A Selfish Constraint Satisfaction Genetic Algorithms for Planning a Long-Distance Transportation Network

Science.gov (United States)

Onoyama, Takashi; Maekawa, Takuya; Kubota, Sen; Tsuruta, Setuso; Komoda, Norihisa

To build a cooperative logistics network covering multiple enterprises, a planning method that can build a long-distance transportation network is required. Many strict constraints are imposed on this type of problem. To solve these strict-constraint problems, a selfish constraint satisfaction genetic algorithm (GA) is proposed. In this GA, each gene of an individual satisfies only its constraint selfishly, disregarding the constraints of other genes in the same individuals. Moreover, a constraint pre-checking method is also applied to improve the GA convergence speed. The experimental result shows the proposed method can obtain an accurate solution in a practical response time.

[Problem-solving strategies and marital satisfaction].

Science.gov (United States)

Kriegelewicz, Olga

2006-01-01

This study investigated the relation between problem-solving strategies in the marital conflict and marital satisfaction. Four problem-solving strategies (Dialogue, Loyalty, Escalation of conflict and Withdrawal) were measured by the Problem-Solving Strategies Inventory, in two versions: self-report and report of partners' perceived behaviour. This measure refers to the concept of Rusbult, Johnson and Morrow, and meets high standards of reliability (alpha Cronbach from alpha = 0.78 to alpha = 0.94) and validity. Marital satisfaction was measured by Marriage Success Scale. The sample was composed of 147 marital couples. The study revealed that satisfied couples, in comparison with non-satisfied couples, tend to use constructive problem-solving strategies (Dialogue and Loyalty). They rarely use destructive strategies like Escalation of conflict or Withdrawal. Dialogue is the strategy connected with satisfaction in a most positive manner. These might be very important guidelines to couples' psychotherapy. Loyalty to oneself is a significant positive predictor of male satisfaction is also own Loyalty. The study shows that constructive attitudes are the most significant predictors of marriage satisfaction. It is therefore worth concentrating mostly on them in the psychotherapeutic process instead of eliminating destructive attitudes.

Distributed constraint satisfaction for coordinating and integrating a large-scale, heterogenous enterprise

CERN Document Server

Eisenberg, C

2003-01-01

Market forces are continuously driving public and private organisations towards higher productivity, shorter process and production times, and fewer labour hours. To cope with these changes, organisations are adopting new organisational models of coordination and cooperation that increase their flexibility, consistency, efficiency, productivity and profit margins. In this thesis an organisational model of coordination and cooperation is examined using a real life example; the technical integration of a distributed large-scale project of an international physics collaboration. The distributed resource constraint project scheduling problem is modelled and solved with the methods of distributed constraint satisfaction. A distributed local search method, the distributed breakout algorithm (DisBO), is used as the basis for the coordination scheme. The efficiency of the local search method is improved by extending it with an incremental problem solving scheme with variable ordering. The scheme is implemented as cen...

Nonlinear Model Predictive Control with Constraint Satisfactions for a Quadcopter

Science.gov (United States)

Wang, Ye; Ramirez-Jaime, Andres; Xu, Feng; Puig, Vicenç

2017-01-01

This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the effectiveness of the proposed strategy.

Logic-based methods for optimization combining optimization and constraint satisfaction

CERN Document Server

Hooker, John

2011-01-01

A pioneering look at the fundamental role of logic in optimization and constraint satisfaction While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible

Correlation-based decimation in constraint satisfaction problems

International Nuclear Information System (INIS)

Higuchi, Saburo; Mezard, Marc

2010-01-01

We study hard constraint satisfaction problems using some decimation algorithms based on mean-field approximations. The message-passing approach is used to estimate, beside the usual one-variable marginals, the pair correlation functions. The identification of strongly correlated pairs allows to use a new decimation procedure, where the relative orientation of a pair of variables is fixed. We apply this novel decimation to locked occupation problems, a class of hard constraint satisfaction problems where the usual belief-propagation guided decimation performs poorly. The pair-decimation approach provides a significant improvement.

Medical image segmentation by means of constraint satisfaction neural network

International Nuclear Information System (INIS)

Chen, C.T.; Tsao, C.K.; Lin, W.C.

1990-01-01

This paper applies the concept of constraint satisfaction neural network (CSNN) to the problem of medical image segmentation. Constraint satisfaction (or constraint propagation), the procedure to achieve global consistency through local computation, is an important paradigm in artificial intelligence. CSNN can be viewed as a three-dimensional neural network, with the two-dimensional image matrix as its base, augmented by various constraint labels for each pixel. These constraint labels can be interpreted as the connections and the topology of the neural network. Through parallel and iterative processes, the CSNN will approach a solution that satisfies the given constraints thus providing segmented regions with global consistency

A neural network approach to breast cancer diagnosis as a constraint satisfaction problem

International Nuclear Information System (INIS)

Tourassi, Georgia D.; Markey, Mia K.; Lo, Joseph Y.; Floyd, Carey E. Jr.

2001-01-01

A constraint satisfaction neural network (CSNN) approach is proposed for breast cancer diagnosis using mammographic and patient history findings. Initially, the diagnostic decision to biopsy was formulated as a constraint satisfaction problem. Then, an associative memory type neural network was applied to solve the problem. The proposed network has a flexible, nonhierarchical architecture that allows it to operate not only as a predictive tool but also as an analysis tool for knowledge discovery of association rules. The CSNN was developed and evaluated using a database of 500 nonpalpable breast lesions with definitive histopathological diagnosis. The CSNN diagnostic performance was evaluated using receiver operating characteristic analysis (ROC). The results of the study showed that the CSNN ROC area index was 0.84±0.02. The CSNN predictive performance is competitive with that achieved by experienced radiologists and backpropagation artificial neural networks (BP-ANNs) presented before. Furthermore, the study illustrates how CSNN can be used as a knowledge discovery tool overcoming some of the well-known limitations of BP-ANNs

Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems

Directory of Open Access Journals (Sweden)

José Carlos Ortiz-Bayliss

2018-01-01

Full Text Available When solving constraint satisfaction problems (CSPs, it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best of our knowledge, no earlier work has dealt with how first variable orderings affect the overall cost. In this paper, we explore the cost of finding high-quality orderings of variables within constraint satisfaction problems. We also study differences among the orderings produced by some commonly used heuristics and the way bad first decisions affect the search cost. One of the most important findings of this work confirms the paramount importance of first decisions. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. We propose a simple method to improve early decisions of heuristics. By using it, performance of heuristics increases.

Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems.

Science.gov (United States)

Ortiz-Bayliss, José Carlos; Amaya, Ivan; Conant-Pablos, Santiago Enrique; Terashima-Marín, Hugo

2018-01-01

When solving constraint satisfaction problems (CSPs), it is a common practice to rely on heuristics to decide which variable should be instantiated at each stage of the search. But, this ordering influences the search cost. Even so, and to the best of our knowledge, no earlier work has dealt with how first variable orderings affect the overall cost. In this paper, we explore the cost of finding high-quality orderings of variables within constraint satisfaction problems. We also study differences among the orderings produced by some commonly used heuristics and the way bad first decisions affect the search cost. One of the most important findings of this work confirms the paramount importance of first decisions. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. Another one is the evidence that many of the existing variable ordering heuristics fail to appropriately select the first variable to instantiate. We propose a simple method to improve early decisions of heuristics. By using it, performance of heuristics increases.

Fuzzy Constraint-Based Agent Negotiation

Institute of Scientific and Technical Information of China (English)

Menq-Wen Lin; K. Robert Lai; Ting-Jung Yu

2005-01-01

Conflicts between two or more parties arise for various reasons and perspectives. Thus, resolution of conflicts frequently relies on some form of negotiation. This paper presents a general problem-solving framework for modeling multi-issue multilateral negotiation using fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraint satisfaction problem (DFCSP). Fuzzy constrains are thus used to naturally represent each agent's desires involving imprecision and human conceptualization, particularly when lexical imprecision and subjective matters are concerned. On the other hand, based on fuzzy constraint-based problem-solving, our approach enables an agent not only to systematically relax fuzzy constraints to generate a proposal, but also to employ fuzzy similarity to select the alternative that is subject to its acceptability by the opponents. This task of problem-solving is to reach an agreement that benefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the deal more quickly since their search focuses only on the feasible solution space. An application to multilateral negotiation of a travel planning is provided to demonstrate the usefulness and effectiveness of our framework.

