layout Design using a Genetic Algorithm) 9. The generalized quadratic assignment problem requiring pre-determined distance and material flow matrices as the input data and the continuous plane model employing a dynamic distance measure and a material flow matrix are discussed. Computational results on test problems are reported as compared with layout solutions generated by the branch - and bound algorithm a hybrid method merging simulated annealing and local search techniques, and an optimization process of an enveloped block
Directory of Open Access Journals (Sweden)
A.V. Degtyarev
2013-10-01
Full Text Available In this article, deviant behavior is considered as a combination of different manifestations of personality, leading eventually to its social desaptation. It is shown that an effective method of preventing deviant behavior is psychological training. Group training activity helps to solve the problems associated with the development of various behavioral skills, to provide psychological support, and can be used as a means of psychological work with teenagers with behavioral problems. We discuss the basic points required to effectively create and conduct training programs in general, as well as the challenges and opportunities of designing trainings in order to develop emotional intelligence as a method of prevention of deviant behavior
High profile students’ growth of mathematical understanding in solving linier programing problems
Utomo; Kusmayadi, TA; Pramudya, I.
2018-04-01
Linear program has an important role in human’s life. This linear program is learned in senior high school and college levels. This material is applied in economy, transportation, military and others. Therefore, mastering linear program is useful for provision of life. This research describes a growth of mathematical understanding in solving linear programming problems based on the growth of understanding by the Piere-Kieren model. Thus, this research used qualitative approach. The subjects were students of grade XI in Salatiga city. The subjects of this study were two students who had high profiles. The researcher generally chose the subjects based on the growth of understanding from a test result in the classroom; the mark from the prerequisite material was ≥ 75. Both of the subjects were interviewed by the researcher to know the students’ growth of mathematical understanding in solving linear programming problems. The finding of this research showed that the subjects often folding back to the primitive knowing level to go forward to the next level. It happened because the subjects’ primitive understanding was not comprehensive.
Directory of Open Access Journals (Sweden)
Dongkai Shen
2016-01-01
Full Text Available In recent studies on the dynamic characteristics of ventilation system, it was considered that human had only one lung, and the coupling effect of double lungs on the air flow can not be illustrated, which has been in regard to be vital to life support of patients. In this article, to illustrate coupling effect of double lungs on flow dynamics of mechanical ventilation system, a mathematical model of a mechanical ventilation system, which consists of double lungs and a bi-level positive airway pressure (BIPAP controlled ventilator, was proposed. To verify the mathematical model, a prototype of BIPAP system with a double-lung simulators and a BIPAP ventilator was set up for experimental study. Lastly, the study on the influences of key parameters of BIPAP system on dynamic characteristics was carried out. The study can be referred to in the development of research on BIPAP ventilation treatment and real respiratory diagnostics.
DEFF Research Database (Denmark)
Cetin, Bilge Kartal; Prasad, Neeli R.; Prasad, Ramjee
2011-01-01
In wireless sensor networks, one of the key challenge is to achieve minimum energy consumption in order to maximize network lifetime. In fact, lifetime depends on many parameters: the topology of the sensor network, the data aggregation regime in the network, the channel access schemes, the routing...... protocols, and the energy model for transmission. In this paper, we tackle the routing challenge for maximum lifetime of the sensor network. We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming...
International Nuclear Information System (INIS)
Zhang, Ning; Hu, Zhaoguang; Springer, Cecilia; Li, Yanning; Shen, Bo
2016-01-01
Highlights: • We put forward a novel bi-level integrated power system planning model. • Generation expansion planning and transmission expansion planning are combined. • The effects of two sorts of demand response in reducing peak load are considered. • Operation simulation is conducted to reflect the actual effects of demand response. • The interactions between the two levels can guarantee a reasonably optimal result. - Abstract: If all the resources in power supply side, transmission part, and power demand side are considered together, the optimal expansion scheme from the perspective of the whole system can be achieved. In this paper, generation expansion planning and transmission expansion planning are combined into one model. Moreover, the effects of demand response in reducing peak load are taken into account in the planning model, which can cut back the generation expansion capacity and transmission expansion capacity. Existing approaches to considering demand response for planning tend to overestimate the impacts of demand response on peak load reduction. These approaches usually focus on power reduction at the moment of peak load without considering the situations in which load demand at another moment may unexpectedly become the new peak load due to demand response. These situations are analyzed in this paper. Accordingly, a novel approach to incorporating demand response in a planning model is proposed. A modified unit commitment model with demand response is utilized. The planning model is thereby a bi-level model with interactions between generation-transmission expansion planning and operation simulation to reflect the actual effects of demand response and find the reasonably optimal planning result.
Mixed-integer programming methods for transportation and power generation problems
Damci Kurt, Pelin
This dissertation conducts theoretical and computational research to solve challenging problems in application areas such as supply chain and power systems. The first part of the dissertation studies a transportation problem with market choice (TPMC) which is a variant of the classical transportation problem in which suppliers with limited capacities have a choice of which demands (markets) to satisfy. We show that TPMC is strongly NP-complete. We consider a version of the problem with a service level constraint on the maximum number of markets that can be rejected and show that if the original problem is polynomial, its cardinality-constrained version is also polynomial. We propose valid inequalities for mixed-integer cover and knapsack sets with variable upper bound constraints, which appear as substructures of TPMC and use them in a branch-and-cut algorithm to solve this problem. The second part of this dissertation studies a unit commitment (UC) problem in which the goal is to minimize the operational cost of power generators over a time period subject to physical constraints while satisfying demand. We provide several exponential classes of multi-period ramping and multi-period variable upper bound inequalities. We prove the strength of these inequalities and describe polynomial-time separation algorithms. Computational results show the effectiveness of the proposed inequalities when used as cuts in a branch-and-cut algorithm to solve the UC problem. The last part of this dissertation investigates the effects of uncertain wind power on the UC problem. A two-stage robust model and a three-stage stochastic program are compared.
An optimal maintenance policy for machine replacement problem using dynamic programming
Directory of Open Access Journals (Sweden)
Mohsen Sadegh Amalnik
2017-06-01
Full Text Available In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling including renew, repair and do nothing and wish to achieve an optimal threshold for making decisions including renew, repair and continue the production in order to minimize the expected cost. Results show that the optimal policy is sensitive to the data, for the probability of defective machines and parameters defined in the model. This can be clearly demonstrated by a sensitivity analysis technique.
Mixed integer linear programming model for dynamic supplier selection problem considering discounts
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Adi Wicaksono Purnawan
2018-01-01
Full Text Available Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP was developed to overcome the dynamic supplier selection problem (DSSP. In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.
PROGRAMMING OF METHODS FOR THE NEEDS OF LOGISTICS DISTRIBUTION SOLVING PROBLEMS
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Andrea Štangová
2014-06-01
Full Text Available Logistics has become one of the dominant factors which is affecting the successful management, competitiveness and mentality of the global economy. Distribution logistics materializes the connesciton of production and consumer marke. It uses different methodology and methods of multicriterial evaluation and allocation. This thesis adresses the problem of the costs of securing the distribution of product. It was therefore relevant to design a software product thet would be helpful in solvin the problems related to distribution logistics. Elodis – electronic distribution logistics program was designed on the basis of theoretical analysis of the issue of distribution logistics and on the analysis of the software products market. The program uses a multicriterial evaluation methods to deremine the appropriate type and mathematical and geometrical method to determine an appropriate allocation of the distribution center, warehouse and company.
Introduction of problem-based learning in undergraduate dentistry program in Nepal
Rimal, Jyotsna; Paudel, Bishnu Hari; Shrestha, Ashish
2015-01-01
Context: Problem-based learning (PBL) is a methodology widely used in medical education and is growing in dental education. Initiation of new ideas and teaching methods requires a change in perception from faculty and institute management. Student-centered education is a need of the day and PBL provides the best outlet to it. Aim: To introduce PBL, assess feasibility and challenges in undergraduate dentistry program and evaluate the impact on their learning. Settings and Design: PBL was used ...
Solving a bi-objective mathematical programming model for bloodmobiles location routing problem
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Masoud Rabbani
2017-01-01
Full Text Available Perishability of platelets, uncertainty of donors’ arrival and conflicting views in platelet supply chain have made platelet supply chain planning a problematic issue. In this paper, mobile blood collection system for platelet production is investigated. Two mathematical models are presented to cover the bloodmobile collection planning problem. The first model is a multi-objective fuzzy mathematical programming in which the bloodmobiles locations are considered with the aim of maximizing potential amount of blood collection and minimizing the operational cost. The second model is a vehicle routing problem with time windows which studies the shuttles routing problem. To tackle the first model, it is reformulated as a crisp multi objective linear programming model and then solved through a fuzzy multi objective programming approach. Several sensitivity analysis are conducted on important parameters to demonstrate the applicability of the proposed model. The proposed model is then solved by using a tailored Simulated Annealing (SA algorithm. The numerical results demonstrate promising efficiency of the proposed solution method.
A Mixed Integer Programming Poultry Feed Ration Optimisation Problem Using the Bat Algorithm
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Godfrey Chagwiza
2016-01-01
Full Text Available In this paper, a feed ration problem is presented as a mixed integer programming problem. An attempt to find the optimal quantities of Moringa oleifera inclusion into the poultry feed ration was done and the problem was solved using the Bat algorithm and the Cplex solver. The study used findings of previous research to investigate the effects of Moringa oleifera inclusion in poultry feed ration. The results show that the farmer is likely to gain US$0.89 more if Moringa oleifera is included in the feed ration. Results also show superiority of the Bat algorithm in terms of execution time and number of iterations required to find the optimum solution as compared with the results obtained by the Cplex solver. Results revealed that there is a significant economic benefit of Moringa oleifera inclusion into the poultry feed ration.
Application of goal programming to decision problem on optimal allocation of radiation workers
International Nuclear Information System (INIS)
Sa, Sangduk; Narita, Masakuni
1993-01-01
This paper is concerned with an optimal planning in a multiple objective decision-making problem of allocating radiation workers to workplaces associated with occupational exposure. The model problem is formulated with the application of goal programming which effectively followed up diverse and conflicting factors influencing the optimal decision. The formulation is based on the data simulating the typical situations encountered at the operating facilities such as nuclear power plants where exposure control is critical to the management. Multiple goals set by the decision-maker/manager who has the operational responsibilities for radiological protection are illustrated in terms of work requirements, exposure constraints of the places, desired allocation of specific personnel and so on. Test results of the model are considered to indicate that the model structure and its solution process can provide the manager with a good set of analysis of his problems in implementing the optimization review of radiation protection during normal operation. (author)
A simulation based research on chance constrained programming in robust facility location problem
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Kaijun Leng
2017-03-01
Full Text Available Since facility location decisions problem include long-term character and potential parameter variations, it is important to consider uncertainty in its modeling. This paper examines robust facility location problem considering supply uncertainty, in which we assume the supply of the facility in the actual operation is not equal to the supply initially established, the supply is subject to random fluctuation. The chance constraints are introduced when formulating the robust facility location model to make sure the system operate properly with a certain probability while the supply fluctuates. The chance constraints are approximated safely by using Hoeffding’s inequality and the problem is transformed to a general deterministic linear programming. Furthermore, how the facility location cost change with confidence level is investigated through a numerical example. The sensitivity analysis is conducted for important parameters of the model and we get the main factors that affect the facility location cost.
An integer programming model for gate assignment problem at airline terminals
Chun, Chong Kok; Nordin, Syarifah Zyurina
2015-05-01
In this paper, we concentrate on a gate assignment problem (GAP) at the airlines terminal. Our problem is to assign an arrival plane to a suitable gate. There are two considerations needed to take. One of its is passenger walking distance from arrival gate to departure gate while another consideration is the transport baggage distance from one gate to another. Our objective is to minimize the total distance between the gates that related to assign the arrival plane to the suitable gates. An integer linear programming (ILP) model is proposed to solve this gate assignment problem. We also conduct a computational experiment using CPLEX 12.1 solver in AIMMS 3.10 software to analyze the performance of the model. Results of the computational experiments are presented. The efficiency of flights assignment is depends on the ratio of the weight for both total passenger traveling distances and total baggage transport distances.
A primal-dual exterior point algorithm for linear programming problems
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Samaras Nikolaos
2009-01-01
Full Text Available The aim of this paper is to present a new simplex type algorithm for the Linear Programming Problem. The Primal - Dual method is a Simplex - type pivoting algorithm that generates two paths in order to converge to the optimal solution. The first path is primal feasible while the second one is dual feasible for the original problem. Specifically, we use a three-phase-implementation. The first two phases construct the required primal and dual feasible solutions, using the Primal Simplex algorithm. Finally, in the third phase the Primal - Dual algorithm is applied. Moreover, a computational study has been carried out, using randomly generated sparse optimal linear problems, to compare its computational efficiency with the Primal Simplex algorithm and also with MATLAB's Interior Point Method implementation. The algorithm appears to be very promising since it clearly shows its superiority to the Primal Simplex algorithm as well as its robustness over the IPM algorithm.
A Two-Stage Stochastic Mixed-Integer Programming Approach to the Smart House Scheduling Problem
Ozoe, Shunsuke; Tanaka, Yoichi; Fukushima, Masao
A “Smart House” is a highly energy-optimized house equipped with photovoltaic systems (PV systems), electric battery systems, fuel cell cogeneration systems (FC systems), electric vehicles (EVs) and so on. Smart houses are attracting much attention recently thanks to their enhanced ability to save energy by making full use of renewable energy and by achieving power grid stability despite an increased power draw for installed PV systems. Yet running a smart house's power system, with its multiple power sources and power storages, is no simple task. In this paper, we consider the problem of power scheduling for a smart house with a PV system, an FC system and an EV. We formulate the problem as a mixed integer programming problem, and then extend it to a stochastic programming problem involving recourse costs to cope with uncertain electricity demand, heat demand and PV power generation. Using our method, we seek to achieve the optimal power schedule running at the minimum expected operation cost. We present some results of numerical experiments with data on real-life demands and PV power generation to show the effectiveness of our method.
Directory of Open Access Journals (Sweden)
Sunxin Wang
2014-01-01
Full Text Available This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP. Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.
Clark, Susan G.; Rutherford, Murray B.; Auer, Matthew R.; Cherney, David N.; Wallace, Richard L.; Mattson, David J.; Clark, Douglas A.; Foote, Lee; Krogman, Naomi; Wilshusen, Peter; Steelman, Toddi
2011-05-01
Environmental studies and environmental sciences programs in American and Canadian colleges and universities seek to ameliorate environmental problems through empirical enquiry and analytic judgment. In a companion article (Part 1) we describe the environmental program movement (EPM) and discuss factors that have hindered its performance. Here, we complete our analysis by proposing strategies for improvement. We recommend that environmental programs re-organize around three principles. First, adopt as an overriding goal the concept of human dignity—defined as freedom and social justice in healthy, sustainable environments. This clear higher-order goal captures the human and environmental aspirations of the EPM and would provide a more coherent direction for the efforts of diverse participants. Second, employ an explicit, genuinely interdisciplinary analytical framework that facilitates the use of multiple methods to investigate and address environmental and social problems in context. Third, develop educational programs and applied experiences that provide students with the technical knowledge, powers of observation, critical thinking skills and management acumen required for them to become effective professionals and leaders. Organizing around these three principles would build unity in the EPM while at the same time capitalizing on the strengths of the many disciplines and diverse local conditions involved.
Solving seismological problems using SGRAPH program: I-source parameters and hypocentral location
International Nuclear Information System (INIS)
Abdelwahed, Mohamed F.
2012-01-01
SGRAPH program is considered one of the seismological programs that maintain seismic data. SGRAPH is considered unique for being able to read a wide range of data formats and manipulate complementary tools in different seismological subjects in a stand-alone Windows-based application. SGRAPH efficiently performs the basic waveform analysis and solves advanced seismological problems. The graphical user interface (GUI) utilities and the Windows facilities such as, dialog boxes, menus, and toolbars simplified the user interaction with data. SGRAPH supported the common data formats like, SAC, SEED, GSE, ASCII, and Nanometrics Y-format, and others. It provides the facilities to solve many seismological problems with the built-in inversion and modeling tools. In this paper, I discuss some of the inversion tools built-in SGRAPH related to source parameters and hypocentral location estimation. Firstly, a description of the SGRAPH program is given discussing some of its features. Secondly, the inversion tools are applied to some selected events of the Dahshour earthquakes as an example of estimating the spectral and source parameters of local earthquakes. In addition, the hypocentral location of these events are estimated using the Hypoinverse 2000 program operated by SGRAPH.
Clark, S.G.; Rutherford, M.B.; Auer, M.R.; Cherney, D.N.; Wallace, R.L.; Mattson, D.J.; Clark, D.A.; Foote, L.; Krogman, N.; Wilshusen, P.; Steelman, T.
2011-01-01
Environmental studies and environmental sciences programs in American and Canadian colleges and universities seek to ameliorate environmental problems through empirical enquiry and analytic judgment. In a companion article (Part 1) we describe the environmental program movement (EPM) and discuss factors that have hindered its performance. Here, we complete our analysis by proposing strategies for improvement. We recommend that environmental programs re-organize around three principles. First, adopt as an overriding goal the concept of human dignity-defined as freedom and social justice in healthy, sustainable environments. This clear higher-order goal captures the human and environmental aspirations of the EPM and would provide a more coherent direction for the efforts of diverse participants. Second, employ an explicit, genuinely interdisciplinary analytical framework that facilitates the use of multiple methods to investigate and address environmental and social problems in context. Third, develop educational programs and applied experiences that provide students with the technical knowledge, powers of observation, critical thinking skills and management acumen required for them to become effective professionals and leaders. Organizing around these three principles would build unity in the EPM while at the same time capitalizing on the strengths of the many disciplines and diverse local conditions involved. ?? 2011 Springer Science+Business Media, LLC.
Assessment of the NASA Space Shuttle Program's Problem Reporting and Corrective Action System
Korsmeryer, D. J.; Schreiner, J. A.; Norvig, Peter (Technical Monitor)
2001-01-01
This paper documents the general findings and recommendations of the Design for Safety Programs Study of the Space Shuttle Programs (SSP) Problem Reporting and Corrective Action (PRACA) System. The goals of this Study were: to evaluate and quantify the technical aspects of the SSP's PRACA systems, and to recommend enhancements addressing specific deficiencies in preparation for future system upgrades. The Study determined that the extant SSP PRACA systems accomplished a project level support capability through the use of a large pool of domain experts and a variety of distributed formal and informal database systems. This operational model is vulnerable to staff turnover and loss of the vast corporate knowledge that is not currently being captured by the PRACA system. A need for a Program-level PRACA system providing improved insight, unification, knowledge capture, and collaborative tools was defined in this study.
Program elaborated of combined regime for on-line and off-line problems
International Nuclear Information System (INIS)
Ivanova, A.B.; Ioramashvili, Eh.Sh.; Polyakov, B.F.; Razdol'skaya, L.A.