Constraint satisfaction problems CSP formalisms and techniques

CERN Document Server

Ghedira, Khaled

2013-01-01

A Constraint Satisfaction Problem (CSP) consists of a set of variables, a domain of values for each variable and a set of constraints. The objective is to assign a value for each variable such that all constraints are satisfied. CSPs continue to receive increased attention because of both their high complexity and their omnipresence in academic, industrial and even real-life problems. This is why they are the subject of intense research in both artificial intelligence and operations research. This book introduces the classic CSP and details several extensions/improvements of both formalisms a

Cognitive Dissonance Reduction as Constraint Satisfaction.

Science.gov (United States)

Shultz, Thomas R.; Lepper, Mark R.

1996-01-01

It is argued that the reduction of cognitive dissonance can be viewed as a constraint satisfaction problem, and a computational model of the process of consonance seeking is proposed. Simulations from this model matched psychological findings from the insufficient justification and free-choice paradigms of cognitive dissonance theory. (SLD)

Ant colony optimization and constraint programming

CERN Document Server

Solnon, Christine

2013-01-01

Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search

Connectionism, parallel constraint satisfaction processes, and gestalt principles: (re) introducing cognitive dynamics to social psychology.

Science.gov (United States)

Read, S J; Vanman, E J; Miller, L C

1997-01-01

We argue that recent work in connectionist modeling, in particular the parallel constraint satisfaction processes that are central to many of these models, has great importance for understanding issues of both historical and current concern for social psychologists. We first provide a brief description of connectionist modeling, with particular emphasis on parallel constraint satisfaction processes. Second, we examine the tremendous similarities between parallel constraint satisfaction processes and the Gestalt principles that were the foundation for much of modem social psychology. We propose that parallel constraint satisfaction processes provide a computational implementation of the principles of Gestalt psychology that were central to the work of such seminal social psychologists as Asch, Festinger, Heider, and Lewin. Third, we then describe how parallel constraint satisfaction processes have been applied to three areas that were key to the beginnings of modern social psychology and remain central today: impression formation and causal reasoning, cognitive consistency (balance and cognitive dissonance), and goal-directed behavior. We conclude by discussing implications of parallel constraint satisfaction principles for a number of broader issues in social psychology, such as the dynamics of social thought and the integration of social information within the narrow time frame of social interaction.

Constraint satisfaction problems with isolated solutions are hard

International Nuclear Information System (INIS)

Zdeborová, Lenka; Mézard, Marc

2008-01-01

We study the phase diagram and the algorithmic hardness of the random 'locked' constraint satisfaction problems, and compare them to the commonly studied 'non-locked' problems like satisfiability of Boolean formulae or graph coloring. The special property of the locked problems is that clusters of solutions are isolated points. This simplifies significantly the determination of the phase diagram, which makes the locked problems particularly appealing from the mathematical point of view. On the other hand, we show empirically that the clustered phase of these problems is extremely hard from the algorithmic point of view: the best known algorithms all fail to find solutions. Our results suggest that the easy/hard transition (for currently known algorithms) in the locked problems coincides with the clustering transition. These should thus be regarded as new benchmarks of really hard constraint satisfaction problems

Solving Large-Scale Computational Problems Using Insights from Statistical Physics

Energy Technology Data Exchange (ETDEWEB)

Selman, Bart [Cornell University

2012-02-29

Many challenging problems in computer science and related fields can be formulated as constraint satisfaction problems. Such problems consist of a set of discrete variables and a set of constraints between those variables, and represent a general class of so-called NP-complete problems. The goal is to find a value assignment to the variables that satisfies all constraints, generally requiring a search through and exponentially large space of variable-value assignments. Models for disordered systems, as studied in statistical physics, can provide important new insights into the nature of constraint satisfaction problems. Recently, work in this area has resulted in the discovery of a new method for solving such problems, called the survey propagation (SP) method. With SP, we can solve problems with millions of variables and constraints, an improvement of two orders of magnitude over previous methods.

The dose-volume constraint satisfaction problem for inverse treatment planning with field segments

International Nuclear Information System (INIS)

Michalski, Darek; Xiao, Ying; Censor, Yair; Galvin, James M

2004-01-01

The prescribed goals of radiation treatment planning are often expressed in terms of dose-volume constraints. We present a novel formulation of a dose-volume constraint satisfaction search for the discretized radiation therapy model. This approach does not rely on any explicit cost function. Inverse treatment planning uses the aperture-based approach with predefined, according to geometric rules, segmental fields. The solver utilizes the simultaneous version of the cyclic subgradient projection algorithm. This is a deterministic iterative method designed for solving the convex feasibility problems. A prescription is expressed with the set of inequalities imposed on the dose at the voxel resolution. Additional constraint functions control the compliance with selected points of the expected cumulative dose-volume histograms. The performance of this method is tested on prostate and head-and-neck cases. The relationships with other models and algorithms of similar conceptual origin are discussed. The demonstrated advantages of the method are: the equivalence of the algorithmic and prescription parameters, the intuitive setup of free parameters, and the improved speed of the method as compared to similar iterative as well as other techniques. The technique reported here will deliver approximate solutions for inconsistent prescriptions

Principals' Self-Efficacy: Relations with Job Autonomy, Job Satisfaction, and Contextual Constraints

Science.gov (United States)

Federici, Roger A.

2013-01-01

The purpose of the present study was to explore relations between principals' self-efficacy, perceived job autonomy, job satisfaction, and perceived contextual constraints to autonomy. Principal self-efficacy was measured by a multidimensional scale called the Norwegian Principal Self-Efficacy Scale. Job autonomy, job satisfaction, and contextual…

Analog Approach to Constraint Satisfaction Enabled by Spin Orbit Torque Magnetic Tunnel Junctions.

Science.gov (United States)

Wijesinghe, Parami; Liyanagedera, Chamika; Roy, Kaushik

2018-05-02

Boolean satisfiability (k-SAT) is an NP-complete (k ≥ 3) problem that constitute one of the hardest classes of constraint satisfaction problems. In this work, we provide a proof of concept hardware based analog k-SAT solver, that is built using Magnetic Tunnel Junctions (MTJs). The inherent physics of MTJs, enhanced by device level modifications, is harnessed here to emulate the intricate dynamics of an analog satisfiability (SAT) solver. In the presence of thermal noise, the MTJ based system can successfully solve Boolean satisfiability problems. Most importantly, our results exhibit that, the proposed MTJ based hardware SAT solver is capable of finding a solution to a significant fraction (at least 85%) of hard 3-SAT problems, within a time that has a polynomial relationship with the number of variables(<50).

A Hybrid Autonomic Computing-Based Approach to Distributed Constraint Satisfaction Problems

Directory of Open Access Journals (Sweden)

Abhishek Bhatia

2015-03-01

Full Text Available Distributed constraint satisfaction problems (DisCSPs are among the widely endeavored problems using agent-based simulation. Fernandez et al. formulated sensor and mobile tracking problem as a DisCSP, known as SensorDCSP In this paper, we adopt a customized ERE (environment, reactive rules and entities algorithm for the SensorDCSP, which is otherwise proven as a computationally intractable problem. An amalgamation of the autonomy-oriented computing (AOC-based algorithm (ERE and genetic algorithm (GA provides an early solution of the modeled DisCSP. Incorporation of GA into ERE facilitates auto-tuning of the simulation parameters, thereby leading to an early solution of constraint satisfaction. This study further contributes towards a model, built up in the NetLogo simulation environment, to infer the efficacy of the proposed approach.