1979-01-01
A description of the part of operational system designed for organization of packet treatment of algol tasks combined with the on-line system is provided. A block-scheme of the operational system functioning in the packet regime is presented. The ''Director'' program is the main part of the operational system which is responsible for the functioning of the algol programs. Its starting for the first time is carried out by the operator. All the subsequent process of the operation is automized. Problems connected with the organization of interruptions appearing in the cases of failures and as a reaction for the end of operation of any algol program or some of its links are considered
Stochastic Fractional Programming Approach to a Mean and Variance Model of a Transportation Problem
Directory of Open Access Journals (Sweden)
V. Charles
2011-01-01
Full Text Available In this paper, we propose a stochastic programming model, which considers a ratio of two nonlinear functions and probabilistic constraints. In the former, only expected model has been proposed without caring variability in the model. On the other hand, in the variance model, the variability played a vital role without concerning its counterpart, namely, the expected model. Further, the expected model optimizes the ratio of two linear cost functions where as variance model optimize the ratio of two non-linear functions, that is, the stochastic nature in the denominator and numerator and considering expectation and variability as well leads to a non-linear fractional program. In this paper, a transportation model with stochastic fractional programming (SFP problem approach is proposed, which strikes the balance between previous models available in the literature.
Pol, Henk J.; Harskamp, Egbert G.; Suhre, Cor J. M.; Goedhart, Martin J.
Many students experience difficulties in solving applied physics problems. Most programs that want students to improve problem-solving skills are concerned with the development of content knowledge. Physhint is an example of a student-controlled computer program that supports students in developing
International Nuclear Information System (INIS)
Wagner, R.A.
1980-12-01
This comparison study involves a preliminary verification of finite element calculations. The methodology of the comparison study consists of solving four example problems with both the SPECTROM finite element program and the MARC-CDC general purpose finite element program. The results show close agreement for all example problems
International Nuclear Information System (INIS)
Maslenikov, O.R.; Johnson, J.J.; Tiong, L.W.; Mraz, M.J.; Bumpus, S.; Gerhard, M.A.
1985-03-01
In this volume of the SMACS User's Manual an example problem is presented to demonstrate the type of problem that SMACS is capable of solving and to familiarize the user with format of the various data files involved. This volume is organized into thirteen appendices which follow a short description of the problem. Each appendix contains listings of the input and output files associated with each computer run that was necessary to solve the problem. In cases where one SMACS program uses data generated by another SMACS program, the data file is shown in the appendix for the programs which generated it
Blum, T C; Roman, P M; Harwood, E M
1995-01-01
After a brief description of employee assistance programs (EAP), we present data collected from 6,400 employees from 84 worksites who used the services of EAPs, a portion of whom were assessed by the EAP as having alcohol-related problems and/or received scores on the Alcohol Dependence Scale (ADS) indicative of a potential alcohol-related problem. In addition, data were collected at intake from the EAP administrators, and employment status of the employee clients was assessed 18 to 24 months later. These data indicate that EAPs are effective in sustaining the employment of most women with alcohol-related problems who seek services from EAPs and that EAPs' goal of early intervention is especially realized among women with alcohol problems. Other conclusions include: women with alcohol problems do not enter EAPs through routes that are strikingly different from those of men; many of the gender differences that are revealed are associated with job status differences; employed women with alcohol problems are detached from nuclear families, with markedly low rates of current marriage; even when married, spouses are less likely to play a role in the referral of women with alcohol problems than the spouses of the men; and, there is no clear indication that women are the target of any form of discrimination in the process of EAP utilization. However, women are considerably more likely to have less adequate insurance coverage, according to the EAP administrators' assessment reported at client intake, than their male counterparts, leading to treatment choices that may be less than appropriate.
International Nuclear Information System (INIS)
Hasuike, Takashi; Ishii, Hiroaki; Katagiri, Hideki
2009-01-01
This paper considers a bi-criteria general 0-1 random fuzzy programming problem based on the degree of necessity which include some previous 0-1 stochastic and fuzzy programming problems. The proposal problem is not well-defined due to including randomness and fuzziness. Therefore, by introducing chance constraint and fuzzy goals for objectives, and considering the maximization of the aspiration level for total profit and the degree of necessity that the objective function's value satisfies the fuzzy goal, the main problem is transformed into a deterministic equivalent problem. Furthermore, by using the assumption that each random variable is distributed according to a normal distribution, the problem is equivalently transformed into a basic 0-1 programming problem, and the efficient strict solution method to find an optimal solution is constructed.
Li, Yanning
2013-10-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
Takabe, Satoshi; Hukushima, Koji
2016-05-01
Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α-uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α=2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c=e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c=1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α≥3, minimum vertex covers on α-uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c=e/(α-1) where the replica symmetry is broken.
Takabe, Satoshi; Hukushima, Koji
2016-05-01
Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.
Li, Yanning; Canepa, Edward S.; Claudel, Christian G.
2013-01-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
Steepest descent method implementation on unconstrained optimization problem using C++ program
Napitupulu, H.; Sukono; Mohd, I. Bin; Hidayat, Y.; Supian, S.
2018-03-01
Steepest Descent is known as the simplest gradient method. Recently, many researches are done to obtain the appropriate step size in order to reduce the objective function value progressively. In this paper, the properties of steepest descent method from literatures are reviewed together with advantages and disadvantages of each step size procedure. The development of steepest descent method due to its step size procedure is discussed. In order to test the performance of each step size, we run a steepest descent procedure in C++ program. We implemented it to unconstrained optimization test problem with two variables, then we compare the numerical results of each step size procedure. Based on the numerical experiment, we conclude the general computational features and weaknesses of each procedure in each case of problem.
A Dynamic Programming-Based Heuristic for the Shift Design Problem in Airport Ground Handling
DEFF Research Database (Denmark)
Clausen, Tommy
We consider the heterogeneous shift design problem for a workforce with multiple skills, where work shifts are created to cover a given demand as well as possible while minimizing cost and satisfying a flexible set of constraints. We focus mainly on applications within airport ground handling whe...... programming that allows flexibility in modeling the workforce. Parameters allow a planner to determine the level of demand coverage that best fulfills the requirements of the organization. Results are presented from several diverse real-life ground handling instances.......We consider the heterogeneous shift design problem for a workforce with multiple skills, where work shifts are created to cover a given demand as well as possible while minimizing cost and satisfying a flexible set of constraints. We focus mainly on applications within airport ground handling where...
Kelle, Pido I.; Ratterman, Christian; Gibbs, Cecil
2009-01-01
This slide presentation reviews the Constellation Program Problem Reporting, Analysis and Corrective Action Process and System (Cx PRACA). The goal of the Cx PRACA is to incorporate Lessons learned from the Shuttle, ISS, and Orbiter programs by creating a single tool for managing the PRACA process, that clearly defines the scope of PRACA applicability and what must be reported, and defines the ownership and responsibility for managing the PRACA process including disposition approval authority. CxP PRACA is a process, supported by a single information gathering data module which will be integrated with a single CxP Information System, providing interoperability, import and export capability making the CxP PRACA a more effective and user friendly technical and management tool.
An evolutionary programming based simulated annealing method for solving the unit commitment problem
Energy Technology Data Exchange (ETDEWEB)
Christober Asir Rajan, C. [Department of EEE, Pondicherry Engineering College, Pondicherry 605014 (India); Mohan, M.R. [Department of EEE, Anna University, Chennai 600 025 (India)
2007-09-15
This paper presents a new approach to solve the short-term unit commitment problem using an evolutionary programming based simulated annealing method. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Evolutionary programming, which happens to be a global optimisation technique for solving unit commitment Problem, operates on a system, which is designed to encode each unit's operating schedule with regard to its minimum up/down time. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status (''flat start''). Here the parents are obtained from a pre-defined set of solution's, i.e. each and every solution is adjusted to meet the requirements. Then, a random recommitment is carried out with respect to the unit's minimum down times. And SA improves the status. The best population is selected by evolutionary strategy. The Neyveli Thermal Power Station (NTPS) Unit-II in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different power systems consists of 10, 26, 34 generating units. Numerical results are shown comparing the cost solutions and computation time obtained by using the Evolutionary Programming method and other conventional methods like Dynamic Programming, Lagrangian Relaxation and Simulated Annealing and Tabu Search in reaching proper unit commitment. (author)
Kuncoro, K. S.; Junaedi, I.; Dwijanto
2018-03-01
This study aimed to reveal the effectiveness of Project Based Learning with Resource Based Learning approach computer-aided program and analyzed problem-solving abilities in terms of problem-solving steps based on Polya stages. The research method used was mixed method with sequential explanatory design. The subject of this research was the students of math semester 4. The results showed that the S-TPS (Strong Top Problem Solving) and W-TPS (Weak Top Problem Solving) had good problem-solving abilities in each problem-solving indicator. The problem-solving ability of S-MPS (Strong Middle Problem Solving) and (Weak Middle Problem Solving) in each indicator was good. The subject of S-BPS (Strong Bottom Problem Solving) had a difficulty in solving the problem with computer program, less precise in writing the final conclusion and could not reflect the problem-solving process using Polya’s step. While the Subject of W-BPS (Weak Bottom Problem Solving) had not been able to meet almost all the indicators of problem-solving. The subject of W-BPS could not precisely made the initial table of completion so that the completion phase with Polya’s step was constrained.
Directory of Open Access Journals (Sweden)
Irene Govender
2014-07-01
Full Text Available The difficulty of learning to program has long been identified amongst novices. This study explored the benefits of teaching a problem solving strategy by comparing students’ perceptions and attitudes towards problem solving before and after the strategy was implemented in secondary schools. Based on self-efficacy theory, students’ problem solving self-efficacy as well as teachers’ self-efficacy were investigated, showing that both students’ and teachers’ self-efficacy may have benefited from the explicit instruction. This would imply that teaching problem solving explicitly should be encouraged to increase self-efficacy to program.
California's program: Indoor air problems aren't amenable to regulation
International Nuclear Information System (INIS)
Wesolowski, J.
1993-01-01
In 1982, California's legislature established an Indoor Air Quality Program (CIAQP) in the Department of Health Services to carry out research on the nature and extent of the indoor air problem (excluding industrial worksites), to find appropriate mitigation measures, and to promote and coordinate the efforts of other state agencies. Since indoor air problems usually are not amenable to regulatory solutions, regulatory authority was not included in the mandate. The program conducts research into a wide range of contaminants--radon, asbestos, formaldehyde, carbon monoxide, volatile organic compounds, environmental tobacco smoke (ETS), as well as into biological aerosols that cause such diseases as Legionnaires disease, tuberculosis, allergies, and asthma. Studies are also carried out to better understand the Sick Building Syndrome. The research includes field surveys to determine the exposure of the population to specific contaminants and experiments in the laboratory to develop protocols for reducing exposures. The research emphasizes measurement of exposure--concentration multiplied by the time a person is exposed--as opposed to measurement of concentration only
Gulland, E.-K.; Veenendaal, B.; Schut, A. G. T.
2012-07-01
Problem-solving knowledge and skills are an important attribute of spatial sciences graduates. The challenge of higher education is to build a teaching and learning environment that enables students to acquire these skills in relevant and authentic applications. This study investigates the effectiveness of traditional face-to-face teaching and online learning technologies in supporting the student learning of problem-solving and computer programming skills, techniques and solutions. The student cohort considered for this study involves students in the surveying as well as geographic information science (GISc) disciplines. Also, students studying across a range of learning modes including on-campus, distance and blended, are considered in this study. Student feedback and past studies reveal a lack of student interest and engagement in problem solving and computer programming. Many students do not see such skills as directly relevant and applicable to their perceptions of what future spatial careers hold. A range of teaching and learning methods for both face-to-face teaching and distance learning were introduced to address some of the perceived weaknesses of the learning environment. These included initiating greater student interaction in lectures, modifying assessments to provide greater feedback and student accountability, and the provision of more interactive and engaging online learning resources. The paper presents and evaluates the teaching methods used to support the student learning environment. Responses of students in relation to their learning experiences were collected via two anonymous, online surveys and these results were analysed with respect to student pass and retention rates. The study found a clear distinction between expectations and engagement of surveying students in comparison to GISc students. A further outcome revealed that students who were already engaged in their learning benefited the most from the interactive learning resources and
Directory of Open Access Journals (Sweden)
E.-K. Gulland
2012-07-01
Full Text Available Problem-solving knowledge and skills are an important attribute of spatial sciences graduates. The challenge of higher education is to build a teaching and learning environment that enables students to acquire these skills in relevant and authentic applications. This study investigates the effectiveness of traditional face-to-face teaching and online learning technologies in supporting the student learning of problem-solving and computer programming skills, techniques and solutions. The student cohort considered for this study involves students in the surveying as well as geographic information science (GISc disciplines. Also, students studying across a range of learning modes including on-campus, distance and blended, are considered in this study. Student feedback and past studies reveal a lack of student interest and engagement in problem solving and computer programming. Many students do not see such skills as directly relevant and applicable to their perceptions of what future spatial careers hold. A range of teaching and learning methods for both face-to-face teaching and distance learning were introduced to address some of the perceived weaknesses of the learning environment. These included initiating greater student interaction in lectures, modifying assessments to provide greater feedback and student accountability, and the provision of more interactive and engaging online learning resources. The paper presents and evaluates the teaching methods used to support the student learning environment. Responses of students in relation to their learning experiences were collected via two anonymous, online surveys and these results were analysed with respect to student pass and retention rates. The study found a clear distinction between expectations and engagement of surveying students in comparison to GISc students. A further outcome revealed that students who were already engaged in their learning benefited the most from the interactive
Directory of Open Access Journals (Sweden)
Yulia V. Dementieva
2016-01-01
Full Text Available The aim of the study is the description of the main problems of formation of the student’s electronic portfolio in the conditions of realization of Federal State Educational Standards of the Higher Education (FSES of HE.Methods.Theoretical analysis of scientific literature concerning the subject under discussion; monitoring of existing practices in modern Russian Universities procedures for the formation and maintenance of students electronic portfolio.Results. The author describes the main problems of the electronic students’ portfolio formation; some ways of solving described problems are offered.Scientific novelty concludes in the formation of key ideas of the electronic students’ portfolio based on the understanding of requirements of Federal State Educational Standards of Higher Education for the results of mastering educational programs. They are the formation of general cultural, general professional and professional competences.Practical significance. The researching results will become the theoretical basis for the systematic organization of the process of creating and maintaining an electronic students’ portfolio during the whole period of their studying at the university; the researching results can become a basis for methodological developments.
An integer programming formulation of the parsimonious loss of heterozygosity problem.
Catanzaro, Daniele; Labbé, Martine; Halldórsson, Bjarni V
2013-01-01
A loss of heterozygosity (LOH) event occurs when, by the laws of Mendelian inheritance, an individual should be heterozygote at a given site but, due to a deletion polymorphism, is not. Deletions play an important role in human disease and their detection could provide fundamental insights for the development of new diagnostics and treatments. In this paper, we investigate the parsimonious loss of heterozygosity problem (PLOHP), i.e., the problem of partitioning suspected polymorphisms from a set of individuals into a minimum number of deletion areas. Specifically, we generalize Halldórsson et al.'s work by providing a more general formulation of the PLOHP and by showing how one can incorporate different recombination rates and prior knowledge about the locations of deletions. Moreover, we show that the PLOHP can be formulated as a specific version of the clique partition problem in a particular class of graphs called undirected catch-point interval graphs and we prove its general $({\\cal NP})$-hardness. Finally, we provide a state-of-the-art integer programming (IP) formulation and strengthening valid inequalities to exactly solve real instances of the PLOHP containing up to 9,000 individuals and 3,000 SNPs. Our results give perspectives on the mathematics of the PLOHP and suggest new directions on the development of future efficient exact solution approaches.
An improved exploratory search technique for pure integer linear programming problems
Fogle, F. R.
1990-01-01
The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.
Ebrahimnejad, Ali
2015-08-01
There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.
Hawken, Leanne S.; O'Neill, Robert E.; MacLeod, K. Sandra
2011-01-01
The Behavior Education Program (BEP) is a check-in, check-out intervention implemented with students who are at-risk for engaging in more severe problem behavior. Previous research with middle and elementary school students found that the BEP was more effective with students who had adult attention maintained problem behavior. The purposes of this…
Govender, I.; Govender, D.; Havenga, M.; Mentz, E.; Breed, B.; Dignum, F.; Dignum, V.
2014-01-01
The difficulty of learning to program has long been identified amongst novices. This study explored the benefits of teaching a problem solving strategy by comparing students’ perceptions and attitudes towards problem solving before and after the strategy was implemented in secondary schools. Based
Sole, Marla A.
2016-01-01
Open-ended questions that can be solved using different strategies help students learn and integrate content, and provide teachers with greater insights into students' unique capabilities and levels of understanding. This article provides a problem that was modified to allow for multiple approaches. Students tended to employ high-powered, complex,…
International Nuclear Information System (INIS)
1994-01-01
Traditional International Conference on programming and mathematical methods for solution of physical problems took place in Dubna in Jun, 14-19, 1993. More than 160 scientists from 14 countries participated in the Conference. They presented about 120 reports, the range of problems including computerized information complexes, experimental data acquisition and processing systems, mathematical simulation and calculation experiment in physics, analytical and numerical methods for solution of physical problems
de Graaf, I.; Speetjens, P.; Smit, F.; de Wolff, M.; Tavecchio, L.
2008-01-01
The Triple P Positive Parenting Program is a multilevel parenting program to prevent and offer treatment for severe behavioral, emotional, and developmental problems in children. The aim of this meta-analysis is to assess the effectiveness of Triple P Level 4 interventions in the management of
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
International Nuclear Information System (INIS)
Bokanowski, Olivier; Picarelli, Athena; Zidani, Hasnaa
2015-01-01
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach
Directory of Open Access Journals (Sweden)
Diamantidis A. C.
2004-01-01
Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
Energy Technology Data Exchange (ETDEWEB)
Bokanowski, Olivier, E-mail: boka@math.jussieu.fr [Laboratoire Jacques-Louis Lions, Université Paris-Diderot (Paris 7) UFR de Mathématiques - Bât. Sophie Germain (France); Picarelli, Athena, E-mail: athena.picarelli@inria.fr [Projet Commands, INRIA Saclay & ENSTA ParisTech (France); Zidani, Hasnaa, E-mail: hasnaa.zidani@ensta.fr [Unité de Mathématiques appliquées (UMA), ENSTA ParisTech (France)
2015-02-15
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach.
TRIP: a finite element computer program for the solution of convection heat transfer problems
International Nuclear Information System (INIS)
Slagter, W.; Roodbergen, H.A.
1976-01-01
The theory and use of the finite element code TRIP are described. The code calculates temperature distributions in three-dimensional continua subjected to convection heat transfer. A variational principle for transport phenomena is applied to solve the convection heat transfer problem with temperature and heat flux boundary conditions. The finite element discretization technique is used to reduce the continuous spatial solution into a finite number of unknowns. The method is developed in detail to determine temperature distributions in coolant passages of fuel rod bundles which are idealized by hexahedral elements. The development of the TRIP code is discussed and the listing of the program is given in FORTRAN IV. An example is given to illustrate the validity and practicality of the method
A chaos-based evolutionary algorithm for general nonlinear programming problems
International Nuclear Information System (INIS)
El-Shorbagy, M.A.; Mousa, A.A.; Nasr, S.M.