Multiobjective CVaR Optimization Model and Solving Method for Hydrothermal System Considering Uncertain Load Demand

Directory of Open Access Journals (Sweden)

Zhongfu Tan

2015-01-01

Full Text Available In order to solve the influence of load uncertainty on hydrothermal power system operation and achieve the optimal objectives of system power generation consumption, pollutant emissions, and first-stage hydropower station storage capacity, this paper introduced CVaR method and built a multiobjective optimization model and its solving method. In the optimization model, load demand’s actual values and deviation values are regarded as random variables, scheduling objective is redefined to meet confidence level requirement and system operation constraints and loss function constraints are taken into consideration. To solve the proposed model, this paper linearized nonlinear constraints, applied fuzzy satisfaction, fuzzy entropy, and weighted multiobjective function theories to build a fuzzy entropy multiobjective CVaR model. The model is a mixed integer linear programming problem. Then, six thermal power plants and three cascade hydropower stations are taken as the hydrothermal system for numerical simulation. The results verified that multiobjective CVaR method is applicable to solve hydrothermal scheduling problems. It can better reflect risk level of the scheduling result. The fuzzy entropy satisfaction degree solving algorithm can simplify solving difficulty and get the optimum operation scheduling scheme.

Judgement of Design Scheme Based on Flexible Constraint in ICAD

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

The conception of flexible constraint is proposed in the paper. The solution of flexible constraint is in special range, and maybe different in different instances of same design scheme. The paper emphasis on how to evaluate and optimize a design scheme with flexible constraints based on the satisfaction degree function defined on flexible constraints. The conception of flexible constraint is used to solve constraint conflict and design optimization in complicated constraint-based assembly design by the PFM parametrization assembly design system. An instance of gear-box design is used for verifying optimization method.

Quiet planting in the locked constraints satisfaction problems

Energy Technology Data Exchange (ETDEWEB)

Zdeborova, Lenka [Los Alamos National Laboratory; Krzakala, Florent [Los Alamos National Laboratory

2009-01-01

We study the planted ensemble of locked constraint satisfaction problems. We describe the connection between the random and planted ensembles. The use of the cavity method is combined with arguments from reconstruction on trees and first and second moment considerations; in particular the connection with the reconstruction on trees appears to be crucial. Our main result is the location of the hard region in the planted ensemble, thus providing hard satisfiable benchmarks. In a part of that hard region instances have with high probability a single satisfying assignment.

What is adaptive about adaptive decision making? A parallel constraint satisfaction account.

Science.gov (United States)

Glöckner, Andreas; Hilbig, Benjamin E; Jekel, Marc

2014-12-01

There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns - as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular. Copyright © 2014 Elsevier B.V. All rights reserved.

Research on engineering-oriented constraints conflict detection in collaborative design of wire harness technology

Institute of Scientific and Technical Information of China (English)

LIU Xiaoping; HE Honglin; XU Benzhu

2012-01-01

Engineering-oriented constraint of harness technology has much information and project information presents progressive changes along with the design. Therefore, how to handle conflict resolution quickly is a problem to be solved. Process model of con- flict detection is put forward according to characteristics of harness technology design engineering-oriented constraint, and then two problems of how to conduct conflict positioning and judgment of constraint rules are introduced in this paper. Afterwards in this pa- per, constraint information directed acyclic graph is established by classified project constraint information to solve the conflict posi- tioning problem; solution of constraint satisfaction problem is applied to realize judgment problem of constraint rules. Finally, exam- ple is used to analyze the method in this paper to further verify the correctness and effectiveness of this method.

An empirical study on collective intelligence algorithms for video games problem-solving

OpenAIRE

González-Pardo, Antonio; Palero, Fernando; Camacho, David

2015-01-01

Computational intelligence (CI), such as evolutionary computation or swarm intelligence methods, is a set of bio-inspired algorithms that have been widely used to solve problems in areas like planning, scheduling or constraint satisfaction problems. Constrained satisfaction problems (CSP) have taken an important attention from the research community due to their applicability to real problems. Any CSP problem is usually modelled as a constrained graph where the edges represent a set of restri...

A Hybrid Method for Modeling and Solving Supply Chain Optimization Problems with Soft and Logical Constraints

Directory of Open Access Journals (Sweden)

Paweł Sitek

2016-01-01

Full Text Available This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP and constraint logic programming (CLP, were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems. The ECLiPSe system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.

Efficient Solving of Large Non-linear Arithmetic Constraint Systems with Complex Boolean Structure

Czech Academy of Sciences Publication Activity Database

Fränzle, M.; Herde, C.; Teige, T.; Ratschan, Stefan; Schubert, T.

2007-01-01

Roč. 1, - (2007), s. 209-236 ISSN 1574-0617 Grant - others:AVACS(DE) SFB/TR 14 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval-based arithmetic constraint solving * SAT modulo theories Subject RIV: BA - General Mathematics

Constraint-based scheduling applying constraint programming to scheduling problems

CERN Document Server

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...

DDeveloping and solving a bi-objective joint replenishment problem under storing space constraint

Directory of Open Access Journals (Sweden)

ommolbanin yousefi

2011-03-01

Full Text Available In this research, a bi-objective joint replenishment problem has been developed and solved with the assumption of one restricted resource. The proposed model has a storing space constraint and tries to optimize two objective functions simultaneously. They include minimizing annual holding and setup costs and minimizing annual inventory investment. Then, for solving this problem, a multi-objective genetic algorithm (MOGA has been developed. In order to analyze the algorithm efficiency, its performance has been examined in solving 1600 randomly produced problems using parameters extracted from literature. The findings imply that the proposed algorithm is capable of producing a good set of Pareto optimal solutions. Finally, the application of the problem solving approach and the findings of the proposed algorithm have been illustrated for a special problem, which has been randomly produced.

Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints

International Nuclear Information System (INIS)

Pothiya, Saravuth; Ngamroo, Issarachai; Kongprawechnon, Waree

2008-01-01

This paper presents a new optimization technique based on a multiple tabu search algorithm (MTS) to solve the dynamic economic dispatch (ED) problem with generator constraints. In the constrained dynamic ED problem, the load demand and spinning reserve capacity as well as some practical operation constraints of generators, such as ramp rate limits and prohibited operating zone are taken into consideration. The MTS algorithm introduces additional mechanisms such as initialization, adaptive searches, multiple searches, crossover and restarting process. To show its efficiency, the MTS algorithm is applied to solve constrained dynamic ED problems of power systems with 6 and 15 units. The results obtained from the MTS algorithm are compared to those achieved from the conventional approaches, such as simulated annealing (SA), genetic algorithm (GA), tabu search (TS) algorithm and particle swarm optimization (PSO). The experimental results show that the proposed MTS algorithm approaches is able to obtain higher quality solutions efficiently and with less computational time than the conventional approaches

Parallel constraint satisfaction in memory-based decisions.

Science.gov (United States)

Glöckner, Andreas; Hodges, Sara D

2011-01-01

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Optimizing Concurrent M3-Transactions: A Fuzzy Constraint Satisfaction Approach

Directory of Open Access Journals (Sweden)

Peng LI

2004-10-01

Full Text Available Due to the high connectivity and great convenience, many E-commerce application systems have a high transaction volume. Consequently, the system state changes rapidly and it is likely that customers issue transactions based on out-of-date state information. Thus, the potential of transaction abortion increases greatly. To address this problem, we proposed an M3-transaction model. An M3-transaction is a generalized transaction where users can issue their preferences in a request by specifying multiple criteria and optional data resources simultaneously within one transaction. In this paper, we introduce the transaction grouping and group evaluation techniques. We consider evaluating a group of M3-transactions arrived to the system within a short duration together. The system makes optimal decisions in allocating data to transactions to achieve better customer satisfaction and lower transaction failure rate. We apply the fuzzy constraint satisfaction approach for decision-making. We also conduct experimental studies to evaluate the performance of our approach. The results show that the M3-transaction with group evaluation is more resilient to failure and yields much better performance than the traditional transaction model.

Applying ant colony optimization metaheuristic to solve forest transportation planning problems with side constraints

Science.gov (United States)

Marco A. Contreras; Woodam Chung; Greg Jones

2008-01-01

Forest transportation planning problems (FTPP) have evolved from considering only the financial aspects of timber management to more holistic problems that also consider the environmental impacts of roads. These additional requirements have introduced side constraints, making FTPP larger and more complex. Mixed-integer programming (MIP) has been used to solve FTPP, but...