2016-01-01
In this paper we present a chaos-based evolutionary algorithm (EA) for solving nonlinear programming problems named chaotic genetic algorithm (CGA). CGA integrates genetic algorithm (GA) and chaotic local search (CLS) strategy to accelerate the optimum seeking operation and to speed the convergence to the global solution. The integration of global search represented in genetic algorithm and CLS procedures should offer the advantages of both optimization methods while offsetting their disadvantages. By this way, it is intended to enhance the global convergence and to prevent to stick on a local solution. The inherent characteristics of chaos can enhance optimization algorithms by enabling it to escape from local solutions and increase the convergence to reach to the global solution. Twelve chaotic maps have been analyzed in the proposed approach. The simulation results using the set of CEC’2005 show that the application of chaotic mapping may be an effective strategy to improve the performances of EAs.
DYNAMIC PROGRAMMING APPROACH TO TESTING RESOURCE ALLOCATION PROBLEM FOR MODULAR SOFTWARE
Directory of Open Access Journals (Sweden)
P.K. Kapur
2003-02-01
Full Text Available Testing phase of a software begins with module testing. During this period modules are tested independently to remove maximum possible number of faults within a specified time limit or testing resource budget. This gives rise to some interesting optimization problems, which are discussed in this paper. Two Optimization models are proposed for optimal allocation of testing resources among the modules of a Software. In the first model, we maximize the total fault removal, subject to budgetary Constraint. In the second model, additional constraint representing aspiration level for fault removals for each module of the software is added. These models are solved using dynamic programming technique. The methods have been illustrated through numerical examples.
An Integer Programming Model for Multi-Echelon Supply Chain Decision Problem Considering Inventories
Harahap, Amin; Mawengkang, Herman; Siswadi; Effendi, Syahril
2018-01-01
In this paper we address a problem that is of significance to the industry, namely the optimal decision of a multi-echelon supply chain and the associated inventory systems. By using the guaranteed service approach to model the multi-echelon inventory system, we develop a mixed integer; programming model to simultaneously optimize the transportation, inventory and network structure of a multi-echelon supply chain. To solve the model we develop a direct search approach using a strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points.
Analysis and presentation of experimental results with examples, problems and programs
Christodoulides, Costas
2017-01-01
This book is intended as a guide to the analysis and presentation of experimental results. It develops various techniques for the numerical processing of experimental data, using basic statistical methods and the theory of errors. After presenting basic theoretical concepts, the book describes the methods by which the results can be presented, both numerically and graphically. The book is divided into three parts, of roughly equal length, addressing the theory, the analysis of data, and the presentation of results. Examples are given and problems are solved using the Excel, Origin, Python and R software packages. In addition, programs in all four languages are made available to readers, allowing them to use them in analyzing and presenting the results of their own experiments. Subjects are treated at a level appropriate for undergraduate students in the natural sciences, but this book should also appeal to anyone whose work involves dealing with experimental results.
Energy Technology Data Exchange (ETDEWEB)
Souza Filho, Erito M.; Bahiense, Laura; Ferreira Filho, Virgilio J.M. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE); Lima, Leonardo [Centro Federal de Educacao Tecnologica Celso Sukow da Fonseca (CEFET-RJ), Rio de Janeiro, RJ (Brazil)
2008-07-01
Pipeline are known as the most reliable and economical mode of transportation for petroleum and its derivatives, especially when large amounts of products have to be pumped for large distances. In this work we address the short-term schedule of a pipeline system comprising the distribution of several petroleum derivatives from a single oil refinery to several depots, connected to local consumer markets, through a single multi-product pipeline. We propose an integer linear programming formulation and a variable neighborhood search meta-heuristic in order to compare the performances of the exact and heuristic approaches to the problem. Computational tests in C language and MOSEL/XPRESS-MP language are performed over a real Brazilian pipeline system. (author)
Developing a Novel Multi-objective Programming Model for Personnel Assignment Problem
Directory of Open Access Journals (Sweden)
Mehdi Seifbarghy
2014-05-01
Full Text Available The assignment of personnel to the right positions in order to increase organization's performance is one of the most crucial tasks in human resource management. In this paper, personnel assignment problem is formulated as a multi-objective binary integer programming model in which skills, level of satisfaction and training cost of personnel are considered simultaneously in productive company. The purpose of this model is to obtain the best matching between candidates and positions. In this model, a set of methods such as a group analytic hierarchy process (GAHP, Shannon entropy, coefficient of variation (CV and fuzzy logic are used to calculate the weights of evaluation criteria, weights of position and coefficient of objective functions. This proposed model can rationalize the subjective judgments of decision makers with mathematic models.
Robust Optimization Using Supremum of the Objective Function for Nonlinear Programming Problems
International Nuclear Information System (INIS)
Lee, Se Jung; Park, Gyung Jin
2014-01-01
In the robust optimization field, the robustness of the objective function emphasizes an insensitive design. In general, the robustness of the objective function can be achieved by reducing the change of the objective function with respect to the variation of the design variables and parameters. However, in conventional methods, when an insensitive design is emphasized, the performance of the objective function can be deteriorated. Besides, if the numbers of the design variables are increased, the numerical cost is quite high in robust optimization for nonlinear programming problems. In this research, the robustness index for the objective function and a process of robust optimization are proposed. Moreover, a method using the supremum of linearized functions is also proposed to reduce the computational cost. Mathematical examples are solved for the verification of the proposed method and the results are compared with those from the conventional methods. The proposed approach improves the performance of the objective function and its efficiency
Levy Merrick, Elizabeth S.; Volpe-Vartanian, Joanna; Horgan, Constance M.; McCann, Bernard
2007-01-01
This column describes employee assistance program (EAPs) and identifies key issues for contemporary EAPs. These programs began as occupational alcohol programs and have evolved into more comprehensive resources. To better understand contemporary EAPs, the authors suggest a research agenda at includes descriptive studies to provide an up-to-date picture of services; investigations of how contemporary EAPs address substance use problems, including management consultation for early identificatio...
Benchmark problem for IAEA coordinated research program (CRP-3) on GCR afterheat removal. 1
International Nuclear Information System (INIS)
Takada, Shoji; Shiina, Yasuaki; Inagaki, Yoshiyuki; Hishida, Makoto; Sudo, Yukio
1995-08-01
In this report, detailed data which are necessary for the benchmark analysis of International Atomic Energy Agency (IAEA) Coordinated Research Program (CRP-3) on 'Heat Transport and Afterheat Removal for Gas-cooled Reactors under Accident Conditions' are described concerning about the configuration and sizes of the cooling panel test apparatus, experimental data and thermal properties. The test section of the test apparatus is composed of pressure vessel (max. 450degC) containing an electric heater (max. 100kW, 600degC) and cooling panels surrounding the pressure vessel. Gas pressure is varied from vacuum to 1.0MPa in the pressure vessel. Two experimental cases are selected as benchmark problems about afterheat removal of HTGR, described as follows, The experimental conditions are vacuum inside the pressure vessel and heater output 13.14kW, and helium gas pressure 0.73MPa inside the pressure vessel and heater output 28.79kW. Benchmark problems are to calculate temperature distributions on the outer surface of pressure vessel and heat transferred to the cooling panel using the experimental data. The analytical result of temperature distribution on the pressure vessel was estimated +38degC, -29degC compared with the experimental data, and analytical result of heat transferred from the surface of pressure vessel to the cooling panel was estimated max. -11.4% compared with the experimental result by using the computational code -THANPACST2- of JAERI. (author)
Integer 1/0 Knapsack Problem Dynamic Programming Approach in Building Maintenance Optimization
Directory of Open Access Journals (Sweden)
Viska Dewi Fawzy
2017-12-01
Full Text Available The most common problem in urban areas is the high public demand and the limited provision of housing. In meeting the needs of affordable housing for low income communities, the Government of Indonesia implements Rusunawa Project. Object of this research is Pandanarang Rusunawa. Rusunawa Pandanarang is one of the vertical housing in Cilacap that is facing deterioration issue and needs good maintenance management. This study aims at insetting priority and optimizing maintenance plan due to limited funds (limited budget and the amount of damage that must be repaired.This study uses one of the optimization methods of Dynamic Programing on the application of Integer 1/0 Knapsack Problem, to determine an schedule the maintenance activities. The Criteria that are used such as: the level of building components damage and the level of occupants participation. In the first criterion, the benefit (p is the percentage of damage that is fixed with the cost (w. While on the second criterion, the benefit (p is the percentage of occupant participation rate on the maintenance activities with the cost (w. For the budget of Rp 125.000.000, 00, it was obtained from the simulation that the value of the optimum solution on the first criterion at the 7th stage of 71.88% with total cost Rp 106.000.000, 00. At the second criterion, the value of the optimum solution at the 7th stage of 89.29% with total cost Rp 124.000.000, 00.
Fitting of full Cobb-Douglas and full VRTS cost frontiers by solving goal programming problem
Venkateswarlu, B.; Mahaboob, B.; Subbarami Reddy, C.; Madhusudhana Rao, B.
2017-11-01
The present research article first defines two popular production functions viz, Cobb-Douglas and VRTS production frontiers and their dual cost functions and then derives their cost limited maximal outputs. This paper tells us that the cost limited maximal output is cost efficient. Here the one side goal programming problem is proposed by which the full Cobb-Douglas cost frontier, full VRTS frontier can be fitted. This paper includes the framing of goal programming by which stochastic cost frontier and stochastic VRTS frontiers are fitted. Hasan et al. [1] used a parameter approach Stochastic Frontier Approach (SFA) to examine the technical efficiency of the Malaysian domestic banks listed in the Kuala Lumpur stock Exchange (KLSE) market over the period 2005-2010. AshkanHassani [2] exposed Cobb-Douglas Production Functions application in construction schedule crashing and project risk analysis related to the duration of construction projects. Nan Jiang [3] applied Stochastic Frontier analysis to a panel of New Zealand dairy forms in 1998/99-2006/2007.
Clark, S.G.; Rutherford, M.B.; Auer, M.R.; Cherney, D.N.; Wallace, R.L.; Mattson, D.J.; Clark, D.A.; Foote, L.; Krogman, N.; Wilshusen, P.; Steelman, T.
2011-01-01
The environmental sciences/studies movement, with more than 1000 programs at colleges and universities in the United States and Canada, is unified by a common interest-ameliorating environmental problems through empirical enquiry and analytic judgment. Unfortunately, environmental programs have struggled in their efforts to integrate knowledge across disciplines and educate students to become sound problem solvers and leaders. We examine the environmental program movement as a policy problem, looking at overall goals, mapping trends in relation to those goals, identifying the underlying factors contributing to trends, and projecting the future. We argue that despite its shared common interest, the environmental program movement is disparate and fragmented by goal ambiguity, positivistic disciplinary approaches, and poorly rationalized curricula, pedagogies, and educational philosophies. We discuss these challenges and the nature of the changes that are needed in order to overcome them. In a subsequent article (Part 2) we propose specific strategies for improvement. ?? 2011 Springer Science+Business Media, LLC.
Palmer, C. L.; Mayernik, M. S.; Weber, N.; Baker, K. S.; Kelly, K.; Marlino, M. R.; Thompson, C. A.
2013-12-01
The need for data curation is being recognized in numerous institutional settings as national research funding agencies extend data archiving mandates to cover more types of research grants. Data curation, however, is not only a practical challenge. It presents many conceptual and theoretical challenges that must be investigated to design appropriate technical systems, social practices and institutions, policies, and services. This presentation reports on outcomes from an investigation of research problems in data curation conducted as part of the Data Curation Education in Research Centers (DCERC) program. DCERC is developing a new model for educating data professionals to contribute to scientific research. The program is organized around foundational courses and field experiences in research and data centers for both master's and doctoral students. The initiative is led by the Graduate School of Library and Information Science at the University of Illinois at Urbana-Champaign, in collaboration with the School of Information Sciences at the University of Tennessee, and library and data professionals at the National Center for Atmospheric Research (NCAR). At the doctoral level DCERC is educating future faculty and researchers in data curation and establishing a research agenda to advance the field. The doctoral seminar, Research Problems in Data Curation, was developed and taught in 2012 by the DCERC principal investigator and two doctoral fellows at the University of Illinois. It was designed to define the problem space of data curation, examine relevant concepts and theories related to both technical and social perspectives, and articulate research questions that are either unexplored or under theorized in the current literature. There was a particular emphasis on the Earth and environmental sciences, with guest speakers brought in from NCAR, National Snow and Ice Data Center (NSIDC), and Rensselaer Polytechnic Institute. Through the assignments, students
Sandler, Irwin; Tein, Jenn-Yun; Cham, Heining; Wolchik, Sharlene; Ayers, Tim
2016-08-01
This study reports on the findings from a 6-year follow-up of a randomized trial of the Family Bereavement Program (FBP) on the outcomes for spousally bereaved parents. Spousally bereaved parents (N = 131) participated in the trial in which they were randomly assigned to receive the FBP (N = 72) or literature control (N = 59). Parents were assessed at four time points: pretest, posttest, and 11-month and 6-year follow-up. They reported on mental health problems, grief, and parenting at all four time periods. At the 6-year follow-up, parents reported on additional measures of persistent complex bereavement disorder, alcohol abuse problems, and coping efficacy. Bereaved parents in the FBP as compared to those in the literature control had lower levels of symptoms of depression, general psychiatric distress, prolonged grief, and alcohol problems, and higher coping efficacy (for mothers) at the 6-year follow-up. Multiple characteristics of the parent (e.g., gender, age, and baseline mental health problems) and of the spousal death (e.g., cause of death) were tested as moderators of program effects on each outcome, but only 3 of 45 tests of moderation were significant. Latent growth modeling found that the effects of the FBP on depression, psychiatric distress, and grief occurred immediately following program participation and were maintained over 6 years. Mediation analysis found that improvement in positive parenting partially mediated program effects to reduce depression and psychiatric distress, but had an indirect effect to higher levels of grief at the 6-year follow-up. Mediation analysis also found that improved parenting at the 6-year follow-up was partially mediated by program effects to reduce depression and that program effects to increase coping efficacy at the 6-year follow-up was partially mediated through reduced depression and grief and improved parenting. FBP reduced mental health problems, prolonged grief, and alcohol abuse, and increased coping
Jua, S. K.; Sarwanto; Sukarmin
2018-05-01
Problem-solving skills are important skills in physics. However, according to some researchers, the problem-solving skill of Indonesian students’ problem in physics learning is categorized still low. The purpose of this study was to identify the profile of problem-solving skills of students who follow the across the interests program of physics. The subjects of the study were high school students of Social Sciences, grade X. The type of this research was descriptive research. The data which used to analyze the problem-solving skills were obtained through student questionnaires and the test results with impulse materials and collision. From the descriptive analysis results, the percentage of students’ problem-solving skill based on the test was 52.93% and indicators respectively. These results indicated that students’ problem-solving skill is categorized low.
Shumway, Sterling T; Wampler, Richard S; Dersch, Charette; Arredondo, Rudy
2004-01-01
Marriage and family services have not been widely recognized as part of employee assistance programs (EAP), although family and relational problems are widely cited as sources of problems on the job. EAP clients (N = 800, 97% self-referred) indicated how much family, psychological/emotional, drug, alcohol, employment-related, legal, and medical problems troubled them and the need for services in each area. Psychological/emotional (66%) and family (65%) problem areas frequently were rated "considerable" or "extreme." Both areas were rated as "considerable" or "extreme" by 48.6% of participants. In view of the evidence that marriage and family services can be effective with both family and psychological/emotional problems, professionals who are competent to provide such services have much to offer EAP programs.
Reisine, S; Schensul, J J; Goldblatt, R; Radda, K; Foster-Bey, C; Acosta-Glynn, C; Miron-Carcamo, L; Ioannidou, E
2016-06-01
This paper describes the results of a bi-level intervention, using a cognitive-behavioral theoretical approach, to improve the oral hygiene of older adults and the disabled in community-based low income senior housing. The bi-level pilot intervention consisted of an on-site tailored adapted motivational interviewing (AMI) session and two oral health fairs, supported by a resident campaign committee, to change community norms. All materials were available in English and Spanish. Participants completed a survey consisting of 12 domains that provided the basis for tailoring the AMI and shaping the campaigns. The domains were activities of daily living (ADLs), access to oral health information, oral hygiene status, dental knowledge, hygiene behaviors, importance of oral hygiene, self-efficacy/locus of control, diet, intentions, self-management worries/fears, perceived risk and dry mouth. Each participant received clinical assessments consisting of full-mouth plaque score (PS) and gingival index (GI) before the intervention and at three months. Twenty-seven residents with at least one tooth completed all phases of the study. The mean number of domains requiring attention was 4.5 (SD 1.6) with a range of one to seven. Mean baseline PS was 83% (SD 16%) which improved significantly to 58% (SD 31%); mean baseline GI was 1.15 (SD 0.61) and improved significantly to 0.49 (SD 0.46). This pilot study supports the feasibility and acceptability of a tailored oral hygiene intervention among older and disabled adults living in low income senior housing. Although a small sample, the study demonstrated significant improvements in both plaque and gingival scores three months after the bi-level intervention.
National Research Council Canada - National Science Library
Khoo, Wai
1999-01-01
.... These problems model stochastic portfolio optimization problems (SPOPs) which assume deterministic unit weight, and normally distributed unit return with known mean and variance for each item type...
An Overview of the WIN Program: Its Objectives, Accomplishments, and Problems.
Comptroller General of the U.S., Washington, DC.
The Work Incentive (WIN) program is supposed to help recipients of Aid to Families with Dependent Children (AFDC) to get jobs through a program of training, work experience, and employment while reducing the cost of the AFDC program. Because of concerns raised about the program, the Government Accounting Office (GAO) assessed the program to…
Jackson, M A
1982-01-01
The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, thi...
Tang, Jiafu; Liu, Yang; Fung, Richard; Luo, Xinggang
2008-12-01
Manufacturers have a legal accountability to deal with industrial waste generated from their production processes in order to avoid pollution. Along with advances in waste recovery techniques, manufacturers may adopt various recycling strategies in dealing with industrial waste. With reuse strategies and technologies, byproducts or wastes will be returned to production processes in the iron and steel industry, and some waste can be recycled back to base material for reuse in other industries. This article focuses on a recovery strategies optimization problem for a typical class of industrial waste recycling process in order to maximize profit. There are multiple strategies for waste recycling available to generate multiple byproducts; these byproducts are then further transformed into several types of chemical products via different production patterns. A mixed integer programming model is developed to determine which recycling strategy and which production pattern should be selected with what quantity of chemical products corresponding to this strategy and pattern in order to yield maximum marginal profits. The sales profits of chemical products and the set-up costs of these strategies, patterns and operation costs of production are considered. A simulated annealing (SA) based heuristic algorithm is developed to solve the problem. Finally, an experiment is designed to verify the effectiveness and feasibility of the proposed method. By comparing a single strategy to multiple strategies in an example, it is shown that the total sales profit of chemical products can be increased by around 25% through the simultaneous use of multiple strategies. This illustrates the superiority of combinatorial multiple strategies. Furthermore, the effects of the model parameters on profit are discussed to help manufacturers organize their waste recycling network.