Solving the Einstein constraint equations on multi-block triangulations using finite element methods

Energy Technology Data Exchange (ETDEWEB)

Korobkin, Oleg; Pazos, Enrique [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA 70803 (United States); Aksoylu, Burak [Center for Computation and Technology, Louisiana State University, Baton Rouge, LA 70803 (United States); Holst, Michael [Department of Mathematics, University of California at San Diego 9500 Gilman Drive La Jolla, CA 92093-0112 (United States); Tiglio, Manuel [Department of Physics, University of Maryland, College Park, MD 20742 (United States)

2009-07-21

In order to generate initial data for nonlinear relativistic simulations, one needs to solve the Einstein constraints, which can be cast into a coupled set of nonlinear elliptic equations. Here we present an approach for solving these equations on three-dimensional multi-block domains using finite element methods. We illustrate our approach on a simple example of Brill wave initial data, with the constraints reducing to a single linear elliptic equation for the conformal factor psi. We use quadratic Lagrange elements on semi-structured simplicial meshes, obtained by triangulation of multi-block grids. In the case of uniform refinement the scheme is superconvergent at most mesh vertices, due to local symmetry of the finite element basis with respect to local spatial inversions. We show that in the superconvergent case subsequent unstructured mesh refinements do not improve the quality of our initial data. As proof of concept that this approach is feasible for generating multi-block initial data in three dimensions, after constructing the initial data we evolve them in time using a high-order finite-differencing multi-block approach and extract the gravitational waves from the numerical solution.

Solving the Einstein constraint equations on multi-block triangulations using finite element methods

International Nuclear Information System (INIS)

Korobkin, Oleg; Pazos, Enrique; Aksoylu, Burak; Holst, Michael; Tiglio, Manuel

2009-01-01

In order to generate initial data for nonlinear relativistic simulations, one needs to solve the Einstein constraints, which can be cast into a coupled set of nonlinear elliptic equations. Here we present an approach for solving these equations on three-dimensional multi-block domains using finite element methods. We illustrate our approach on a simple example of Brill wave initial data, with the constraints reducing to a single linear elliptic equation for the conformal factor ψ. We use quadratic Lagrange elements on semi-structured simplicial meshes, obtained by triangulation of multi-block grids. In the case of uniform refinement the scheme is superconvergent at most mesh vertices, due to local symmetry of the finite element basis with respect to local spatial inversions. We show that in the superconvergent case subsequent unstructured mesh refinements do not improve the quality of our initial data. As proof of concept that this approach is feasible for generating multi-block initial data in three dimensions, after constructing the initial data we evolve them in time using a high-order finite-differencing multi-block approach and extract the gravitational waves from the numerical solution.

Implicit Motives and Men's Perceived Constraint in Fatherhood.

Science.gov (United States)

Ruppen, Jessica; Waldvogel, Patricia; Ehlert, Ulrike

2016-01-01

Research shows that implicit motives influence social relationships. However, little is known about their role in fatherhood and, particularly, how men experience their paternal role. Therefore, this study examined the association of implicit motives and fathers' perceived constraint due to fatherhood. Furthermore, we explored their relation to fathers' life satisfaction. Participants were fathers with biological children ( N = 276). They were asked to write picture stories, which were then coded for implicit affiliation and power motives. Perceived constraint and life satisfaction were assessed on a visual analog scale. A higher implicit need for affiliation was significantly associated with lower perceived constraint, whereas the implicit need for power had the opposite effect. Perceived constraint had a negative influence on life satisfaction. Structural equation modeling revealed significant indirect effects of implicit affiliation and power motives on life satisfaction mediated by perceived constraint. Our findings indicate that men with a higher implicit need for affiliation experience less constraint due to fatherhood, resulting in higher life satisfaction. The implicit need for power, however, results in more perceived constraint and is related to decreased life satisfaction.

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...

A General Connectionist Model of Attitude Structure and Change: The ACS (Attitudes as Constraint Satisfaction) Model

Science.gov (United States)

Monroe, Brian M.; Read, Stephen J.

2008-01-01

A localist, parallel constraint satisfaction, artificial neural network model is presented that accounts for a broad collection of attitude and attitude-change phenomena. The network represents the attitude object and cognitions and beliefs related to the attitude, as well as how to integrate a persuasive message into this network. Short-term…

Learning and Parallelization Boost Constraint Search

Science.gov (United States)

Yun, Xi

2013-01-01

Constraint satisfaction problems are a powerful way to abstract and represent academic and real-world problems from both artificial intelligence and operations research. A constraint satisfaction problem is typically addressed by a sequential constraint solver running on a single processor. Rather than construct a new, parallel solver, this work…

Implicit Motives and Men’s Perceived Constraint in Fatherhood

Science.gov (United States)

Ruppen, Jessica; Waldvogel, Patricia; Ehlert, Ulrike

2016-01-01

Research shows that implicit motives influence social relationships. However, little is known about their role in fatherhood and, particularly, how men experience their paternal role. Therefore, this study examined the association of implicit motives and fathers’ perceived constraint due to fatherhood. Furthermore, we explored their relation to fathers’ life satisfaction. Participants were fathers with biological children (N = 276). They were asked to write picture stories, which were then coded for implicit affiliation and power motives. Perceived constraint and life satisfaction were assessed on a visual analog scale. A higher implicit need for affiliation was significantly associated with lower perceived constraint, whereas the implicit need for power had the opposite effect. Perceived constraint had a negative influence on life satisfaction. Structural equation modeling revealed significant indirect effects of implicit affiliation and power motives on life satisfaction mediated by perceived constraint. Our findings indicate that men with a higher implicit need for affiliation experience less constraint due to fatherhood, resulting in higher life satisfaction. The implicit need for power, however, results in more perceived constraint and is related to decreased life satisfaction. PMID:27933023

Implicit Motives and Men’s Perceived Constraint in Fatherhood

Directory of Open Access Journals (Sweden)

Jessica Ruppen

2016-11-01

Full Text Available Research shows that implicit motives influence social relationships. However, little is known about their role in fatherhood and, particularly, how men experience their paternal role. Therefore, this study examined the association of implicit motives and fathers’ perceived constraint due to fatherhood. Furthermore, we explored their relation to fathers’ life satisfaction. Participants were fathers with biological children (N = 276. They were asked to write picture stories, which were then coded for implicit affiliation and power motives. Perceived constraint and life satisfaction were assessed on a visual analog scale. A higher implicit need for affiliation was significantly associated with lower perceived constraint, whereas the implicit need for power had the opposite effect. Perceived constraint had a negative influence on life satisfaction. Structural equation modeling revealed significant indirect effects of implicit affiliation and power motives on life satisfaction mediated by perceived constraint. Our findings indicate that men with a higher implicit need for affiliation experience less constraint due to fatherhood, resulting in higher life satisfaction. The implicit need for power, however, results in more perceived constraint and is related to decreased life satisfaction.

AN INVESTIGATION OF RELATIONSHIP BETWEEN LEADERSHIP STYLES OF HUMAN RESOURCES MANAGER, CREATIVE PROBLEM SOLVING CAPACITY AND CAREER SATISFACTION: AN EMPIRICAL STUDY

Directory of Open Access Journals (Sweden)

Hüseyin YILMAZ

2016-12-01

Full Text Available The aim of this study is the creative problem-solving capacity of the organization with leadership behaviors of human resources managers and employees to examine the relationship between career satisfaction and is tested empirically. Research within the scope of the required data structured questionnaire method, operating in the province of Aydin was obtained from 130 employees working in five star hotels. Democratic leadership style according to the factor analysis, easygoing, participants converter, and releasing autocratic leadership dimensions were determined. According to the analysis, the dependent variable with a significant level of research and positive leadership style has been determined that no relationships. Regression analysis revealed that the leadership of the relationship with the creative problem-solving capacity of democratic leadership in style when found to be stronger than other leadership styles, while the variable describing the career of the employee satisfaction level of the maximum it was concluded that the creative problem-solving capacity of the organization. Research in the context of human resources on the very important for organizations, leadership behavior, creative problem-solving capacity and career satisfaction studies analyzing the relationships between variables it seems to be quite limited. The discovery by analyzing the relationship between the aforementioned variables, can make significant contributions to knowledge in the literature and are expected to form the basis for future research.