A linear programming model for protein inference problem in shotgun proteomics.
Huang, Ting; He, Zengyou
2012-11-15
Assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is an important issue in shotgun proteomics. The objective of protein inference is to find a subset of proteins that are truly present in the sample. Although many methods have been proposed for protein inference, several issues such as peptide degeneracy still remain unsolved. In this article, we present a linear programming model for protein inference. In this model, we use a transformation of the joint probability that each peptide/protein pair is present in the sample as the variable. Then, both the peptide probability and protein probability can be expressed as a formula in terms of the linear combination of these variables. Based on this simple fact, the protein inference problem is formulated as an optimization problem: minimize the number of proteins with non-zero probabilities under the constraint that the difference between the calculated peptide probability and the peptide probability generated from peptide identification algorithms should be less than some threshold. This model addresses the peptide degeneracy issue by forcing some joint probability variables involving degenerate peptides to be zero in a rigorous manner. The corresponding inference algorithm is named as ProteinLP. We test the performance of ProteinLP on six datasets. Experimental results show that our method is competitive with the state-of-the-art protein inference algorithms. The source code of our algorithm is available at: https://sourceforge.net/projects/prolp/. zyhe@dlut.edu.cn. Supplementary data are available at Bioinformatics Online.
McMillen, J Curtis; Narendorf, Sarah Carter; Robinson, Debra; Havlicek, Judy; Fedoravicius, Nicole; Bertram, Julie; McNelly, David
2015-01-01
Older youth in out-of-home care often live in restrictive settings and face psychiatric issues without sufficient family support. This paper reports on the development and piloting of a manualized treatment foster care program designed to step down older youth with high psychiatric needs from residential programs to treatment foster care homes. A team of researchers and agency partners set out to develop a treatment foster care model for older youth based on Multi-dimensional Treatment Foster Care (MTFC). After matching youth by mental health condition and determining for whom randomization would be allowed, 14 youth were randomized to treatment as usual or a treatment foster home intervention. Stakeholders were interviewed qualitatively at multiple time points. Quantitative measures assessed mental health symptoms, days in locked facilities, employment and educational outcomes. Development efforts led to substantial variations from the MTFC model and a new model, Treatment Foster Care for Older Youth was piloted. Feasibility monitoring suggested that it was difficult, but possible to recruit and randomize youth from and out of residential homes and that foster parents could be recruited to serve them. Qualitative data pointed to some qualified clinical successes. Stakeholders viewed two team roles - that of psychiatric nurse and skills coaches - very highly. However, results also suggested that foster parents and some staff did not tolerate the intervention well and struggled to address the emotion dysregulation issues of the young people they served. Quantitative data demonstrated that the intervention was not keeping youth out of locked facilities. The intervention needed further refinement prior to a broader trial. Intervention development work continued until components were developed to help address emotion regulation problems among fostered youth. Psychiatric nurses and skills coaches who work with youth in community settings hold promise as important
Graziano, Paulo A; Ros, Rosmary; Hart, Katie C; Slavec, Janine
2017-11-07
Within an at-risk sample of preschoolers with externalizing behavior problems (EBP), the current study examined the initial promise of a multimodal intervention, the Summer Treatment Program for Pre-Kindergarteners (STP-PreK), in improving parenting outcomes. Using an open trial design, 154 parents and their preschool children (73% male; M age = 5.06 years; 82% Hispanic/Latino background) with at-risk or clinically elevated levels of EBP (57% of which were referred by schools or mental health/medical professionals) completed a baseline and post-treatment assessment. A subsample of 90 families completed a follow-up assessment approximately 6 to 9 months after treatment completion. Parental measures of parenting stress and discipline strategies were collected across all three assessments. Observational data were also collected across all assessments during a 5-min standardized child-led play situation and a 5-min parent-led clean up task. The parenting component of the STP-PreK included a School Readiness Parenting Program (SRPP) of which the behavioral management component was implemented via a Parent-Child Interaction Therapy (PCIT) adaptation (8 weekly group sessions with 15-20 parents in each group, lack of requirement of "mastery" criteria). All parenting outcomes (both ratings and observed) significantly improved after the intervention (Cohen's d mean effect size across measures 0.89) with all effects being maintained at the 6-9 month follow-up. These findings highlight the initial promise of our SRPP's PCIT adaptation in targeting multiple aspects of parenting while yielding comparable parenting skills acquisition compared to traditional individual PCIT.
Fong, Kenneth N K; Howie, Dorothy R
2009-01-01
We investigated the effects of an explicit problem-solving skills training program using a metacomponential approach with 33 outpatients with moderate acquired brain injury, in the Hong Kong context. We compared an experimental training intervention with this explicit problem-solving approach, which taught metacomponential strategies, with a conventional cognitive training approach that did not have this explicit metacognitive training. We found significant advantages for the experimental group on the Metacomponential Interview measure in association with the explicit metacomponential training, but transfer to the real-life problem-solving measures was not evidenced in statistically significant findings. Small sample size, limited time of intervention, and some limitations with these tools may have been contributing factors to these results. The training program was demonstrated to have a significantly greater effect than the conventional training approach on metacomponential functioning and the component of problem representation. However, these benefits were not transferable to real-life situations.
Error Analysis Of Students Working About Word Problem Of Linear Program With NEA Procedure
Santoso, D. A.; Farid, A.; Ulum, B.
2017-06-01
Evaluation and assessment is an important part of learning. In evaluation process of learning, written test is still commonly used. However, the tests usually do not following-up by further evaluation. The process only up to grading stage not to evaluate the process and errors which done by students. Whereas if the student has a pattern error and process error, actions taken can be more focused on the fault and why is that happen. NEA procedure provides a way for educators to evaluate student progress more comprehensively. In this study, students’ mistakes in working on some word problem about linear programming have been analyzed. As a result, mistakes are often made students exist in the modeling phase (transformation) and process skills (process skill) with the overall percentage distribution respectively 20% and 15%. According to the observations, these errors occur most commonly due to lack of precision of students in modeling and in hastiness calculation. Error analysis with students on this matter, it is expected educators can determine or use the right way to solve it in the next lesson.
Win, Ni Ni; Nadarajah, Vishna Devi V; Win, Daw Khin
2015-01-01
Problem-based learning (PBL) is usually conducted in small-group learning sessions with approximately eight students per facilitator. In this study, we implemented a modified version of PBL involving collaborative groups in an undergraduate chiropractic program and assessed its pedagogical effectiveness. This study was conducted at the International Medical University, Kuala Lumpur, Malaysia, and involved the 2012 chiropractic student cohort. Six PBL cases were provided to chiropractic students, consisting of three PBL cases for which learning resources were provided and another three PBL cases for which learning resources were not provided. Group discussions were not continuously supervised, since only one facilitator was present. The students' perceptions of PBL in collaborative groups were assessed with a questionnaire that was divided into three domains: motivation, cognitive skills, and perceived pressure to work. Thirty of the 31 students (97%) participated in the study. PBL in collaborative groups was significantly associated with positive responses regarding students' motivation, cognitive skills, and perceived pressure to work (Plearning resources increased motivation and cognitive skills (Plearning resources.
The problems and solutions of predicting participation in energy efficiency programs
International Nuclear Information System (INIS)
Davis, Alexander L.; Krishnamurti, Tamar
2013-01-01
Highlights: • Energy efficiency pilot studies suffer from severe volunteer bias. • We formulate an approach for accommodating volunteer bias. • A short questionnaire and classification trees can control for the bias. - Abstract: This paper discusses volunteer bias in residential energy efficiency studies. We briefly evaluate the bias in existing studies. We then show how volunteer bias can be corrected when not avoidable, using an on-line study of intentions to enroll in an in-home display trial as an example. We found that the best predictor of intentions to enroll was expected benefit from the in-home display. Constraints on participation, such as time in the home and trust in scientists, were also associated with enrollment intentions. Using Breiman’s classification tree algorithm we found that the best model of intentions to enroll contained only five variables: expected enjoyment of the program, presence in the home during morning hours, trust (in friends and in scientists), and perceived ability to handle unexpected problems. These results suggest that a short questionnaire, that takes at most 1 min to complete, would allow better control of volunteer bias than a more extensive questionnaire. This paper should allow researchers who employ field studies involving human behavior to be better equipped to address volunteer bias
Gassman-Pines, Anna; Godfrey, Erin B; Yoshikawa, Hirokazu
2013-01-01
Grounded in person-environment fit theory, this study examined whether low-income mothers' preferences for education moderated the effects of employment- and education-focused welfare programs on children's positive and problem behaviors. The sample included 1,365 families with children between ages 3 and 5 years at study entry. Results 5 years after random assignment, when children were ages 8-10 years, indicated that mothers' education preferences did moderate program impacts on teacher-reported child behavior problems and positive behavior. Children whose mothers were assigned to the education program were rated by teachers to have less externalizing behavior and more positive behavior than children whose mothers were assigned to the employment program but only when mothers had strong preferences for education. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.
Directory of Open Access Journals (Sweden)
Reza Hosnavi Atashgah
2013-06-01
Full Text Available Selecting from a pool of interdependent projects under certainty, when faced with resource constraints, has been studied well in the literature of project selection problem. After briefly reviewing and discussing popular modeling approaches for dealing with uncertainty, this paper proposes an approach based on chance constrained programming and utility theory for a certain range of problems and under some practical assumptions. Expected Utility Programming, as the proposed modeling approach, will be compared with other well-known methods and its meaningfulness and usefulness will be illustrated via two numerical examples and one real case.
Sutrisno; Widowati; Sunarsih; Kartono
2018-01-01
In this paper, a mathematical model in quadratic programming with fuzzy parameter is proposed to determine the optimal strategy for integrated inventory control and supplier selection problem with fuzzy demand. To solve the corresponding optimization problem, we use the expected value based fuzzy programming. Numerical examples are performed to evaluate the model. From the results, the optimal amount of each product that have to be purchased from each supplier for each time period and the optimal amount of each product that have to be stored in the inventory for each time period were determined with minimum total cost and the inventory level was sufficiently closed to the reference level.
Lyubetsky, Vassily; Gershgorin, Roman; Gorbunov, Konstantin
2017-12-06
Chromosome structure is a very limited model of the genome including the information about its chromosomes such as their linear or circular organization, the order of genes on them, and the DNA strand encoding a gene. Gene lengths, nucleotide composition, and intergenic regions are ignored. Although highly incomplete, such structure can be used in many cases, e.g., to reconstruct phylogeny and evolutionary events, to identify gene synteny, regulatory elements and promoters (considering highly conserved elements), etc. Three problems are considered; all assume unequal gene content and the presence of gene paralogs. The distance problem is to determine the minimum number of operations required to transform one chromosome structure into another and the corresponding transformation itself including the identification of paralogs in two structures. We use the DCJ model which is one of the most studied combinatorial rearrangement models. Double-, sesqui-, and single-operations as well as deletion and insertion of a chromosome region are considered in the model; the single ones comprise cut and join. In the reconstruction problem, a phylogenetic tree with chromosome structures in the leaves is given. It is necessary to assign the structures to inner nodes of the tree to minimize the sum of distances between terminal structures of each edge and to identify the mutual paralogs in a fairly large set of structures. A linear algorithm is known for the distance problem without paralogs, while the presence of paralogs makes it NP-hard. If paralogs are allowed but the insertion and deletion operations are missing (and special constraints are imposed), the reduction of the distance problem to integer linear programming is known. Apparently, the reconstruction problem is NP-hard even in the absence of paralogs. The problem of contigs is to find the optimal arrangements for each given set of contigs, which also includes the mutual identification of paralogs. We proved that these
Bierman, Karen L.
2012-01-01
Childhood conduct problems are predictive of a number of serious long-term difficulties (e.g., school failure, delinquent behavior, and mental health problems), making the design of effective prevention programs a priority. The Fast Track Program is a demonstration project currently underway in four demographically diverse areas of the United States, testing the feasibility and effectiveness of a comprehensive, multicomponent prevention program targeting children at risk for conduct disorders. This paper describes some lessons learned about the implementation of this program in a rural area. Although there are many areas of commonality in terms of program needs, program design, and implementation issues in rural and urban sites, rural areas differ from urban areas along the dimensions of geographical dispersion and regionalism, and community stability and insularity. Rural programs must cover a broad geographical area and must be sensitive to the multiple, small and regional communities that constitute their service area. Small schools, homogeneous populations, traditional values, limited recreational, educational and mental health services, and politically conservative climates are all more likely to emerge as characteristics of rural rather than urban sites (Sherman, 1992). These characteristics may both pose particular challenges to the implementation of prevention programs in rural areas, as well as offer particular benefits. Three aspects of program implementation are described in detail: (a) community entry and program initiation in rural areas, (b) the adaptation of program components and service delivery to meet the needs of rural families and schools, and (c) issues in administrative organization of a broadly dispersed tricounty rural prevention program. PMID:9338956
A bilevel model for electricity retailers' participation in a demand response market environment
DEFF Research Database (Denmark)
Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre
2013-01-01
(followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal......-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility....
Energy Technology Data Exchange (ETDEWEB)
Korotkov, S F; Khalitov, N T
1965-01-01
he quadratic method of programming is used to solve the following type of problem. A circular reservoir is subjected to a peripheral waterflood. The reservoir is drained by wells arranged in 3 concentric circles. The objective is to control the operation of producing wells, that a maximum quantity of water-free oil will be produced. The wells are flowed so that bottomhole pressure is above the bubble point. A quadratic equation is used to express the essential features of the problem; a system of linear equations is used to express the boundary conditions. The problem is solved by means of the Wolf algorithm method. The method is demonstrated by an illustrative example.
Merrick, Elizabeth S Levy; Volpe-Vartanian, Joanna; Horgan, Constance M; McCann, Bernard
2007-10-01
This column describes employee assistance program (EAPs) and identifies key issues for contemporary EAPs. These programs began as occupational alcohol programs and have evolved into more comprehensive resources. To better understand contemporary EAPs, the authors suggest a research agenda that includes descriptive studies to provide an up-to-date picture of services; investigations of how contemporary EAPs address substance use problems, including management consultation for early identification; further study of EAPs' effects on outcomes, such as productivity and work group outcomes; examination of the relationship between EAPs and other workplace resources; further examination of influences on EAP utilization; and development and testing of EAP performance measures.
Levy Merrick, Elizabeth S.; Volpe-Vartanian, Joanna; Horgan, Constance M.; McCann, Bernard
2012-01-01
This column describes employee assistance program (EAPs) and identifies key issues for contemporary EAPs. These programs began as occupational alcohol programs and have evolved into more comprehensive resources. To better understand contemporary EAPs, the authors suggest a research agenda at includes descriptive studies to provide an up-to-date picture of services; investigations of how contemporary EAPs address substance use problems, including management consultation for early identification; further study of EAPs’ effects on outcomes, such as productivity and work group outcomes; examination of the relationship between EAPs and other workplace resources; further examination of influences on EAP utilization; and development and testing of EAP performance measures. PMID:17914000
A constraint programming solution for the military unit path finding problem
CSIR Research Space (South Africa)
Leenen, L
2012-01-01
Full Text Available In this chapter the authors present an algorithm to solve the Dynamic Military Unit Path Finding Problem (DMUPFP) which is based on Stentz’s well-known D* algorithm to solve dynamic path finding problems. The Military Unit Path Finding Problem...
Urselmann, Maren; Emmerich, Michael T. M.; Till, Jochen; Sand, Guido; Engell, Sebastian
2007-07-01
Engineering optimization often deals with large, mixed-integer search spaces with a rigid structure due to the presence of a large number of constraints. Metaheuristics, such as evolutionary algorithms (EAs), are frequently suggested as solution algorithms in such cases. In order to exploit the full potential of these algorithms, it is important to choose an adequate representation of the search space and to integrate expert-knowledge into the stochastic search operators, without adding unnecessary bias to the search. Moreover, hybridisation with mathematical programming techniques such as mixed-integer programming (MIP) based on a problem decomposition can be considered for improving algorithmic performance. In order to design problem-specific EAs it is desirable to have a set of design guidelines that specify properties of search operators and representations. Recently, a set of guidelines has been proposed that gives rise to so-called Metric-based EAs (MBEAs). Extended by the minimal moves mutation they allow for a generalization of EA with self-adaptive mutation strength in discrete search spaces. In this article, a problem-specific EA for process engineering task is designed, following the MBEA guidelines and minimal moves mutation. On the background of the application, the usefulness of the design framework is discussed, and further extensions and corrections proposed. As a case-study, a two-stage stochastic programming problem in chemical batch process scheduling is considered. The algorithm design problem can be viewed as the choice of a hierarchical decision structure, where on different layers of the decision process symmetries and similarities can be exploited for the design of minimal moves. After a discussion of the design approach and its instantiation for the case-study, the resulting problem-specific EA/MIP is compared to a straightforward application of a canonical EA/MIP and to a monolithic mathematical programming algorithm. In view of the
DEFF Research Database (Denmark)
Schow, Trine; Harris, Paul; Teasdale, Thomas William
2016-01-01
Trine Schow, Paul Harris, Thomas William Teasdale, Morten Arendt Rasmussen. Evaluation of a four month rehabilitation program for stroke patients with balance problems and binocular visual dysfunction. NeuroRehabilitation. 2016 Apr 6;38(4):331-41. doi: 10.3233/NRE-161324....
Brody, Z. H.
The paper describes transportation problems encountered and solutions employed in delivering systems of comprehensive services to handicapped children in Anderson County, Tennessee, a predominantly rural area with considerable mountain area. Detailed are methods of transportation utilized in the four different program areas of the county special…
de Koning, Bjorn B.; Loyens, Sofie M. M.; Rikers, Remy M. J. P.; Smeets, Guus; van der Molen, Henk T.
2012-01-01
This study investigated the simultaneous impact of demographic, personality, intelligence, and (prior) study performance factors on students' academic achievement in a three-year academic problem-based psychology program. Information regarding students' gender, age, nationality, pre-university education, high school grades, Big Five personality…
International Nuclear Information System (INIS)
1991-01-01
This report discusses the following topics: brief description of the Oak Ridge Reservation Environmental Restoration Program; descriptions of representative waste burials at each site; ongoing, planned, or potential remediation; known or anticipated remediation problems; potential applications for robotics in the remediation of Oak Ridge Reservation landfills
International Nuclear Information System (INIS)
Callahan, G.D.; Fossum, A.F.
1982-11-01
General plasticity theory and solution techniques as are currently employed in RE/SPEC's finite element plasticity code SPECTROM-II are presented. Various yield functions are discussed and their differences are illustrated using example problems. Comparison of the results of SPECTROM-II with analytical solutions, numerical solutions, and the general purpose finite element program MARC-CDC show excellent agreement
Domínguez, Luis F.
2012-06-25
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear programming subproblem and a mixed-integer nonlinear programming subproblem to provide a series of parametric upper and lower bounds. The primal subproblem is formulated by fixing the integer variables and solved through a series of multiparametric quadratic programming (mp-QP) problems based on quadratic approximations of the objective function, while the deterministic master subproblem is formulated so as to provide feasible integer solutions for the next primal subproblem. To reduce the computational effort when infeasibilities are encountered at the vertices of the critical regions (CRs) generated by the primal subproblem, a simplicial approximation approach is used to obtain CRs that are feasible at each of their vertices. The algorithm terminates when there does not exist an integer solution that is better than the one previously used by the primal problem. Through a series of examples, the proposed algorithm is compared with a multiparametric mixed-integer outer approximation (mp-MIOA) algorithm to demonstrate its computational advantages. © 2012 American Institute of Chemical Engineers (AIChE).
Nara, Jun
2010-01-01
This research explores how chief cabin crew members of major airlines made their decisions on-the-spot when they had unexpected problems. This research also presents some insights that may improve personnel training programs for future stewardesses and stewards based on the investigation of their decision-making styles. The theoretical framework…
This article examines the development and implementation of the NOx Budget Trading Program (NBP) and the lessons the Environmental Protection Agency has learned from this seasonal emissions cap-and-trade program.
Sampaio, Filipa; Enebrink, Pia; Mihalopoulos, Cathrine; Feldman, Inna
2016-12-01
Parenting programs and self-help parenting interventions employing written materials are effective in reducing child conduct problems (CP) in the short-term compared to control groups, however evidence on the cost-effectiveness of such interventions is insufficient. Few studies have looked at the differences in effects between interventions in the same study design. This study aimed to determine the cost-effectiveness of four parenting programs: Comet, Incredible Years (IY), Cope and Connect, and bibliotherapy, compared to a waitlist control (WC), with a time horizon of 4 months, targeting CP in children aged 3-12 years. This economic evaluation was conducted alongside an RCT of the four parenting interventions and bibliotherapy compared to a WC. The study sample consisted of 961 parents of 3-12 year-old children with CP. CP was measured by the Eyberg Child Behavior Inventory. Effectiveness was expressed as the proportion of "recovered" cases of CP. The time horizon of the study was four months with a limited health sector perspective, including parents' time costs. We performed an initial comparative cost analysis for interventions whose outcomes differed significantly from the WC, and later a cost-effectiveness analysis of interventions whose outcomes differed significantly from both the WC and each other. Secondary analyses were performed: (i) joint outcome "recovered and improved", (ii) intervention completers, (iii) exclusion of parents' time costs, (iv) exclusion of training costs. All interventions apart from Connect significantly reduced CP compared to the WC. Of the other interventions Comet resulted in a significantly higher proportion of recovered cases compared to bibliotherapy. A comparative cost analysis of the effective interventions rendered an average cost per recovered case for bibliotherapy of USD 483, Cope USD 1972, Comet USD 3741, and IY USD 6668. Furthermore, Comet had an ICER of USD 8375 compared to bibliotherapy. Secondary analyses of
Program Evaluation of a Special Education Day School for Conduct Problem Adolescents.
Maher, Charles A.
1981-01-01
Describes a procedure for program evaluation of a special education day school. The procedure enables a program evaluator to: (1) identify priority evaluation information needs of a school staff, (2) involve those persons in evaluation design and implementation, and (3) determine the utility of the evaluation for program decision-making purposes.…
Toledo, Raciel Yera; Mota, Yailé Caballero
2014-01-01
The paper proposes a recommender system approach to cover online judge's domains. Online judges are e-learning tools that support the automatic evaluation of programming tasks done by individual users, and for this reason they are usually used for training students in programming contest and for supporting basic programming teachings. The…
de Graaf, Ireen; Speetjens, Paula; Smit, Filip; de Wolff, Marianne; Tavecchio, Louis
2008-09-01
The Triple P Positive Parenting Program is a multilevel parenting program to prevent and offer treatment for severe behavioral, emotional, and developmental problems in children. The aim of this meta-analysis is to assess the effectiveness of Triple P Level 4 interventions in the management of behavioral problems in children by pooling the evidence from relevant literature that included Level 4 Triple P interventions. Level 4 intervention is indicated if the child has multiple behavior problems in a variety of settings and there are clear deficits in parenting skills. Results indicate that Level 4 of Triple P interventions reduced disruptive behaviors in children. These improvements were maintained well over time, with further improvements in long-term follow-up. These effects support the widespread adoption and implementation of Triple P that is taking place in an increasing number of countries in quite diverse cultural contexts around the world.
Canepa, Edward S.; Claudel, Christian G.
2012-01-01
This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.
Canepa, Edward S.
2012-09-01
This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.
Directory of Open Access Journals (Sweden)
Ali Alavi
2008-07-01
Full Text Available "n "n "nObjective: "nSchool-based interventions (such as life skills training have become the mainstay for prevention of some behavioral problems. This study was conducted to evaluate the efficacy of a social skills training program on a group of students who were in the first grade of high school in an urban area of Tehran, Iran "n "n "nMethod: "nIn a before-after study, a kind of social skill education program named Right Choices" was used for high school female students. The entire students of a class in a high school participated in the study. The students' age ranged from 14-16 years. All of the participants lived in an urban area. Demographic characteristics were recorded in a designed questionnaire and included the name, age, educational level of the students and their parents, and prior history of psychiatric and medical condition. The total problem score and each of the subscale scores of the students before and after the study were calculated and compared. "n "n "nResults: "nThe mean age of the 33 participants in the study whose SDQ answer sheets were completed was equal to 15.15±6.2 years (14 to 17 years. The mean total problem score of the participants in the beginning of the program was equal to 14.3±5. After the program, the students' total problem score and all of the subscale scores improved, however, the differences between pre- and post intervention scores were not statistically significant. "n "n "nConclusion: "nSocial skills training program may impact the problem behaviors of the adolescent girls.
Java programming fundamentals problem solving through object oriented analysis and design
Nair, Premchand S
2008-01-01
While Java texts are plentiful, it's difficult to find one that takes a real-world approach, and encourages novice programmers to build on their Java skills through practical exercise. Written by an expert with 19 experience teaching computer programming, Java Programming Fundamentals presents object-oriented programming by employing examples taken from everyday life. Provides a foundation in object-oriented design principles and UML notation Describes common pitfalls and good programming practicesFurnishes supplemental links, documents, and programs on its companion website, www.premnair.netU
Directory of Open Access Journals (Sweden)
J. Fabian Lopez
2010-01-01
Full Text Available We consider a Pickup and Delivery Vehicle Routing Problem (PDP commonly encountered in real-world logistics operations. The problem involves a set of practical complications that have received little attention in the vehicle routing literature. In this problem, there are multiple vehicle types available to cover a set of pickup and delivery requests, each of which has pickup time windows and delivery time windows. Transportation orders and vehicle types must satisfy a set of compatibility constraints that specify which orders cannot be covered by which vehicle types. In addition we include some dock service capacity constraints as is required on common real world operations. This problem requires to be attended on large scale instances (orders ≥ 500, (vehicles ≥ 150. As a generalization of the traveling salesman problem, clearly this problem is NP-hard. The exact algorithms are too slow for large scale instances. The PDP-TWDS is both a packing problem (assign order to vehicles, and a routing problem (find the best route for each vehicle. We propose to solve the problem in three stages. The first stage constructs initials solutions at aggregate level relaxing some constraints on the original problem. The other two stages imposes time windows and dock service constraints. Our results are favorable finding good quality solutions in relatively short computational times.
Miles, Margaret Shandor
2003-01-01
This review identified nurse researchers and research teams that have current programs of research focused on parents and parenting of children with chronic health problems. Researchers were included if they had at least five publications since 1990, with at least three of these articles first-authored. These programs of research were critiqued from a developmental science perspective. Multiple methods were used for the search, including examination of previous review articles, hand search of journals, online computer searches, and review of the curriculum vitae of authors. Seven programs of research were identified. Two programs of research focused on childhood cancer--Ida M. Martinson et al. and Marsha H. Cohen. Three programs of research used a noncategorical approach encompassing a variety of childhood chronic conditions--Katherine A. Knafl and Janet A. Deatrick, Sharon O. Burke, and Ann Garwick. One program focused primarily on parents of children with Down syndrome and disabilities--Marsha Van Riper--and another on parents of infants with a variety of chronic health problems--Margaret S. Miles and Diane Holditch-Davis. Diverse theories and conceptual frameworks were used, and most had some focus on ecological systems that might affect parents and parenting. Many used a family perspective and included fathers. Still broader aspects of the family and community ecology and the health care were not generally included. Few examined the bidirectionality of the relationship between the child and aspects of the child's illness and parental responses. There was variability in the extent to which ethnicity and socioeconomic status were considered. Studies provide important insight into the responses of parents and their parenting of children with chronic health problems. The studies provide a sound base for continuing to build a developmentally sensitive body of knowledge related to parents and parenting of the child with chronic health problems.
An integer programming model for a forest harvest problem in Pinus pinaster stands
Energy Technology Data Exchange (ETDEWEB)
Fonseca, T. F.; Cerveira, A.; Mota, A.
2012-11-01
The study addresses the special case of a management plan for maritime pine (Pinus pinaster Ait.) in common lands. The study area refers to 4,432 ha of maritime pine stands in North Portugal (Perimetro Florestal do Barroso in the county of Ribeira de Pena), distributed among five common lands called baldio areas. Those lands are co-managed by the Official Forest Services and the local communities, essentially for timber production, using empirical guidance. As the current procedure does not guarantee the best thinning and clear-cutting scheduling, it was considered important to develop easy-to-use models, supported by optimization techniques, to be employed by the forest managers in the harvest planning of these communitarian forests. Planning of the thinning and clear-cutting operations involved certain conditions, such as: (1) the optimal age for harvesting; (2) the maximum stand density permitted; (3) the minimum volume to be cut; (4) the guarantee of incomes for each of the five baldios in at least a two year period; (5) balanced incomes during the length of the projection period. In order to evaluate the sustainability of the wood resources, a set of constraints lower bounding the average ending age was additionally tested. The problem was formulated as an integer linear programming model where the incomes from thinning and clear-cutting are maximized while considering the constraints mentioned above. Five major scenarios were simulated. The simplest one allows for silvicultural constraints only, whereas the other four consider these constraints besides different management options. Two of them introduce joint management of all common areas with or without constraints addressing balanced distribution of incomes during the plan horizon, whilst the other two consider the same options but for individual management of the baldios. The proposed model is easy to apply, providing immediate advantages for short and mid-term planning periods compared to the empirical
Studies of radiant heat transfer problems by the MOXY-program
International Nuclear Information System (INIS)
Wennerberg, D.; Thiede, M.
1988-01-01
MOXY is a program for calculation of transients at LOCA in a BWR. The program has been enlarged for application to 9 x 9 bundles (earlier only 7 x 7 - and 8 x 8 geometries). The report presents the results of five runs, two cases for 8 x 8 -bundle and three for 9 x 9 bundle. Comparison is made with estimates made by other, similar programs. (O.S.)
Jacobson, Jodi M; Sacco, Paul
2012-01-01
Fourteen million U.S. workers meet the diagnostic criteria for substance dependence, costing millions in lost productivity. Prior research suggests that employees who follow through with their Employee Assistance Program's (EAP) recommendations are more likely to participate and remain engaged in alcohol and other drug (AOD) treatment programs. This study identified rates of lifetime EAP service use for AOD problems and compared adults who reported using EAP services for AOD problems with those who used services other than EAP. Researchers analyzed a subset of participants from the National Epidemiologic Survey of Alcohol and Related Conditions who reported having received help for an AOD problem (NESARC, 2001-2002). Statistical analyses tested for differences in sociodemographic variables, lifetime mental health and substance abuse disorders, and health disability between EAP services users and users of other types of services. Among adults who sought services for AOD problems (n= 2,272), 7.58% (n= 166) reported using EAP services for these problems at some point during their lives. Major depressive disorder (lifetime), a drug use disorder (lifetime), and Black race/ethnicity were associated with a greater likelihood that someone would seek EAP services for help with their AOD problem. Results provide a foundation for researchers to understand who uses EAP services for AOD problems. Health and mental health professionals should increase their knowledge of EAP services to improve continuity of care for employees with AOD problems. EAPs are in a unique position to reach out to vulnerable employees in the workplace and engage them in treatment. Copyright © American Academy of Addiction Psychiatry.
Junqueira, Marcelle Aparecida de Barros; Rassool, G Hussein; Santos, Manoel Antônio dos; Pillon, Sandra Cristina
2015-01-01
Nurses are the prime movers in the prevention and harm reduction in alcohol-related harm especially for those patients who are unwilling to access specialist care. The aim of the study is to evaluate the attitudes and knowledge of nursing students before and after Brief Intervention Training for alcohol problems. A quasi-experimental study was conducted with 120 undergraduate nursing students. Sixty recruited students were randomized into experimental and control groups (n = 60 each). Participants completed questionnaires on knowledge and attitudes before and after this training of brief intervention. The brief intervention program, 16 hours of duration, includes training for screening and early recognition, nursing, and the treatment of alcohol problems. Analysis of the data showed statistically significant positive change in the nursing students' knowledge (identifications and care) and personal and professional attitudes in working with patients with alcohol problems after the educational intervention. The experimental group differed significantly in all the variables measured at posteducational program. The provision of educational program on brief intervention in undergraduate nursing education can be an effective way for acquisition of knowledge and changes in attitudes in working with patients with alcohol problems.
The Orienteering Problem under Uncertainty Stochastic Programming and Robust Optimization compared
L. Evers (Lanah); K.M. Glorie (Kristiaan); S. van der Ster (Suzanne); A.I. Barros (Ana); H. Monsuur (Herman)
2012-01-01
textabstractThe Orienteering Problem (OP) is a generalization of the well-known traveling salesman problem and has many interesting applications in logistics, tourism and defense. To reflect real-life situations, we focus on an uncertain variant of the OP. Two main approaches that deal with
Florida State Legislature, Tallahassee. Office of Program Policy Analysis and Government Accountability.
The Florida legislature has passed several reforms designed to shorten the time it takes students to obtain their degrees. Although the reforms have produced benefits, some articulation problems continue. The problems include the following: (1) One in five (20%) AA transfer students take a semester or more of lower division courses at a…
Investigating Problem-Based Learning Tutorship in Medical and Engineering Programs in Malaysia
Servant, Virginie F. C.; Dewar, Eleanor F. A.
2015-01-01
Although Malaysia was the first country in Asia to adopt problem-based learning (PBL), the impact that this has had on its tutors remains largely unexplored. This paper details a qualitative study of the changing perceptions of teaching roles in two groups of problem-based learning tutors in two institutional contexts--one in medicine located in…
Tausendfreund, Tim; Knot-Dickscheit, Jana; Post, Wendy J.; Knorth, Erik J.; Grietens, Hans
2014-01-01
Families who face a multitude of severe and persistent problems in a number of different areas of life are commonly referred to as multi-problem families in Dutch child welfare. Although evidence suggests that short-term crisis interventions can have positive effects in these families, they have up
Fire Problems in High-Rise Buildings. California Fire Service Training Program.
California State Dept. of Education, Sacramento. Bureau of Industrial Education.
Resulting from a conference concerned with high-rise fire problems, this manual has been prepared as a fire department training manual and as a reference for students enrolled in fire service training courses. Information is provided for topics dealing with: (1) Typical Fire Problems in High-Rise Buildings, (2) Heat, (3) Smoke and Fire Gases, (4)…
Backtrack Programming: A Computer-Based Approach to Group Problem Solving.
Scott, Michael D.; Bodaken, Edward M.
Backtrack problem-solving appears to be a viable alternative to current problem-solving methodologies. It appears to have considerable heuristic potential as a conceptual and operational framework for small group communication research, as well as functional utility for the student group in the small group class or the management team in the…
A dynamic programming algorithm for the space allocation and aisle positioning problem
DEFF Research Database (Denmark)
Bodnar, Peter; Lysgaard, Jens
2014-01-01
The space allocation and aisle positioning problem (SAAPP) in a material handling system with gravity flow racks is the problem of minimizing the total number of replenishments over a period subject to practical constraints related to the need for aisles granting safe and easy access to storage...
The Orienteering Problem under Uncertainty Stochastic Programming and Robust Optimization compared
Evers, L.; Glorie, K.; Ster, S. van der; Barros, A.I.; Monsuur, H.
2012-01-01
The Orienteering Problem (OP) is a generalization of the well-known traveling salesman problem and has many interesting applications in logistics, tourism and defense. To reflect real-life situations, we focus on an uncertain variant of the OP. Two main approaches that deal with optimization under
Jeong, In Ju; Kim, Soo Jin
2017-04-01
The purpose of this study was to examine the effects of a group counseling program based on goal attainment theory on self-esteem, interpersonal relationships, and school adjustment of middle school students with emotional and behavioral problems. Forty-four middle school students with emotional and behavioral problems (22 in the experimental group and 22 in the control group) from G city participated in this study. Data were collected from July 30 to September 24, 2015. The experimental group received the 8-session program, scheduled once a week, with each session lasting 45 minutes. Outcome variables included self-esteem, interpersonal relationship, and school adjustment. There were significant increases for self-esteem (t=3.69, p=.001), interpersonal relationship (t=8.88, pgroup compared to the control group. These results indicate that the group counseling program based on goal attainment theory is very effective in increasing self-esteem, interpersonal relationship, and school adjustment for middle school students with emotional and behavioral problems. Therefore, it is recommended that the group counseling program based on goal attainment theory be used as an effective psychiatric nursing intervention for mental health promotion and the prevention of mental illness in adolescents. © 2017 Korean Society of Nursing Science
International Nuclear Information System (INIS)
Jackson, M.A.
1982-01-01
The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, this model is elaborated to produce the required program outputs; third, the resulting program is transformed to run efficiently in the execution environment. The first two stages deal in network structures of sequential processes; only the third is concerned with procedure hierarchies. (orig.)
Gleason, Brenda L; Gaebelein, Claude J; Grice, Gloria R; Crannage, Andrew J; Weck, Margaret A; Hurd, Peter; Walter, Brenda; Duncan, Wendy
2013-10-14
To determine the feasibility of using a validated set of assessment rubrics to assess students' critical-thinking and problem-solving abilities across a doctor of pharmacy (PharmD) curriculum. Trained faculty assessors used validated rubrics to assess student work samples for critical-thinking and problem-solving abilities. Assessment scores were collected and analyzed to determine student achievement of these 2 ability outcomes across the curriculum. Feasibility of the process was evaluated in terms of time and resources used. One hundred sixty-one samples were assessed for critical thinking, and 159 samples were assessed for problem-solving. Rubric scoring allowed assessors to evaluate four 5- to 7-page work samples per hour. The analysis indicated that overall critical-thinking scores improved over the curriculum. Although low yield for problem-solving samples precluded meaningful data analysis, it was informative for identifying potentially needed curricular improvements. Use of assessment rubrics for program ability outcomes was deemed authentic and feasible. Problem-solving was identified as a curricular area that may need improving. This assessment method has great potential to inform continuous quality improvement of a PharmD program.