Graphical constraints: a graphical user interface for constraint problems

OpenAIRE

Vieira, Nelson Manuel Marques

2015-01-01

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embrace...

Using Coevolution Genetic Algorithm with Pareto Principles to Solve Project Scheduling Problem under Duration and Cost Constraints

Directory of Open Access Journals (Sweden)

Alexandr Victorovich Budylskiy

2014-06-01

Full Text Available This article considers the multicriteria optimization approach using the modified genetic algorithm to solve the project-scheduling problem under duration and cost constraints. The work contains the list of choices for solving this problem. The multicriteria optimization approach is justified here. The study describes the Pareto principles, which are used in the modified genetic algorithm. We identify the mathematical model of the project-scheduling problem. We introduced the modified genetic algorithm, the ranking strategies, the elitism approaches. The article includes the example.

Entropy landscape and non-Gibbs solutions in constraint satisfaction problems

International Nuclear Information System (INIS)

Dall'Asta, L.; Ramezanpour, A.; Zecchina, R.

2008-05-01

We study the entropy landscape of solutions for the bicoloring problem in random graphs, a representative difficult constraint satisfaction problem. Our goal is to classify which type of clusters of solutions are addressed by different algorithms. In the first part of the study we use the cavity method to obtain the number of clusters with a given internal entropy and determine the phase diagram of the problem, e.g. dynamical, rigidity and SAT-UNSAT transitions. In the second part of the paper we analyze different algorithms and locate their behavior in the entropy landscape of the problem. For instance we show that a smoothed version of a decimation strategy based on Belief Propagation is able to find solutions belonging to sub-dominant clusters even beyond the so called rigidity transition where the thermodynamically relevant clusters become frozen. These non-equilibrium solutions belong to the most probable unfrozen clusters. (author)

A message-passing approach to random constraint satisfaction problems with growing domains

International Nuclear Information System (INIS)

Zhao, Chunyan; Zheng, Zhiming; Zhou, Haijun; Xu, Ke

2011-01-01

Message-passing algorithms based on belief propagation (BP) are implemented on a random constraint satisfaction problem (CSP) referred to as model RB, which is a prototype of hard random CSPs with growing domain size. In model RB, the number of candidate discrete values (the domain size) of each variable increases polynomially with the variable number N of the problem formula. Although the satisfiability threshold of model RB is exactly known, finding solutions for a single problem formula is quite challenging and attempts have been limited to cases of N ∼ 10 2 . In this paper, we propose two different kinds of message-passing algorithms guided by BP for this problem. Numerical simulations demonstrate that these algorithms allow us to find a solution for random formulas of model RB with constraint tightness slightly less than p cr , the threshold value for the satisfiability phase transition. To evaluate the performance of these algorithms, we also provide a local search algorithm (random walk) as a comparison. Besides this, the simulated time dependence of the problem size N and the entropy of the variables for growing domain size are discussed

Constraint programming for modelling and solving modal satisfiability

NARCIS (Netherlands)

Brand, S.; Gennari, R.; de Rijke, M.

2003-01-01

We explore to what extent and how efficiently constraint programmingcan be used in the context of automated reasoning for modal logics. We encode modal satisfiability problems as constraint satisfactionproblems with non-boolean domains, together with suitable constraints.Experiments show that the

Neural Based Tabu Search method for solving unit commitment problem with cooling-banking constraints

Directory of Open Access Journals (Sweden)

Rajan Asir Christober Gnanakkan Charles

2009-01-01

Full Text Available This paper presents a new approach to solve short-term unit commitment problem (UCP using Neural Based Tabu Search (NBTS with cooling and banking constraints. 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 next H hours. A 7-unit utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 10, 26 and 34 units. Numerical results are shown to compare the superiority of the cost solutions obtained using the Tabu Search (TS method, Dynamic Programming (DP and Lagrangian Relaxation (LR methods in reaching proper unit commitment.

Constraint solving for direct manipulation of features

NARCIS (Netherlands)

Lourenco, D.; Oliveira, P.; Noort, A.; Bidarra, R.

2006-01-01

In current commercial feature modeling systems, support for direct manipulation of features is not commonly available. This is partly due to the strong reliance of such systems on constraints, but also to the lack of speed of current constraint solvers. In this paper, an approach to the optimization

Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets

KAUST Repository

Lenzen, F.

2014-01-01

© 2014 Society for Industrial and Applied Mathematics. We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied both theoretical and numerical issues. While we were able to show the existence of solutions for a relatively broad class of problems, we encountered difficulties concerning uniqueness of the solution as well as convergence of existing algorithms for solving QVIs. In particular, it seemed that with increasing image size the growing condition number of the involved differential operator posed severe problems. In the present paper we prove uniqueness for a larger class of problems, particularly independent of the image size. Moreover, we provide a numerical algorithm with proved convergence. Experimental results support our theoretical findings.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Directory of Open Access Journals (Sweden)

Mark G Orr

Full Text Available The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior, does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence. To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Science.gov (United States)

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

Solving binary-state multi-objective reliability redundancy allocation series-parallel problem using efficient epsilon-constraint, multi-start partial bound enumeration algorithm, and DEA

International Nuclear Information System (INIS)

Khalili-Damghani, Kaveh; Amiri, Maghsoud

2012-01-01

In this paper, a procedure based on efficient epsilon-constraint method and data envelopment analysis (DEA) is proposed for solving binary-state multi-objective reliability redundancy allocation series-parallel problem (MORAP). In first module, a set of qualified non-dominated solutions on Pareto front of binary-state MORAP is generated using an efficient epsilon-constraint method. In order to test the quality of generated non-dominated solutions in this module, a multi-start partial bound enumeration algorithm is also proposed for MORAP. The performance of both procedures is compared using different metrics on well-known benchmark instance. The statistical analysis represents that not only the proposed efficient epsilon-constraint method outperform the multi-start partial bound enumeration algorithm but also it improves the founded upper bound of benchmark instance. Then, in second module, a DEA model is supplied to prune the generated non-dominated solutions of efficient epsilon-constraint method. This helps reduction of non-dominated solutions in a systematic manner and eases the decision making process for practical implementations. - Highlights: ► A procedure based on efficient epsilon-constraint method and DEA was proposed for solving MORAP. ► The performance of proposed procedure was compared with a multi-start PBEA. ► Methods were statistically compared using multi-objective metrics.

Revisiting the simplicity constraints and coherent intertwiners

International Nuclear Information System (INIS)

Dupuis, Maite; Livine, Etera R

2011-01-01

In the context of loop quantum gravity and spinfoam models, the simplicity constraints are essential in that they allow one to write general relativity as a constrained topological BF theory. In this work, we apply the recently developed U(N) framework for SU(2) intertwiners to the issue of imposing the simplicity constraints to spin network states. More particularly, we focus on solving on individual intertwiners in the 4D Euclidean theory. We review the standard way of solving the simplicity constraints using coherent intertwiners and we explain how these fit within the U(N) framework. Then we show how these constraints can be written as a closed u(N) algebra and we propose a set of U(N) coherent states that solves all the simplicity constraints weakly for an arbitrary Immirzi parameter.

Variations Method to Solve Terminal Problems for the Second Order Systems of Canonical Form with State Constraints

Directory of Open Access Journals (Sweden)

T. S. Kasatkina

2015-01-01

Full Text Available Terminal control problem with fixed finite time for the second order affine systems with state constraints is considered. A solution of such terminal problem is suggested for the systems with scalar control of regular canonical form.In this article it is shown that the initial terminal problem is equivalent to the problem of auxiliary function search. This function should satisfy some conditions. Such function design consists of two stages. The first stage includes search of function which corresponds the solution of the terminal control problem without state constraints. This function is designed as polynom of the fifth power which depends on time variable. Coefficients of the polynom are defined by boundary conditions. The second stage includes modification of designed function if corresponding to that function trajectory is not satisfied constraints. Modification process is realized by adding to the current function supplementary polynom. Influence of that polynom handles by variation of a parameter value. Modification process can include a few iterations. After process termination continuous control is found. This control is the solution of the initial terminal prUsing presented scheme the terminal control problem for system, which describes oscillations of the mathematical pendulum, is solved. This approach can be used for the solution of terminal control problems with state constraints for affine systems with multi-dimensional control.