Are Elementary Teacher Education Programs the Real Problem of Unqualified Teachers?
Weitman, Catheryn J.; Colbert, Ronald P.
This paper describes 10 factors that impact misguided perceptions of teacher preparation and teacher quality, especially elementary teachers prepared in highly-structured, university-based teacher preparation programs: (1) the offshoot of P-12 preparation, prior to attending postsecondary programs; (2) alignment of certification tests to state…
Family Support in Prevention Programs for Children at Risk for Emotional/Behavioral Problems
Cavaleri, Mary A.; Olin, S. Serene; Kim, Annie; Hoagwood, Kimberly E.; Burns, Barbara J.
2011-01-01
We conducted a review of empirically based prevention programs to identify prevalence and types of family support services within these programs. A total of 238 articles published between 1990 and 2011 that included a family support component were identified; 37 met criteria for inclusion. Following the Institute of Medicine's typology, prevention…
PROGRAMMED LEARNING--THEORY AND RESEARCH, AN ENDURING PROBLEM IN PSYCHOLOGY. SELECTED READINGS.
MOORE, J. WILLIAM, ED.; SMITH, WENDELL I., ED.
THIS IS A COMPILATION OF ARTICLES DEALING WITH PROGRAMED INSTRUCTION AND AUTO-INSTRUCTIONAL DEVICES (TEACHING-MACHINES). THE LITERATURE IS REVIEWED AND AN OVERVIEW OF THE FIELD IS PRESENTED. THE APPLICATION OF INSTRUCTIONAL TECHNOLOGY AND LEARNING THEORY TO TEACHING MACHINES IS DISCUSSED, AND THE PROCEDURE AND RULES OF PROGRAMING METHOD. SAMPLES…
Han, Ah-Reum; Park, Sin-Ae; Ahn, Byung-Eun
2018-06-01
This study aimed to determine the effects of a plant cultivation-based horticultural therapy program for elderly people with mental health problems. Pre- and post-test design with experimental and control groups. Twenty-eight elderly Korean people with mental health problems participated from April to June 2017 at a farm located in Suwon, South Korea. The participants were randomly assigned to either the control (n = 14) or horticultural therapy group (n = 14); the latter participated in once-weekly sessions of a previously designed 10-session horticultural therapy program. The pre-test occurred 1 week before starting the horticultural therapy program. The post-test was completed within 1 week after finishing the final program session. Cortisol levels were measured in saliva samples collected from both groups. The Senior Fitness Test was used to assess physical functional ability in both groups. In the horticultural therapy group, the cortisol levels decreased significantly from before to after the horticultural therapy program, and the post-test scores for six subtests of the Senior Fitness Test improved significantly. No significant improvements were seen in either measure in the control group. This study demonstrates the potential ability of horticultural therapy to improve the stress levels and physical functional abilities of elderly people with mental health problems. In future studies, it would be interesting to verify the long-term effects of this horticultural therapy program and to compare its effects with regard to sex, age, and various mental symptoms. Copyright © 2018 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Taufik Nur Hidayat
2017-10-01
Full Text Available The study is to classify the problem triggers in consecutive interpreting especially in listening. The objectives of the research are to find out the relationship between listening skills and sound problem by comparing the test results of English student and non-English student and prove that students’ problem triggers are closely related to the writing and reading performances which are caused by listening skill problems such as domain in comprehension, similar word, etc. The method used in the research is descriptive qualitative. The participants are English Department and non English student. Technique of collecting data in the research uses questionnaire, test, and interview. The biggest problem faced by non-English student group is numbering and proper names. It is 34 % which occupy in first rank. Whereas the percentage of English student in comprehension is 27%, then the numbering and proper names, the last is similar word which has 20%. Meanwhile, the test result of English group is 84.5 and non-English group is 60. It represent the background knowledge factors are also play an important role in doing the test. In conclusion, there is relationship between students’ problem triggers, writing and reading performances, especially homophone errors. So, the hypothesis is accepted and it strengthens a currently underdeveloped theory that sounds problem play an important role in listening.
Energy Technology Data Exchange (ETDEWEB)
1980-07-01
Program summaries, issue developments, governmental processes, and impacts are discussed for 10 case studies dealing with lifeline electric rates and alternative approaches to the problems of low-income ratepayers, namely; the Boston Edison rate freeze; the California lifeline; Florida Power and Light conservation rate; the Iowa-Illinois Gas and Electric small-use rate; the Maine demonstration lifeline program; the Massachusetts Electric Company A-65 rate; the Michigan optional senior citizen rate; the Narragansett Electric Company A-65 SSI rate; the Northern States Power Company conservation rate break; and the Potomac Electric Power Company rate freeze. (MCW)
Directory of Open Access Journals (Sweden)
Zhimiao Tao
2013-01-01
Full Text Available An equilibrium chance-constrained multiobjective programming model with birandom parameters is proposed. A type of linear model is converted into its crisp equivalent model. Then a birandom simulation technique is developed to tackle the general birandom objective functions and birandom constraints. By embedding the birandom simulation technique, a modified genetic algorithm is designed to solve the equilibrium chance-constrained multiobjective programming model. We apply the proposed model and algorithm to a real-world inventory problem and show the effectiveness of the model and the solution method.
Lexicographic goal programming and assessment tools for a combinatorial production problem.
2008-01-01
NP-complete combinatorial problems often necessitate the use of near-optimal solution techniques including : heuristics and metaheuristics. The addition of multiple optimization criteria can further complicate : comparison of these solution technique...
Pérez Gladish, Blanca María; Arenas Parra, María del Mar; Bilbao Terol, Amelia María; Rodríguez Uria, María Victoria
2005-01-01
This study attempts to apply a management science technique to improve the efficiency of Hospital Administration. We aim to design the performance of the surgical services at a Public Hospital that allows the Decision-Maker to plan surgical scheduling over one year in order to reduce waiting lists. Real decision problems usually involve several objectives that have parameters which are often given by the decision maker in an imprecise way. It is possible to handle these kinds of problems ...
1989-08-01
1977. Pp. 1-229. 25. V. Lesser and R. Fennell. "Parallelism in Aritificial Intelligence Problem Solving: A Case Study of Hearsay II," IEEE Transactions...artificial intelligence architecture used to solve the radar tracking problem. The research described was performed at Purdue University during long...TION 1 COSA TI CODES 18 SUBJECT TERMS in ,,tnu; . ’ .’ , .., ,’ a-, ,’£ ,i-, ,4’o4,, nun br) ,LD I GROUP SUB.GROu P Artificial intelligence Object
Energy Technology Data Exchange (ETDEWEB)
Szilard, Ronaldo Henriques [Idaho National Lab. (INL), Idaho Falls, ID (United States); Coleman, Justin [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Prescott, Steven [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kammerer, Annie [Annie Kammerer Consulting, Rye, NH (United States); Youngblood, Robert [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pope, Chad [Idaho State Univ., Pocatello, ID (United States)
2015-07-01
Risk-Informed Margin Management Industry Application on External Events. More specifically, combined events, seismically induced external flooding analyses for a generic nuclear power plant with a generic site soil, and generic power plant system and structure. The focus of this report is to define the problem above, set up the analysis, describe the methods to be used, tools to be applied to each problem, and data analysis and validation associated with the above.
International Nuclear Information System (INIS)
Snider, D.M.
1981-02-01
INVERT 1.0 is a digital computer program written in FORTRAN IV which calculates the surface heat flux of a one-dimensional solid using an interior-measured temperature and a physical description of the solid. By using two interior-measured temperatures, INVERT 1.0 can provide a solution for the heat flux at two surfaces, the heat flux at a boundary and the time dependent power, or the heat flux at a boundary and the time varying thermal conductivity of a material composing the solid. The analytical solution to inversion problem is described for the one-dimensional cylinder, sphere, or rectangular slab. The program structure, input instructions, and sample problems demonstrating the accuracy of the solution technique are included
Directory of Open Access Journals (Sweden)
m. s. osman
2017-09-01
Full Text Available In this paper, we consider fuzzy goal programming (FGP approach for solving multi-level multi-objective quadratic fractional programming (ML-MOQFP problem with fuzzy parameters in the constraints. Firstly, the concept of the ?-cut approach is applied to transform the set of fuzzy constraints into a common deterministic one. Then, the quadratic fractional objective functions in each level are transformed into quadratic objective functions based on a proposed transformation. Secondly, the FGP approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach.
Directory of Open Access Journals (Sweden)
Wallace Agyei
2015-03-01
Full Text Available Abstract The problem of scheduling nurses at the Out-Patient Department OPD at Tafo Government Hospital Kumasi Ghana is presented. Currently the schedules are prepared by head nurse who performs this difficult and time consuming task by hand. Due to the existence of many constraints the resulting schedule usually does not guarantee the fairness of distribution of work. The problem was formulated as 0-1goal programming model with the of objective of evenly balancing the workload among nurses and satisfying their preferences as much as possible while complying with the legal and working regulations.. The developed model was then solved using LINGO14.0 software. The resulting schedules based on 0-1goal programming model balanced the workload in terms of the distribution of shift duties fairness in terms of the number of consecutive night duties and satisfied the preferences of the nurses. This is an improvement over the schedules done manually.
International Nuclear Information System (INIS)
Fernandes, L.; Friedlander, A.; Guedes, M.; Judice, J.
2001-01-01
This paper addresses a General Linear Complementarity Problem (GLCP) that has found applications in global optimization. It is shown that a solution of the GLCP can be computed by finding a stationary point of a differentiable function over a set defined by simple bounds on the variables. The application of this result to the solution of bilinear programs and LCPs is discussed. Some computational evidence of its usefulness is included in the last part of the paper
HOUSTON, we’ve got a problem : Introduction program case Houston Galveston Bay Region, Texas (USA)
Brand, A.D.; Kothuis, B.L.M.; Kothuis, Baukje; Kok, Matthijs
2017-01-01
Various interesting tools were used and/or developed to stimulate knowledge integration in the Multifunctional Flood Defenses program. This chapter will present a diverse collection of these tools, hopefully stimulating others to consider using some of them in future.
Shadymov, A B; Fominykh, S A; Dik, V P
This article reports the results of the analysis of the new tendencies and normatives of the working legislation in the field of additional professional education in the speciality of «forensic medical expertise» and the application of the competency-based approach to the training of specialists in the framework of professional requalification and advanced training programs. Special attention is given to the problems of organization of the educational process and the elaboration of additional training programs based on the competency approach to the training of specialists at the Department of Forensic Medicine and Law with the professor V.N. Kryukov Course of Advanced Professional Training and Professional Requalification of Specialists at the state budgetary educational Institution of higher professional education «Altai State Medical University», Russian Ministry of Health. The study revealed the problems pertaining to the development of professional competencies in the framework of educational programs for the professional requalification and advanced training in the speciality «forensic medical expertise». The authors propose the legally substantiated approaches to the solution of these problems.
Directory of Open Access Journals (Sweden)
H Kazemipoor
2012-04-01
Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.
Programming and Tuning a Quantum Annealing Device to Solve Real World Problems
Perdomo-Ortiz, Alejandro; O'Gorman, Bryan; Fluegemann, Joseph; Smelyanskiy, Vadim
2015-03-01
Solving real-world applications with quantum algorithms requires overcoming several challenges, ranging from translating the computational problem at hand to the quantum-machine language to tuning parameters of the quantum algorithm that have a significant impact on the performance of the device. In this talk, we discuss these challenges, strategies developed to enhance performance, and also a more efficient implementation of several applications. Although we will focus on applications of interest to NASA's Quantum Artificial Intelligence Laboratory, the methods and concepts presented here apply to a broader family of hard discrete optimization problems, including those that occur in many machine-learning algorithms.
A Review On Linear Programming Analysis Of The Outsourcing Problem Using MATLAB
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FLt Lt Dinesh Kumar Gupta Retd.
2015-08-01
Full Text Available Abstract This study examines the case where market demand exceeds the companys capacity to manufacture. Manufacturing companies often function in situations where internal production resources constrain their throughput. Such situations are characterized as the problem of finite capacity scheduling. Management policy is to meet all demand in order to prevent competitor from entering the field. Now if management needs to decide what quantities of each product to manufacture and what quantities to buy from external contractors. In this study we have described two methodologies based on LP analysis to solve production outsourcing problem using latest version of MATLAB. We choose the best methodology which gives us maximum profits.
The US radon problem, policy, program and industry: achievements, challenges and strategies
International Nuclear Information System (INIS)
Angell, W. J.
2008-01-01
US radon research, policy and programs have stalled since their start in the late 1980's and early 1990's. In 2005, more homes had radon above the US Environmental Protection Agency (EPA) Reference Level than anytime in history since more homes were added to the housing stock that had indoor radon concentrations exceeding 150 Bq m -3 than had been mitigated. Funding for the US radon program has declined two-thirds from 1997 to 2007. Despite impressive goals for radon reduction, EPA lacks sound progress indicators especially in new construction radon control systems. School radon reduction has been at a standstill since the early 1990's. There has been no significant radon risk reduction in low-income sectors of the population. There is need for effective partnerships between the public and private sectors of the US radon professional communities as well as with the international programs and professionals. (authors)
Use of Software Programs as Zero Fill Help in Overcoming the Problem Around Hard Drive
Eko Prasetyo Nugroho; Fivtatianti Fivtatianti, Skom, MM
2003-01-01
Zero Fill, is a software tool programs that are designed for hard disk drive specially branded Quantum. This software is a tool programs that function to format the hard drive. Where is the type of format here is the first format or in other words the software to format the hard drive is working under conditions of low- level or commonly referred to as a low- level format. The advantages of this software is able to fix and remove all existing data within the disk, such as files...
Constraint Programming based Local Search for the Vehicle Routing Problem with Time Windows
Sala Reixach, Joan
2012-01-01
El projecte es centra en el "Vehicle Routing Problem with Time Windows". Explora i testeja un mètode basat en una formulació del problema en termes de programació de restriccions. Implementa un mètode de cerca local amb la capacitat de fer grans moviments anomenat "Large Neighbourhood Search".
Çakiroglu, Ünal; Öztürk, Mücahit
2017-01-01
This study intended to explore the development of self-regulation in a flipped classroom setting. Problem based learning activities were carried out in flipped classrooms to promote self-regulation. A total of 30 undergraduate students from Mechatronic department participated in the study. Self-regulation skills were discussed through students'…
Integer Programming Formulation of the Problem of Generating Milton Babbitt's All-partition Arrays
DEFF Research Database (Denmark)
Tanaka, Tsubasa; Bemman, Brian; Meredith, David
2016-01-01
Milton Babbitt (1916–2011) was a composer of twelve-tone serial music noted for creating the all-partition array. The problem of generating an all-partition array involves finding a rectangular array of pitch-class integers that can be partitioned into regions, each of which represents a distinct...
The Problems of Validation in a Competency-Based Preservice Reading Education Program.
Bergquist, Sidney R.
A problem of teacher education is to successfully integrate the knowledge students learn in the college classroom with the practical experiences of student teaching. A principal objective of an ideal teacher training situation would be to establish a vertical integration of the various types of exposure to reading both prior to and during contact…
Directory of Open Access Journals (Sweden)
Hossein Yousefi
2017-06-01
Full Text Available A vehicle routing problem with time windows (VRPTW is an important problem with many real applications in a transportation problem. The optimum set of routes with the minimum distance and vehicles used is determined to deliver goods from a central depot, using a vehicle with capacity constraint. In the real cases, there are other objective functions that should be considered. This paper considers not only the minimum distance and the number of vehicles used as the objective function, the customer’s satisfaction with the priority of customers is also considered. Additionally, it presents a new model for a bi-objective VRPTW solved by a revised multi-choice goal programming approach, in which the decision maker determines optimistic aspiration levels for each objective function. Two meta-heuristic methods, namely simulated annealing (SA and genetic algorithm (GA, are proposed to solve large-sized problems. Moreover, the experimental design is used to tune the parameters of the proposed algorithms. The presented model is verified by a real-world case study and a number of test problems. The computational results verify the efficiency of the proposed SA and GA.
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Haruo Fujino
2017-09-01
Full Text Available Psychological and psychiatric dysfunction is a major problem in a substantial proportion of young adults with Down syndrome. Some patients develop psychiatric issues, such as depressive, obsessive-compulsive, or psychotic-like disorders, in their late adolescence or young adulthood. Furthermore, these individuals may experience moderate to severe emotional and psychological distress. Development of a psychosocial treatment to address these issues is needed in addition to psychotropic medication. The current study reports two cases of young adults with Down syndrome, who presented psychiatric symptoms and marked disruption in their daily lives. These individuals participated in a Dohsa-hou treatment program. Following treatment, adaptive levels, maladaptive behaviors, and internalizing problems were evaluated by the Vineland Adaptive Behavior Scales-II. Participants showed improvement in maladaptive behaviors and internalizing problems; however, improvement in these areas may be influenced by baseline severity of the problems. This case report suggests that Dohsa-hou could be an effective therapeutic approach for maladaptive and internalizing problems in adults with Down syndrome.
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Tatyana V. Matveeva
2015-01-01
Full Text Available Leading role in the process of development and improvement of modern Russian education plays an additional professional education, which, to the greatest extent, responds to the qualitative changes in the socio-economic relations in a rapidly changing world. The aim of this paper is to identify the organizational and legal problems of professional and public accreditation of additional professional education programs in Russia and the opportunities development of this institution in modern conditions. The scientific research problem was to justify the need for professional and public accreditation of additional professional education programs of modern universities on the basis of delegation of procedures for evaluating the quality of education by public authorities to the public expert organizations, which ensure the independence and objectivity of the decisions made by qualified experts using a standardized assessment tools and tech to meet the needs of all parties concerned for highly qualified professionals. Methods. Empirical and theoretical methods were applied in the process of solving the problems in the scientific work to achieve the objectives of the study and test the hypothesis of an integrated methodology. Theoretical research methods involve: analysis of different literary sources (including legislative and regulatory enactments of the Higher Authorities of the Russian Federation, regulatory enactments of the Ministry of General and Vocational Education of the Russian Federation, compilation, synthesis of empirical data, comparative analysis, and others. Empirical research methods include: observation, testing, interview, questionnaire, ranking, pedagogical experiment, analysis of the products of activity, method of expert evaluations, methods of mathematical statistics, and other. Results. The expediency of independent accreditation procedures is proved. The goals that need to be solved to enhance the competitiveness of
Prevention of language problems in children: the effectiveness of an intervention program
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José Luis GALLEGO ORTEGA
2011-09-01
Full Text Available Language is an essential tool for personal and social development of children and it is perceived as the most important learning that children undertake in the early years of their lives. It is generally accepted that from birth to the age of three-four years old, children achieve a basic repertory of skills in different linguistic dimensions which allow them to communicate effectively with their environment. However, research has shown that phonemic disorders, morphosyntactic dysfunctions and semantic poverty figure prominently in the overall oral language disorders in infancy. In this respect, the review of literature informs us of the abundance of work aimed at rehabiliting the conditions already set in childlike expression, but there are significant gaps in regard to systematic prevention programs to prevent such evolutionary disorders which can become operational because of an early intervention in the field of communication. According to the above, it was developed a research project designed to establish the differential impact of a program to develop language skills in preschoolers. We worked with a sample of 32 children (5 years old in a pretest-posttest design. The data analysis shows that the magnitude of change is significant when comparing the results obtained by the experimental and the control group before and after program implementation. The overall effect of the program allowed to determine its effectiveness to increase language skills in the morph syntactic level.
Responding to Problem Behavior in Schools: The Behavior Education Program. Second Edition
Crone, Deanne A.; Hawken, Leanne S.; Horner, Robert H.
2010-01-01
This bestselling book has been used in schools across the country to establish efficient and cost-effective systems of Tier II positive behavior support. The Behavior Education Program (BEP) was developed for the approximately 10-15% of students who fail to meet schoolwide disciplinary expectations but do not yet require intensive, individualized…
Model-based problem solving through symbolic regression via pareto genetic programming
Vladislavleva, E.
2008-01-01
Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust
Rotarius, T; Liberman, A; Liberman, J S
2000-09-01
Employee assistance programs (EAPs) are a by-product of community-based mental health services--making behavioral care available in an outpatient ambulatory setting. This manuscript outlines an application of EAPs to health care workers and the multiplicity of challenges they must confront and describes the importance of timely intervention and support.
Fluid history computation methods for reactor safeguards problems using MNODE computer program
International Nuclear Information System (INIS)
Huang, Y.S.; Savery, C.W.
1976-10-01
A method for predicting the pressure-temperature histories of air, water liquid, and vapor flowing in a zoned containment as a result of high energy pipe rupture is described. The computer code, MNODE, has been developed for 12 connected control volumes and 24 inertia flow paths. Predictions by the code are compared with the results of an analytical gas dynamic problem, semiscale blowdown experiments, full scale MARVIKEN test results, Battelle-Frankfurt model PWR containment test data. The MNODE solutions to NRC/AEC subcompartment benchmark problems are also compared with results predicted by other computer codes such as RELAP-3, FLASH-2, CONTEMPT-PS. The analytical consideration is consistent with Section 6.2.1.2 of the Standard Format (Rev. 2) issued by U.S. Nuclear Regulatory Commission in September 1975
Producing Television Agriculture Program: Issues and Problems among Malaysian Television Producers
Md. S. Hassan; Hayrol A.M. Shaffril; Bahaman A. Samah; Mohamad S.S. Ali; Nor S. Ramli
2010-01-01
Problem statement: One of the developing sectors in Malaysia is agriculture. Agriculture doubtlessly has assisted this country in terms of enhancing the economic level, offering a huge number of employment opportunities and uplifting the socio-economy status of the community. To ensure the sustainability of this sector to the country, we must ensure that the valuable agriculture information is continuously provided to the public and the information must be disseminated through the most effect...
The Neighborhood Covering Heuristic (NCH) Approach for the General Mixed Integer Programming Problem
2004-02-02
5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Creative Action LLC 680 N. Portage Path Akron, OH 44303; The...University of Akron Department of Theoretical and Applied Mathematics Akron OH 44325-4002 8. PERFORMING ORGANIZATION REPORT NUMBER SF309 9...algorithm is naturally adaptable to a parallel architechture . In particular, under NCH, one could parcel out pieces of the problem to many processors
Parametric linear programming for a materials requirement planning problem solution with uncertainty
Martin Darío Arango Serna; Conrado Augusto Serna; Giovanni Pérez Ortega
2010-01-01
Using fuzzy set theory as a methodology for modelling and analysing decision systems is particularly interesting for researchers in industrial engineering because it allows qualitative and quantitative analysis of problems involving uncertainty and imprecision. Thus, in an effort to gain a better understanding of the use of fuzzy logic in industrial engineering, more specifically in the field of production planning, this article was aimed at providing a materials requirement planning (MRP) pr...
International Nuclear Information System (INIS)
Biffle, J.H.
1991-01-01
1 - Description of program or function: JAC is a two-dimensional finite element program for solving large deformation, temperature dependent, quasi-static mechanics problems with the nonlinear conjugate gradient (CG) technique. Either plane strain or axisymmetric geometry may be used with material descriptions which include temperature dependent elastic-plastic, temperature dependent secondary creep, and isothermal soil models. The nonlinear effects examined include material and geometric nonlinearities due to large rotations, large strains, and surface which slide relative to one another. JAC is vectorized to perform efficiently on the Cray1 computer. A restart capability is included. 2 - Method of solution: The nonlinear conjugate gradient method is employed in a two-dimensional plane strain or axisymmetric setting with various techniques for accelerating convergence. Sliding interface conditions are also implemented. A four-node Lagrangian uniform strain element is used with orthogonal hourglass viscosity to control the zero energy modes. Three sets of continuum equations are needed - kinematic statements, constitutive equations, and equations of equilibrium - to describe the deformed configuration of the body. 3 - Restrictions on the complexity of the problem - Maxima of: 10 load and solution control functions, 4 materials. The strain rate is assumed constant over a time interval. Current large rotation theory is applicable to a maximum shear strain of 1.0. JAC should be used with caution for large shear strains. Problem size is limited only by available memory
Morgan, Amy J; Rapee, Ronald M; Salim, Agus; Goharpey, Nahal; Tamir, Elli; McLellan, Lauren F; Bayer, Jordana K
2017-05-01
The Cool Little Kids parenting group program is an effective intervention for preventing anxiety disorders in young children who are at risk because of inhibited temperament. The program has six group sessions delivered by trained psychologists to parents of 3- to 6-year-old children. An online adaptation (Cool Little Kids Online) has been developed to overcome barriers to its wide dissemination in the community. This study tested the efficacy of Cool Little Kids Online in a randomized controlled trial. A total of 433 parents of a child aged 3 to 6 years with an inhibited temperament were randomized to the online parenting program or to a 24-week waitlist. The online program has 8 interactive modules providing strategies that parents can implement with their child to manage their child's avoidant coping, reduce parental overprotection, and encourage child independence. Parents were provided telephone consultation support with a psychologist when requested. Parents completed self-report questionnaires at baseline and at 12 and 24 weeks after baseline. The intervention group showed significantly greater improvement over time in child anxiety symptoms compared to the control group (d = 0.38). The intervention group also showed greater reductions in anxiety life interference (ds = 0.33-0.35) and lower rates of anxiety disorders than the control group (40% versus 54%), but there were minimal effects on broader internalizing symptoms or overprotective parenting. Results provide empirical support for the efficacy of online delivery of the Cool Little Kids program. Online dissemination may improve access to an evidence-based prevention program for child anxiety disorders. Clinical trial registration information-Randomised Controlled Trial of Cool Little Kids Online: A Parenting Program to Prevent Anxiety Problems in Young Children; http://www.anzctr.org.au/; 12615000217505. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc
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Daniel T.L. Shek
2006-01-01
Full Text Available This paper outlines the proposal for the development, implementation, and evaluation of a positive youth development program that attempts to promote the mental health of stressful Chinese adolescents using principles of Problem Solving Therapy (PST. There are two general aims of PST: to help clients identify life difficulties and resolve them, as well as to teach them skills on how to deal with future problems. The proposed project will utilize the principles of PST as the guiding framework to run two mental health promotion courses for adolescents who are experiencing disturbing stressful responses and students who want to improve their stress management style. Both objective and subjective outcome evaluation strategies will be carried out to assess the effectiveness of the intervention to promote the psychological well-being in adolescents who are experiencing stress. A related sample proposal is described that can give social workers some insight on how to prepare a proposal for developing the Tier 2 Program of the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programs.
A Unique Technique to get Kaprekar Iteration in Linear Programming Problem
Sumathi, P.; Preethy, V.
2018-04-01
This paper explores about a frivolous number popularly known as Kaprekar constant and Kaprekar numbers. A large number of courses and the different classroom capacities with difference in study periods make the assignment between classrooms and courses complicated. An approach of getting the minimum value of number of iterations to reach the Kaprekar constant for four digit numbers and maximum value is also obtained through linear programming techniques.
Energy Technology Data Exchange (ETDEWEB)
Shadid, J.N.; Moffat, H.K.; Hutchinson, S.A.; Hennigan, G.L.; Devine, K.D.; Salinger, A.G.
1996-05-01
The theoretical background for the finite element computer program, MPSalsa, is presented in detail. MPSalsa is designed to solve laminar, low Mach number, two- or three-dimensional incompressible and variable density reacting fluid flows on massively parallel computers, using a Petrov-Galerkin finite element formulation. The code has the capability to solve coupled fluid flow, heat transport, multicomponent species transport, and finite-rate chemical reactions, and to solver coupled multiple Poisson or advection-diffusion- reaction equations. The program employs the CHEMKIN library to provide a rigorous treatment of multicomponent ideal gas kinetics and transport. Chemical reactions occurring in the gas phase and on surfaces are treated by calls to CHEMKIN and SURFACE CHEMKIN, respectively. The code employs unstructured meshes, using the EXODUS II finite element data base suite of programs for its input and output files. MPSalsa solves both transient and steady flows by using fully implicit time integration, an inexact Newton method and iterative solvers based on preconditioned Krylov methods as implemented in the Aztec solver library.
An Improved Method for Solving Multiobjective Integer Linear Fractional Programming Problem
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Meriem Ait Mehdi
2014-01-01
Full Text Available We describe an improvement of Chergui and Moulaï’s method (2008 that generates the whole efficient set of a multiobjective integer linear fractional program based on the branch and cut concept. The general step of this method consists in optimizing (maximizing without loss of generality one of the fractional objective functions over a subset of the original continuous feasible set; then if necessary, a branching process is carried out until obtaining an integer feasible solution. At this stage, an efficient cut is built from the criteria’s growth directions in order to discard a part of the feasible domain containing only nonefficient solutions. Our contribution concerns firstly the optimization process where a linear program that we define later will be solved at each step rather than a fractional linear program. Secondly, local ideal and nadir points will be used as bounds to prune some branches leading to nonefficient solutions. The computational experiments show that the new method outperforms the old one in all the treated instances.
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Narong Wichapa
2018-01-01
Full Text Available Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any stand-alone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in Upper-Northeastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP. After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP, namely the HGP model, was tested. Finally, the vehicle routing problem (VRP for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA which hybridizes the push forward insertion heuristic (PFIH, genetic algorithm (GA and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles
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Salah Eldin Kassab
2017-06-01
Discussion: Analyzing the tutors’ scores of their motivation for PBL tutoring yielded three significantly correlated constructs representing tutoring self-efficacy, tutoring interest and tutoring value. The findings demonstrated high internal consistency reliability of the questionnaire, strong correlation between the three constructs as well as correlations between the constructs and the self-rated tutoring skills scores. Taken together, the current study demonstrates that the newly developed instrument measuring motivation for PBL tutoring exhibits good psychometric properties. The findings in this paper pave the way for further studies for refining the measurement of this construct in different problem-based contexts.
A Mixed-Integer Linear Programming Problem which is Efficiently Solvable.
1987-10-01
ger prongramn rg versions or the problem is not ac’hievable in genieral for sparse inistancves of’ P rolem(r Mi. Th le remrai nder or thris paper is...rClazes c:oIh edge (i,I*) by comlpli urg +- rnirr(z 3, ,x + a,j). A sirnI) le analysis (11 vto Nei [131 indicates why whe Iellinan-Ford algorithm works...ari cl(cck to iceat reguilar rnct’vtuls. For c’xamiic, oi1cc Wwitiil pcroccc’ssicg svlstcici1 rccjcilrcc thicit I iisc wires ice repeated verr 200W
An Optimization Approach for Hazardous Waste Management Problem under Stochastic Programming
International Nuclear Information System (INIS)
Abass, S.A.; Abdallah, A.S.; Gomaa, M.A.
2008-01-01
Hazardous waste is the waste which, due to their nature and quantity, is potentially hazardous to human health and/or the environment. This kind of waste requires special disposal techniques to eliminate or reduce thc hazardous. Hazardous waste management (HWM) problem is concerned in the basic with the disposal method. hi this paper we focus on incineration as an effective to dispose the waste. For this type of disposal, there arc air pollution standards imposed by the government. We will propose an optimization model satisfied the air pollution standards and based on the model of Emek and Kara with using random variable coefficients in the constraint
NAMMU: finite element program for coupled heat and groundwater flow problems
International Nuclear Information System (INIS)
Rae, J.; Robinson, P.C.
1979-11-01
NAMMU is a computer program which will calculate the evolution in time of coupled water and heat flow in a porous medium. It is intended to be used primarily for modelling studies of underground nuclear waste repositories. NAMMU is based on the Galerkin-Finite-element method and has self-adjusting time stepping. The present version is written for 2-dimensional cartesian or cylindrical coordinate systems. It has been checked against two calculations from the KBS study and an exact solution by Hodgkinson for a very idealised repository design. (author)
Duan, Qianqian; Yang, Genke; Xu, Guanglin; Pan, Changchun
2014-01-01
This paper is devoted to develop an approximation method for scheduling refinery crude oil operations by taking into consideration the demand uncertainty. In the stochastic model the demand uncertainty is modeled as random variables which follow a joint multivariate distribution with a specific correlation structure. Compared to deterministic models in existing works, the stochastic model can be more practical for optimizing crude oil operations. Using joint chance constraints, the demand uncertainty is treated by specifying proximity level on the satisfaction of product demands. However, the joint chance constraints usually hold strong nonlinearity and consequently, it is still hard to handle it directly. In this paper, an approximation method combines a relax-and-tight technique to approximately transform the joint chance constraints to a serial of parameterized linear constraints so that the complicated problem can be attacked iteratively. The basic idea behind this approach is to approximate, as much as possible, nonlinear constraints by a lot of easily handled linear constraints which will lead to a well balance between the problem complexity and tractability. Case studies are conducted to demonstrate the proposed methods. Results show that the operation cost can be reduced effectively compared with the case without considering the demand correlation.
Directory of Open Access Journals (Sweden)
Qianqian Duan
2014-01-01
Full Text Available This paper is devoted to develop an approximation method for scheduling refinery crude oil operations by taking into consideration the demand uncertainty. In the stochastic model the demand uncertainty is modeled as random variables which follow a joint multivariate distribution with a specific correlation structure. Compared to deterministic models in existing works, the stochastic model can be more practical for optimizing crude oil operations. Using joint chance constraints, the demand uncertainty is treated by specifying proximity level on the satisfaction of product demands. However, the joint chance constraints usually hold strong nonlinearity and consequently, it is still hard to handle it directly. In this paper, an approximation method combines a relax-and-tight technique to approximately transform the joint chance constraints to a serial of parameterized linear constraints so that the complicated problem can be attacked iteratively. The basic idea behind this approach is to approximate, as much as possible, nonlinear constraints by a lot of easily handled linear constraints which will lead to a well balance between the problem complexity and tractability. Case studies are conducted to demonstrate the proposed methods. Results show that the operation cost can be reduced effectively compared with the case without considering the demand correlation.
DEFF Research Database (Denmark)
Fattahi, Mohammad; Govindan, Kannan; Keyvanshokooh, Esmaeil
2018-01-01
In this paper, we address a multi-period supply chain network redesign problem in which customer zones have price-dependent stochastic demand for multiple products. A novel multi-stage stochastic program is proposed to simultaneously make tactical decisions including products' prices and strategic...... redesign decisions. Existing uncertainty in potential demands of customer zones is modeled through a finite set of scenarios, described in the form of a scenario tree. The scenarios are generated using a Latin Hypercube Sampling method and then a forward scenario construction technique is employed...
International Nuclear Information System (INIS)
Kim, Min Soo; Kim, Jae San
2009-01-01
From past to present, Iran have been focused by international society and still have continued their enrichment activity despite of many sanctions. It is barely easy to solve this situation and to negotiate between related countries. Because there are many factors to influence this. New president of U.S. Barack Obama could be a great deal of factor for solving Iran's nuclear issue as well. From this point of view, following Iran's unsolved problems of nuclear program could be helpful to understand the situation and what the key point to solve it, and forecast the future with surrounding political and regional factors
Young, Katherine C.; Sobieszczanski-Sobieski, Jaroslaw
1988-01-01
This project has two objectives. The first is to determine whether linear programming techniques can improve performance when handling design optimization problems with a large number of design variables and constraints relative to the feasible directions algorithm. The second purpose is to determine whether using the Kreisselmeier-Steinhauser (KS) function to replace the constraints with one constraint will reduce the cost of total optimization. Comparisons are made using solutions obtained with linear and non-linear methods. The results indicate that there is no cost saving using the linear method or in using the KS function to replace constraints.
Fathil Bakir Allami; Mohdsofian Omar-Fauzee; Ishak Sin
2016-01-01
The overweight problem in Iraq has been a great issue that needs to be solved by government to ensure a better well-being. The purpose of this paper is to explore the need of the modern technology in physical education in order to overcome the issues of overweight in Iraq. The methodology used in this paper is through library research which focuses on issues of overweight and modern technology application in physical education programs. It can be concluded that the use of modern technology in...
Directory of Open Access Journals (Sweden)
Hassan Barati
2011-10-01
Full Text Available In this paper a new bidding strategy become modeling to day-ahead markets. The proposed algorithm is related to the point of view of a generation company (Genco that its end is maximized its benefit as a participant in sale markets of active power and spinning reserve. In this method, hourly forecasted energy price (FEP and forecasted reserve price (FRP is used as a reference to model the possible and probable price strategies of Gencos. A bi-level optimization problem That first level, is used to maximize the individual Genco’s payoffs for obtaining the optimal offered quantity of Gencos. The second one, uses the results of the upper sub-problem and minimizes the consumer’s payment with regard to the technical and network constraints, which leads to the awarded generation of the Gencos. In this paper use of the game theory in exist optimization model. The paper proposes a linear programming approach. A six bus system is employed to illustrate the application of the proposed method and to show its high precision and capabilities.