From near to eternity: Spin-glass planting, tiling puzzles, and constraint-satisfaction problems

Science.gov (United States)

Hamze, Firas; Jacob, Darryl C.; Ochoa, Andrew J.; Perera, Dilina; Wang, Wenlong; Katzgraber, Helmut G.

2018-04-01

We present a methodology for generating Ising Hamiltonians of tunable complexity and with a priori known ground states based on a decomposition of the model graph into edge-disjoint subgraphs. The idea is illustrated with a spin-glass model defined on a cubic lattice, where subproblems, whose couplers are restricted to the two values {-1 ,+1 } , are specified on unit cubes and are parametrized by their local degeneracy. The construction is shown to be equivalent to a type of three-dimensional constraint-satisfaction problem known as the tiling puzzle. By varying the proportions of subproblem types, the Hamiltonian can span a dramatic range of typical computational complexity, from fairly easy to many orders of magnitude more difficult than prototypical bimodal and Gaussian spin glasses in three space dimensions. We corroborate this behavior via experiments with different algorithms and discuss generalizations and extensions to different types of graphs.

Constraint-Muse: A Soft-Constraint Based System for Music Therapy

Science.gov (United States)

Hölzl, Matthias; Denker, Grit; Meier, Max; Wirsing, Martin

Monoidal soft constraints are a versatile formalism for specifying and solving multi-criteria optimization problems with dynamically changing user preferences. We have developed a prototype tool for interactive music creation, called Constraint Muse, that uses monoidal soft constraints to ensure that a dynamically generated melody harmonizes with input from other sources. Constraint Muse provides an easy to use interface based on Nintendo Wii controllers and is intended to be used in music therapy for people with Parkinson’s disease and for children with high-functioning autism or Asperger’s syndrome.

Comparing Mixed & Integer Programming vs. Constraint Programming by solving Job-Shop Scheduling Problems

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.

Finding Deadlocks of Event-B Models by Constraint Solving

DEFF Research Database (Denmark)

Hallerstede, Stefan; Leuschel, Michael

we propose a constraint-based approach to nding deadlocks employing the ProB constraint solver to nd values for the constants and variables of formal models that describe a deadlocking state. We discuss the principles of the technique implemented in ProB's Prolog kernel and present some results...

Nurses Returning to School: Motivators, Inhibitors and Job Satisfaction.

Science.gov (United States)

Harris, Patrick W; Burman, Mary E

2016-01-01

Health care employers and national nursing organizations are placing increased emphasis on nurses earning a baccalaureate degree or higher. This study examines the impact of motivators (professional and personal motivation), inhibitors (time constraints and employer discouragement), and job satisfaction on intent to return to school. Approximately half of the employed nurses in Wyoming were surveyed using a mailed questionnaire in the summer of 2013. Perceived employer discouragement and time constraints continued to play a direct role on intent to return to school regardless of nurse motivation or job satisfaction. However, motivation and job satisfaction also contributed to a nurse's intent to return to school. These results suggest that motivation and job satisfaction are significant regarding intent to return to school but can be limited by both perceived discouragement of one's employer and perceived time constraints. In order to meet the increasing demands of a better-educated nursing workforce, a shift in workplace dynamics may be warranted. Copyright © 2016 Elsevier Inc. All rights reserved.

Solving a Novel Inventory Location Model with Stochastic Constraints and (R,s,S Inventory Control Policy

Directory of Open Access Journals (Sweden)

Guillermo Cabrera

2013-01-01

Full Text Available We solve a novel inventory-location model with a stochastic capacity constraint based on a periodic inventory control (ILM-PR policy. The ILM-PR policy implies several changes with regard to other previous models proposed in the literature, which consider continuous review as their inventory policy. One of these changes is the inclusion of the undershoot concept, which has not been considered in previous ILM models in the literature. Based on our model, we are able to design a distribution network for a two-level supply chain, addressing both warehouse location and customer assignment decisions, whilst taking into consideration several aspects of inventory planning, in particular, evaluating the impact of the inventory control review period on the network configuration and system costs. Because the model is a very hard-to solve combinatorial nonlinear optimisation problem, we implemented two heuristics to solve it, namely, Tabu Search and Particle Swarm Optimisation. These approaches were tested over small instances in which they were able to find the optimal solution in just a few seconds. Because the model is a new one, a set of medium-size instances is provided that can be useful as a benchmark in future research. The heuristics showed a good convergence rate when applied to those instances. The results confirm that decision making over the inventory control policy has effects on the distribution network design.

Local entropy as a measure for sampling solutions in constraint satisfaction problems

International Nuclear Information System (INIS)

Baldassi, Carlo; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo

2016-01-01

We introduce a novel entropy-driven Monte Carlo (EdMC) strategy to efficiently sample solutions of random constraint satisfaction problems (CSPs). First, we extend a recent result that, using a large-deviation analysis, shows that the geometry of the space of solutions of the binary perceptron learning problem (a prototypical CSP), contains regions of very high-density of solutions. Despite being sub-dominant, these regions can be found by optimizing a local entropy measure. Building on these results, we construct a fast solver that relies exclusively on a local entropy estimate, and can be applied to general CSPs. We describe its performance not only for the perceptron learning problem but also for the random K-satisfiabilty problem (another prototypical CSP with a radically different structure), and show numerically that a simple zero-temperature Metropolis search in the smooth local entropy landscape can reach sub-dominant clusters of optimal solutions in a small number of steps, while standard Simulated Annealing either requires extremely long cooling procedures or just fails. We also discuss how the EdMC can heuristically be made even more efficient for the cases we studied. (paper: disordered systems, classical and quantum)

AN INVESTIGATION OF RELATIONSHIP BETWEEN LEADERSHIP STYLES OF HUMAN RESOURCES MANAGER, CREATIVE PROBLEM SOLVING CAPACITY AND CAREER SATISFACTION: AN EMPIRICAL STUDY

OpenAIRE

Hüseyin YILMAZ

2016-01-01

The aim of this study is the creative problem-solving capacity of the organization with leadership behaviors of human resources managers and employees to examine the relationship between career satisfaction and is tested empirically. Research within the scope of the required data structured questionnaire method, operating in the province of Aydin was obtained from 130 employees working in five star hotels. Democratic leadership style according to the factor analysis, easygoing, participants c...

An Integer Programming Approach to Solving Tantrix on Fixed Boards

Directory of Open Access Journals (Sweden)

Yushi Uno

2012-03-01

Full Text Available Tantrix (Tantrix R ⃝ is a registered trademark of Colour of Strategy Ltd. in New Zealand, and of TANTRIX JAPAN in Japan, respectively, under the license of M. McManaway, the inventor. is a puzzle to make a loop by connecting lines drawn on hexagonal tiles, and the objective of this research is to solve it by a computer. For this purpose, we first give a problem setting of solving Tantrix as making a loop on a given fixed board. We then formulate it as an integer program by describing the rules of Tantrix as its constraints, and solve it by a mathematical programming solver to have a solution. As a result, we establish a formulation that can solve Tantrix of moderate size, and even when the solutions are invalid only by elementary constraints, we achieved it by introducing additional constraints and re-solve it. By this approach we succeeded to solve Tantrix of size up to 60.

Identifying Social Satisfaction from Social Media

OpenAIRE

Bai, Shuotian; Gao, Rui; Hao, Bibo; Yuan, Sha; Zhu, Tingshao

2014-01-01

We demonstrate the critical need to identify social situation and instability factors by acquiring public social satisfaction in this research. However, subject to the large amount of manual work cost in subject recruitment and data processing, conventional self-reported method cannot be implemented in real time or applied in large scale investigation. To solve the problem, this paper proposed an approach to predict users' social satisfaction, especially for the economy-related satisfaction b...