Ginzburg, Samara B; Deutsch, Susan; Bellissimo, Jaclyn; Elkowitz, David E; Stern, Joel Nh; Lucito, Robert
2018-01-01
The evolution of health care systems in response to societal and financial pressures has changed care delivery models, which presents new challenges for physicians. Leadership training is increasingly being recognized as an essential component of medical education training to prepare physicians to meet these needs. Unfortunately, most medical schools do not include leadership training. It has been suggested that a longitudinal and integrated approach to leadership training should be sought. We hypothesized that integration of leadership training into our hybrid problem-based learning (PBL)/case-based learning (CBL) program, Patient-Centered Explorations in Active Reasoning, Learning and Synthesis (PEARLS), would be an effective way for medical students to develop leadership skills without the addition of curricular time. We designed a unique leadership program in PEARLS in which 98 medical students participated during each of their six courses throughout the first 2 years of school. A program director and trained faculty facilitators educated students and coached them on leadership development throughout this time. Students were assessed by their facilitator at the end of every course on development of leadership skills related to teamwork, meaningful self-assessment, process improvement, and thinking outside the box. Students consistently improved their performance from the first to the final course in all four leadership parameters evaluated. The skills that demonstrated the greatest change were those pertaining to thinking outside the box and process improvement. Incorporation of a longitudinal and integrated approach to leadership training into an existing PBL/CBL program is an effective way for medical students to improve their leadership skills without the addition of curricular time. These results offer a new, time-efficient option for leadership development in schools with existing PBL/CBL programs.
Behavior improvement: a two-track program for the correction of employee problems.
McConnell, C R
1993-03-01
In the best of all possible working worlds no one would ever have to be involuntarily terminated from employment. Whether a punitive discharge for a severe violation of a word rule, or a gentle dismissal for failure to meet job standards, termination is one of the most difficult tasks a supervisor ever has to perform. However, it is the effect on the employee that should dominate the supervisor's thoughts and actions, not the personal uneasiness with which the supervisor greets the task. It is because of the impact on the employee that the supervisor has a responsibility to do everything reasonably possible to ensure the employee's success before resorting to dismissal or discharge. Adopting this sort of caring attitude toward employees is not easy; most of our management role models of past years were raised on authoritarianism. As a result there is in many supervisors a tendency to simply weed out the troublesome employee and start again with someone new. However, any supervisor can fire, but it is the exceptional supervisor who can salvage an employee and turn a source of problems into an effective producer.
MPSalsa a finite element computer program for reacting flow problems. Part 2 - user`s guide
Energy Technology Data Exchange (ETDEWEB)
Salinger, A.; Devine, K.; Hennigan, G.; Moffat, H. [and others
1996-09-01
This manual describes the use of MPSalsa, an unstructured finite element (FE) code for solving chemically reacting flow problems on massively parallel computers. MPSalsa has been written to enable the rigorous modeling of the complex geometry and physics found in engineering systems that exhibit coupled fluid flow, heat transfer, mass transfer, and detailed reactions. In addition, considerable effort has been made to ensure that the code makes efficient use of the computational resources of massively parallel (MP), distributed memory architectures in a way that is nearly transparent to the user. The result is the ability to simultaneously model both three-dimensional geometries and flow as well as detailed reaction chemistry in a timely manner on MT computers, an ability we believe to be unique. MPSalsa has been designed to allow the experienced researcher considerable flexibility in modeling a system. Any combination of the momentum equations, energy balance, and an arbitrary number of species mass balances can be solved. The physical and transport properties can be specified as constants, as functions, or taken from the Chemkin library and associated database. Any of the standard set of boundary conditions and source terms can be adapted by writing user functions, for which templates and examples exist.
The nurse scheduling problem: a goal programming and nonlinear optimization approaches
Hakim, L.; Bakhtiar, T.; Jaharuddin
2017-01-01
Nurses scheduling is an activity of allocating nurses to conduct a set of tasks at certain room at a hospital or health centre within a certain period. One of obstacles in the nurse scheduling is the lack of resources in order to fulfil the needs of the hospital. Nurse scheduling which is undertaken manually will be at risk of not fulfilling some nursing rules set by the hospital. Therefore, this study aimed to perform scheduling models that satisfy all the specific rules set by the management of Bogor State Hospital. We have developed three models to overcome the scheduling needs. Model 1 is designed to schedule nurses who are solely assigned to a certain inpatient unit and Model 2 is constructed to manage nurses who are assigned to an inpatient room as well as at Polyclinic room as conjunct nurses. As the assignment of nurses on each shift is uneven, then we propose Model 3 to minimize the variance of the workload in order to achieve equitable assignment on every shift. The first two models are formulated in goal programming framework, while the last model is in nonlinear optimization form.
Schow, Trine; Harris, Paul; Teasdale, Thomas William; Rasmussen, Morten Arendt
2016-04-06
Balance problems and binocular visual dysfunction (BVD) are common problems after stroke, however evidence of an effective rehabilitation method are limited. To evaluate the effect of a four-month rehabilitation program for individuals with balance problems and BVD after a stroke. About 40 sessions of 1.5 hours duration over four months with visual therapy and balance rehabilitation, was provided to all 29 participants, aged 18-67 years, in groups of 7-8 individuals. Several measures for BVD, balance, gait, Health Related Quality Of Life (HRQoL) and functional recovery were used at baseline, at the end of training and at a six-month follow up (FU). We found significant improvements in stereopsis, vergence, saccadic movements, burden of binocular visual symptoms, balance and gait speed, fatigue, HRQoL and functional recovery. Moreover, 60% of the participants were in employment at the six-month FU, compared to only 23% before training. All improvements were sustained at the six-month FU. Although a control group is lacking, the evidence suggests that the positive improvement is a result of the combined visual and balance training. The combination of balance and visual training appears to facilitate changes at a multimodal level affecting several functions important in daily life.
Maddrey, Elizabeth
Research in academia and industry continues to identify a decline in enrollment in computer science. One major component of this decline in enrollment is a shortage of female students. The primary reasons for the gender gap presented in the research include lack of computer experience prior to their first year in college, misconceptions about the field, negative cultural stereotypes, lack of female mentors and role models, subtle discriminations in the classroom, and lack of self-confidence (Pollock, McCoy, Carberry, Hundigopal, & You, 2004). Male students are also leaving the field due to misconceptions about the field, negative cultural stereotypes, and a lack of self-confidence. Analysis of first year attrition revealed that one of the major challenges faced by students of both genders is a lack of problem-solving skills (Beaubouef, Lucas & Howatt, 2001; Olsen, 2005; Paxton & Mumey, 2001). The purpose of this study was to investigate whether specific, non-mathematical problem-solving instruction as part of introductory programming courses significantly increased computer programming self-efficacy and achievement of students. The results of this study showed that students in the experimental group had significantly higher achievement than students in the control group. While this shows statistical significance, due to the effect size and disordinal nature of the data between groups, care has to be taken in its interpretation. The study did not show significantly higher programming self-efficacy among the experimental students. There was not enough data collected to statistically analyze the effect of the treatment on self-efficacy and achievement by gender. However, differences in means were observed between the gender groups, with females in the experimental group demonstrating a higher than average degree of self-efficacy when compared with males in the experimental group and both genders in the control group. These results suggest that the treatment from this
International Nuclear Information System (INIS)
Ju, Liwei; Tan, Zhongfu; Yuan, Jinyun; Tan, Qingkun; Li, Huanhuan; Dong, Fugui
2016-01-01
Highlights: • Our research focuses on Virtual Power Plant (VPP). • Virtual Power Plant consists of WPP, PV, CGT, ESSs and DRPs. • Robust optimization theory is introduced to analyze uncertainties. • A bi-level stochastic scheduling optimization model is proposed for VPP. • Models are built to measure the impacts of ESSs and DERPs on VPP operation. - Abstract: To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could
Iwata, Kentaro; Doi, Asako
2017-11-10
The purpose of this study is to investigate the medical students'perceptions of the Hybrid Educational Activities between team based learning (TBL) and problem based learning (PBL) Program (HEATAPP), a novel educational program that combines characteristics of PBL and TBL. A five-day HEATAPP on infectious diseases was provided to 4th year medical students at Kobe University School of Medicine, Kobe, Japan. After the program, a focus group discussion was held among 6 medical students who participated in HEATAPP. We qualitatively analyzed the recorded data to delineate the effectiveness of, and the perceptions on, HEATAPP. Some students considered HEATAPP being effective as an active learning, and in developing questions. However, some students found active learning difficult to execute, since they were so familiar with passive learning such as lectures and examinations. They also found it difficult to identify important points by reading authentic textbooks on given issues, particularly English textbooks. Even though active learning and group discussion are underscored as important in medicine, some Japanese medical students may be reluctant to shift towards these since they are so used to passive learning since childhood. English language is another barrier to active learning. The introduction of active learning in the earlier stages of education might be an effective solution. Teachers at medical schools in Japan should be mindful of the students'potentially negative attitudes towards active learning, which is claimed to be successful in western countries.
Directory of Open Access Journals (Sweden)
Elena Faccio
2013-12-01
Full Text Available Nowadays, we find in the literature many researches and related theories about body diseases and eating disorders in adolescence. Basing on these theories, the health promotion interventions at school are inclined to give youth the outcomes of risk behavior analysis, in the development of eating disorders. Those interventions lack of consideration regarding what students already think about the origins of the diseases. In this work we seek for the spontaneous ideas about developing of eating disorders and theories about how these problems could be prevented at school. In order to do that, we constructed an ad hoc survey which have been validated. Using the factorial analysis, we recognized three factors that participants used to explain the disorder: Relationship with parents, self-harm and mental illness; Organic illness; and Social comparison and social acceptance. The analysis of the data suggest that, in the schools that did not have programs of health promotion on food and the body (70%, students are more vulnerable to eating disorder. Among the others, the factor considered the most important by the students of these school, was the social comparison and social acceptance. On the contrary, the students who participated to the health programs on this topic, were more likely to consider responsible the relationships with parents, mental illness and self-harm. Considering the outcomes, we could suggest to rethink the methods utilized to promote health programs for preventing eating disorders at school.
Hanisch, Charlotte; Hautmann, Christopher; Plück, Julia; Eichelberger, Ilka; Döpfner, Manfred
2014-01-01
Background: Our indicated Prevention program for preschool children with Externalizing Problem behavior (PEP) demonstrated improved parenting and child problem behavior in a randomized controlled efficacy trial and in a study with an effectiveness design. The aim of the present analysis of data from the randomized controlled trial was to identify…
Korkmaz, Özgen
2016-01-01
The aim of this study was to investigate the effect of the Scratch and Lego Mindstorms Ev3 programming activities on academic achievement with respect to computer programming, and on the problem-solving and logical-mathematical thinking skills of students. This study was a semi-experimental, pretest-posttest study with two experimental groups and…
Lesmana, E.; Chaerani, D.; Khansa, H. N.
2018-03-01
Energy-Saving Generation Dispatch (ESGD) is a scheme made by Chinese Government in attempt to minimize CO2 emission produced by power plant. This scheme is made related to global warming which is primarily caused by too much CO2 in earth’s atmosphere, and while the need of electricity is something absolute, the power plants producing it are mostly thermal-power plant which produced many CO2. Many approach to fulfill this scheme has been made, one of them came through Minimum Cost Flow in which resulted in a Quadratically Constrained Quadratic Programming (QCQP) form. In this paper, ESGD problem with Minimum Cost Flow in QCQP form will be solved using Lagrange’s Multiplier Method
Tian, Yanping; Li, Chengren; Wang, Jiali; Cai, Qiyan; Wang, Hanzhi; Chen, Xingshu; Liu, Yunlai; Mei, Feng; Xiao, Lan; Jian, Rui; Li, Hongli
2017-09-07
Despite great advances, China's postgraduate education faces many problems, for example traditional lecture-based learning (LBL) method provides fewer oppotunities to apply knowledge in a working situation. Task-based learning (TBL) is an efficient strategy for increasing the connections among skills, knowledge and competences. This study aimed to evaluate the effect of a modified TBL model on problem-solving abilities among postgraduate medical students in China. We allocated 228 first-year postgraduate students at Third Military Medical University into two groups: the TBL group and LBL group. The TBL group was taught using a TBL program for immunohistochemistry. The curriculum consisted of five phases: task design, self-learning, experimental operations, discussion and summary. The LBL group was taught using traditional LBL. After the course, learning performance was assessed using theoretical and practical tests. The students' preferences and satisfaction of TBL and LBL were also evaluated using questionnaires. There were notable differences in the mean score rates in the practical test (P 80) in the TBL group was higher than that in the LBL group. We observed no substantial differences in the theoretical test between the two groups (P > 0.05). The questionnaire results indicated that the TBL students were satisfied with teaching content, teaching methods and experiment content. The TBL program was also beneficial for the postgraduates in completing their research projects. Furthermore, the TBL students reported positive effects in terms of innovative thinking, collaboration, and communication. TBL is a powerful educational strategy for postgraduate education in China. Our modified TBL imparted basic knowledge to the students and also engaged them more effectively in applying knowledge to solve real-world issues. In conclusion, our TBL established a good foundation for the students' future in both medical research and clinical work.
Yu, Hao; Solvang, Wei Deng
2016-05-31
Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
Directory of Open Access Journals (Sweden)
Hao Yu
2016-05-01
Full Text Available Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
Vahdani, Behnam; Jolai, Fariborz; Tavakkoli-Moghaddam, Reza; Meysam Mousavi, S.
2012-07-01
Maintenance outsourcing can be regarded as a strategic weapon to increase productivity and customer satisfaction in many companies, and this critical activity can be performed in a more efficient and effective way. This article presents two novel fuzzy possibilistic bi-objective zero-one programming (FPBOZOP) models for outsourcing of the equipment maintenance. In these models, cost parameters, including outsourcing cost, risk cost, time operations for performing the equipment maintenance and reliability level, as well as other influential parameters are considered through the outsourcing process. Moreover, the presented models can measure the capability of the company in doing different activities, unlike previous studies, in order to see the possibility of maintenance in-house, and can lead to make a best decision on the basis of the models' results. Both models are developed under uncertainty, which bring top managers the possibility of assigning more than one equipment or project to the supplier so that the profit is maximized, and the cost is minimized by considering bi-objectives concurrently. Then, a new fuzzy mathematical programming based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed bi-objective zero-one programming (BOZOP) models and to reach a preferred compromise solution. Furthermore, a real-case study is utilized to demonstrate and to validate the effectiveness of the presented models. The computational results revealed that the models can be implemented in variety of problems in the domain of the equipment maintenance outsourcing and project outsourcing either from theory or application perspectives.
Directory of Open Access Journals (Sweden)
Ntina Kourmousi
2016-06-01
Full Text Available The Problem Solving Inventory (PSI is designed to measure adults’ perceptions of problem-solving ability. The presented study aimed to translate it and assess its reliability and validity in a nationwide sample of 3668 Greek educators. In order to evaluate internal consistency reliability, Cronbach’s alpha coefficient was used. The scale’s construct validity was examined by a confirmatory factor analysis (CFA and by investigating its correlation with the Internality, Powerful others and Chance Multidimensional Locus of Control Scale (IPC LOC Scale, the Rosenberg Self-Esteem Scale (RSES and demographic information. Internal consistency reliability was satisfactory with Cronbach’s alphas ranging from 0.79 to 0.91 for all PSI scales. CFA confirmed that the bi-level model fitted the data well. The root mean square error of approximation (RMSEA, the comparative fit index (CFI and the goodness of fit index (GFI values were 0.030, 0.97 and 0.96, respectively, further confirming the bi-level model and the three-factors construct of the PSI. Intercorrelations and correlation coefficients between the PSI, the IPC LOC Scale and the RSES were significant. Age, sex, and working experience differences were found. In conclusion, the Greek version of the PSI was found to have satisfactory psychometric properties and therefore, it can be used to evaluate Greek teachers’ perceptions of their problem-solving skills.
Wolchik, Sharlene A; Tein, Jenn-Yun; Sandler, Irwin N; Kim, Han-Joe
2016-08-01
A developmental cascade model from functioning in adolescence to emerging adulthood was tested using data from a 15-year longitudinal follow-up of 240 emerging adults whose families participated in a randomized, experimental trial of a preventive program for divorced families. Families participated in the program or literature control condition when the offspring were ages 9-12. Short-term follow-ups were conducted 3 months and 6 months following completion of the program when the offspring were in late childhood/early adolescence. Long-term follow-ups were conducted 6 years and 15 years after program completion when the offspring were in middle to late adolescence and emerging adulthood, respectively. It was hypothesized that the impact of the program on mental health and substance use outcomes in emerging adulthood would be explained by developmental cascade effects of program effects in adolescence. The results provided support for a cascade effects model. Specifically, academic competence in adolescence had cross-domain effects on internalizing problems and externalizing problems in emerging adulthood. In addition, adaptive coping in adolescence was significantly, negatively related to binge drinking. It was unexpected that internalizing symptoms in adolescence were significantly negatively related to marijuana use and alcohol use. Gender differences occurred in the links between mental health problems and substance use in adolescence and mental health problems and substance use in emerging adulthood.
Roberts, C T; Davis, P G; Owen, L S
2013-01-01
Nasal continuous positive airway pressure (NCPAP) has proven to be an effective mode of non-invasive respiratory support in preterm infants; however, many infants still require endotracheal ventilation, placing them at an increased risk of morbidities such as bronchopulmonary dysplasia. Several other modes of non-invasive respiratory support beyond NCPAP, including synchronised and non-synchronised nasal intermittent positive pressure ventilation (SNIPPV and nsNIPPV) and bi-level positive airway pressure (BiPAP) are now also available. These techniques require different approaches, and the exact mechanisms by which they act remain unclear. SNIPPV has been shown to reduce the rate of reintubation in comparison to NCPAP when used as post-extubation support, but the evidence for nsNIPPV and BiPAP in this context is less convincing. There is some evidence that NIPPV (whether synchronised or non-synchronised) used as primary respiratory support is beneficial, but the variation in study methodology makes this hard to translate confidently into clinical practice. There is currently no evidence to suggest a reduction in mortality or important morbidities such as bronchopulmonary dysplasia, with NIPPV or BiPAP in comparison to NCPAP, and there is a lack of appropriately designed studies in this area. This review discusses the different approaches and proposed mechanisms of action of SNIPPV, nsNIPPV and BiPAP, the challenges of applying the available evidence for these distinct modalities of non-invasive respiratory support to clinical practice, and possible areas of future research. © 2013 S. Karger AG, Basel.
Directory of Open Access Journals (Sweden)
Carolyn Webster-Stratton
2012-07-01
Full Text Available Disruptive behavior disorders in children are on the increase. However, there is evidence that the younger a child is at the time of intervention, the more positive the behavioral effects on his/her adjustment at home and at school. Parental education might be an effective way of addressing early problems. The Incredible Years (IY programs were designed to prevent and treat behavior problems when they first appear (in infancy-toddlerhood through middle childhood and to intervene in multiple areas through parent, teacher, and child training. This paper summarizes the literature demonstrating the impact of the IY parent, teacher and child intervention programs, and describes in more detail the work done in Portugal so far to disseminate IY programs with fidelity, with particular emphasis on the IY Basic Preschool Parenting and Teacher Classroom Management programs.
Energy Technology Data Exchange (ETDEWEB)
Wichapa, Narong; Khokhajaikiat, Porntep
2017-07-01
Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.
International Nuclear Information System (INIS)
Wichapa, Narong; Khokhajaikiat, Porntep
2017-01-01
Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.