Constraint-based Word Segmentation for Chinese

DEFF Research Database (Denmark)

Christiansen, Henning; Bo, Li

2014-01-01

-hoc and statistically based methods. In this paper, we show experiments of implementing different approaches to CWSP in the framework of CHR Grammars [Christiansen, 2005] that provides a constraint solving approach to language analysis. CHR Grammars are based upon Constraint Handling Rules, CHR [Frühwirth, 1998, 2009......], which is a declarative, high-level programming language for specification and implementation of constraint solvers....

Constraint-based solver for the Military unit path finding problem

CSIR Research Space (South Africa)

Leenen, L

2010-04-01

Full Text Available -based approach because it requires flexibility in modelling. The authors formulate the MUPFP as a constraint satisfaction problem and a constraint-based extension of the search algorithm. The concept demonstrator uses a provided map, for example taken from Google...

Constraint-based reachability

Directory of Open Access Journals (Sweden)

Arnaud Gotlieb

2013-02-01

Full Text Available Iterative imperative programs can be considered as infinite-state systems computing over possibly unbounded domains. Studying reachability in these systems is challenging as it requires to deal with an infinite number of states with standard backward or forward exploration strategies. An approach that we call Constraint-based reachability, is proposed to address reachability problems by exploring program states using a constraint model of the whole program. The keypoint of the approach is to interpret imperative constructions such as conditionals, loops, array and memory manipulations with the fundamental notion of constraint over a computational domain. By combining constraint filtering and abstraction techniques, Constraint-based reachability is able to solve reachability problems which are usually outside the scope of backward or forward exploration strategies. This paper proposes an interpretation of classical filtering consistencies used in Constraint Programming as abstract domain computations, and shows how this approach can be used to produce a constraint solver that efficiently generates solutions for reachability problems that are unsolvable by other approaches.

Synthesis of models for order-sorted first-order theories using linear algebra and constraint solving

Directory of Open Access Journals (Sweden)

Salvador Lucas

2015-12-01

Full Text Available Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.

Phase-Field Relaxation of Topology Optimization with Local Stress Constraints

DEFF Research Database (Denmark)

Stainko, Roman; Burger, Martin

2006-01-01

inequality constraints. We discretize the problem by finite elements and solve the arising finite-dimensional programming problems by a primal-dual interior point method. Numerical experiments for problems with local stress constraints based on different criteria indicate the success and robustness......We introduce a new relaxation scheme for structural topology optimization problems with local stress constraints based on a phase-field method. In the basic formulation we have a PDE-constrained optimization problem, where the finite element and design analysis are solved simultaneously...

Momentum constraint relaxation

International Nuclear Information System (INIS)

Marronetti, Pedro

2006-01-01

Full relativistic simulations in three dimensions invariably develop runaway modes that grow exponentially and are accompanied by violations of the Hamiltonian and momentum constraints. Recently, we introduced a numerical method (Hamiltonian relaxation) that greatly reduces the Hamiltonian constraint violation and helps improve the quality of the numerical model. We present here a method that controls the violation of the momentum constraint. The method is based on the addition of a longitudinal component to the traceless extrinsic curvature A ij -tilde, generated by a vector potential w i , as outlined by York. The components of w i are relaxed to solve approximately the momentum constraint equations, slowly pushing the evolution towards the space of solutions of the constraint equations. We test this method with simulations of binary neutron stars in circular orbits and show that it effectively controls the growth of the aforementioned violations. We also show that a full numerical enforcement of the constraints, as opposed to the gentle correction of the momentum relaxation scheme, results in the development of instabilities that stop the runs shortly

Robust Model Predictive Control Using Linear Matrix Inequalities for the Treatment of Asymmetric Output Constraints

Directory of Open Access Journals (Sweden)

Mariana Santos Matos Cavalca

2012-01-01

Full Text Available One of the main advantages of predictive control approaches is the capability of dealing explicitly with constraints on the manipulated and output variables. However, if the predictive control formulation does not consider model uncertainties, then the constraint satisfaction may be compromised. A solution for this inconvenience is to use robust model predictive control (RMPC strategies based on linear matrix inequalities (LMIs. However, LMI-based RMPC formulations typically consider only symmetric constraints. This paper proposes a method based on pseudoreferences to treat asymmetric output constraints in integrating SISO systems. Such technique guarantees robust constraint satisfaction and convergence of the state to the desired equilibrium point. A case study using numerical simulation indicates that satisfactory results can be achieved.

Solving University Scheduling Problem Using Hybrid Approach

Directory of Open Access Journals (Sweden)

Aftab Ahmed Shaikh

2011-10-01

Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.

Constraint Embedding for Multibody System Dynamics

Science.gov (United States)

Jain, Abhinandan

2009-01-01

This paper describes a constraint embedding approach for the handling of local closure constraints in multibody system dynamics. The approach uses spatial operator techniques to eliminate local-loop constraints from the system and effectively convert the system into tree-topology systems. This approach allows the direct derivation of recursive O(N) techniques for solving the system dynamics and avoiding the expensive steps that would otherwise be required for handling the closedchain dynamics. The approach is very effective for systems where the constraints are confined to small-subgraphs within the system topology. The paper provides background on the spatial operator O(N) algorithms, the extensions for handling embedded constraints, and concludes with some examples of such constraints.

A combined constraint handling framework: an empirical study

DEFF Research Database (Denmark)

Si, Chengyong; Hu, Junjie; Lan, Tian

2017-01-01

This paper presents a new combined constraint handling framework (CCHF) for solving constrained optimization problems (COPs). The framework combines promising aspects of different constraint handling techniques (CHTs) in different situations with consideration of problem characteristics. In order...

Design and Evaluation of the User-Adapted Program Scheduling system based on Bayesian Network and Constraint Satisfaction

Science.gov (United States)

Iwasaki, Hirotoshi; Sega, Shinichiro; Hiraishi, Hironori; Mizoguchi, Fumio

In recent years, lots of music content can be stored in mobile computing devices, such as a portable digital music player and a car navigation system. Moreover, various information content like news or traffic information can be acquired always anywhere by a cellular communication and a wireless LAN. However, usability issues arise from the simple interfaces of mobile computing devices. Moreover, retrieving and selecting such content poses safety issues, especially while driving. Thus, it is important for the mobile system to recommend content automatically adapted to user's preference and situation. In this paper, we present the user-adapted program scheduling that generates sequences of content (Program) suiting user's preference and situation based on the Bayesian network and the Constraint Satisfaction Problem (CSP) technique. We also describe the design and evaluation of its realization system, the Personal Program Producer (P3). First, preference such as a genre ratio of content in a program is learned as a Bayesian network model using simple operations such as a skip behavior. A model including each content tends to become large-scale. In order to make it small, we present the model separation method that carries out losslessly compression of the model. Using the model, probabilistic distributions of preference to generate constraints are inferred. Finally satisfying the constraints, a program is produced. This kind of CSP has an issue of which the number of variables is not fixedness. In order to make it variable, we propose a method using metavariables. To evaluate the above methods, we applied them to P3 on a car navigation system. User evaluations helped us clarify that the P3 can produce the program that a user prefers and adapt it to the user.

A comparison of Heuristic method and Llewellyn’s rules for identification of redundant constraints

Science.gov (United States)

Estiningsih, Y.; Farikhin; Tjahjana, R. H.

2018-03-01

Important techniques in linear programming is modelling and solving practical optimization. Redundant constraints are consider for their effects on general linear programming problems. Identification and reduce redundant constraints are for avoidance of all the calculations associated when solving an associated linear programming problems. Many researchers have been proposed for identification redundant constraints. This paper a compararison of Heuristic method and Llewellyn’s rules for identification of redundant constraints.

Predictors of employer satisfaction: technical and non-technical skills.

Science.gov (United States)

Danielson, Jared A; Wu, Tsui-Feng; Fales-Williams, Amanda J; Kirk, Ryan A; Preast, Vanessa A

2012-01-01

Employers of 2007-2009 graduates from Iowa State University College of Veterinary Medicine were asked to respond to a survey regarding their overall satisfaction with their new employees as well as their new employees' preparation in several technical and non-technical skill areas. Seventy-five responses contained complete data and were used in the analysis. Four technical skill areas (data collection, data interpretation, planning, and taking action) and five non-technical skill areas (interpersonal skills, ability to deal with legal issues, business skills, making referrals, and problem solving) were identified. All of the skill area subscales listed above had appropriate reliability (Cronbach's alpha>0.70) and were positively and significantly correlated with overall employer satisfaction. Results of two simultaneous regression analyses indicated that of the four technical skill areas, taking action is the most salient predictor of employer satisfaction. Of the five non-technical skill areas, interpersonal skills, business skills, making referrals, and problem solving were the most important skills in predicting employer satisfaction. Hierarchical regression analysis revealed that all technical skills explained 25% of the variation in employer satisfaction; non-technical skills explained an additional 42% of the variation in employer satisfaction.

Optimal Portfolio Choice with Wash Sale Constraints

DEFF Research Database (Denmark)

Astrup Jensen, Bjarne; Marekwica, Marcel

2011-01-01

We analytically solve the portfolio choice problem in the presence of wash sale constraints in a two-period model with one risky asset. Our results show that wash sale constraints can heavily affect portfolio choice of investors with unrealized losses. The trading behavior of such investors...

Transformational and derivational strategies in analogical problem solving.

Science.gov (United States)

Schelhorn, Sven-Eric; Griego, Jacqueline; Schmid, Ute

2007-03-01

Analogical problem solving is mostly described as transfer of a source solution to a target problem based on the structural correspondences (mapping) between source and target. Derivational analogy (Carbonell, Machine learning: an artificial intelligence approach Los Altos. Morgan Kaufmann, 1986) proposes an alternative view: a target problem is solved by replaying a remembered problem-solving episode. Thus, the experience with the source problem is used to guide the search for the target solution by applying the same solution technique rather than by transferring the complete solution. We report an empirical study using the path finding problems presented in Novick and Hmelo (J Exp Psychol Learn Mem Cogn 20:1296-1321, 1994) as material. We show that both transformational and derivational analogy are problem-solving strategies realized by human problem solvers. Which strategy is evoked in a given problem-solving context depends on the constraints guiding object-to-object mapping between source and target problem. Specifically, if constraints facilitating mapping are available, subjects are more likely to employ a transformational strategy, otherwise they are more likely to use a derivational strategy.

Social support, problem solving, and the longitudinal course of newlywed marriage.

Science.gov (United States)

Sullivan, Kieran T; Pasch, Lauri A; Johnson, Matthew D; Bradbury, Thomas N

2010-04-01

Married couples (N = 172) were observed as newlyweds and observed again 1 year later while engaging in 2 problem-solving and 2 personal support discussions. Microanalytic coding of these conversations was used to examine associations between problem-solving and social support behaviors for 1 year and their relative contributions to 10-year trajectories of self-reported relationship satisfaction and dissolution. Results demonstrated that initially lower levels of positive support behaviors and higher levels of negative support behaviors predicted 1-year increases in negative emotion displayed during problem-solving conversations. Emotions coded from the initial problem-solving conversations did not predict 1-year changes in social support behaviors. Controlling for emotions displayed during problem-solving interactions eliminated or reduced associations between initial social support behaviors and (a) later levels of satisfaction and (b) relationship dissolution. These findings corroborate models that prioritize empathy, validation, and caring as key elements in the development of intimacy (e.g., Reis & Shaver, 1988) and suggest that deficits in these domains foreshadow deterioration in problem solving and conflict management. Implications for integrating support and problem solving in models of relationship change are outlined, as are implications for incorporating social support in education programs for developing relationships.

Machine tongues. X. Constraint languages

Energy Technology Data Exchange (ETDEWEB)

Levitt, D.

Constraint languages and programming environments will help the designer produce a lucid description of a problem domain, and then of particular situations and problems in it. Early versions of these languages were given descriptions of real world domain constraints, like the operation of electrical and mechanical parts. More recently, the author has automated a vocabulary for describing musical jazz phrases, using constraint language as a jazz improviser. General constraint languages will handle all of these domains. Once the model is in place, the system will connect built-in code fragments and algorithms to answer questions about situations; that is, to help solve problems. Bugs will surface not in code, but in designs themselves. 15 references.

The effect of job organizational factors on job satisfaction in two automotive industries in Malaysia.

Science.gov (United States)

Dawal, Siti Zawiah Md; Taha, Zahari

2007-12-01

A methodology is developed in diagnosing the effect of job organizational factors on job satisfaction in two automotive industries in Malaysia. One hundred and seventy male subjects of age 18-40 years with the mean age of 26.8 and standard deviation (SD) of 5.3 years and the mean work experience of 6.5 years and SD of 4.9 years took part in the study. Five job organizational factors were tested in the study including job rotation, work method, training, problem solving and goal setting. A job organization questionnaire was designed and was based on respondents' perception in relation to job satisfaction. The results showed that job organization factors were significantly related to job satisfaction. Job rotation, work method, training and goal setting showed strong correlation with job satisfaction while problem solving had intermediate correlation in the first automotive industry. On the other hand, most job organization factors showed intermediate correlation with job satisfaction in the second automotive industry except the training factor which had low correlation with job satisfaction. These results highlight that job rotation, work methods, problem solving and goal setting are outstanding factors in the study of job satisfaction for automotive industries.

An integrated model to measure service management and physical constraints' effect on food consumption in assisted-living facilities.

Science.gov (United States)

Huang, Hui-Chun; Shanklin, Carol W

2008-05-01

The United States is experiencing remarkable growth in the elderly population, which provides both opportunities and challenges for assisted-living facilities. The objective of this study was to explore how service management influences residents' actual food consumption in assisted-living facilities. Physical factors influencing residents' service evaluation and food consumption also were investigated. A total of 394 questionnaires were distributed to assisted-living residents in seven randomly selected facilities. The questionnaire was developed based on an in-depth literature review and pilot study. Residents' perceived quality evaluations, satisfaction, and physical constraints were measured. Residents' actual food consumption was measured using a plate waste technique. A total of 118 residents in five facilities completed both questionnaires and food consumption assessments. Descriptive, multivariate analyses and structural equation modeling techniques were employed. Service management, including food and service quality and customer satisfaction, was found to significantly influence residents' food consumption. Physical constraints associated with aging, including a decline in health status, chewing problems, sensory loss, and functional disability, also significantly influenced residents' food consumption. A significant relationship was found between physical constraints and customer satisfaction. Foodservice that provides good food and service quality increases customer satisfaction and affects residents' actual food consumption. Physical constraints also influence residents' food consumption directly, or indirectly through satisfaction. The findings suggest that food and nutrition professionals in assisted-living should consider the physical profiles of their residents to enhance residents' satisfaction and nutrient intake. Recommendations for exploring residents' perspectives are discussed.

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 ...

A Constraint Model for Constrained Hidden Markov Models

DEFF Research Database (Denmark)

Christiansen, Henning; Have, Christian Theil; Lassen, Ole Torp

2009-01-01

A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we extend HMMs with constraints and show how the familiar Viterbi algorithm can be generalized, based on constraint solving ...

Enhancing the Effectiveness of Problem-Solving Processes through Employee Motivation and Involvement

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Andrea Chlpeková

2014-12-01

indicators into the motivation system. The question to be answered is how to effectively use the intellectual capital of problem-solving teams and increase employees’ satisfaction in the broader context of the improvement of the effectiveness of problem-solving methodology.

Origin of constraints in relativistic classical Hamiltonian dynamics

International Nuclear Information System (INIS)

Mallik, S.; Hugentobler, E.

1979-01-01

We investigate the null-plane or the front form of relativistic classical Hamiltonian dynamics as proposed by Dirac and developed by Leutwyler and Stern. For systems of two spinless particles we show that the algebra of Poincare generators is equivalent to describing dynamics in terms of two covariant constraint equations, the Poisson bracket of the two constraints being weakly zero. The latter condition is solved for certain simple forms of constraints

Simon on Problem-Solving

DEFF Research Database (Denmark)

Foss, Kirsten; Foss, Nicolai Juul

as a general approach to problem solving. We apply these Simonian ideas to organizational issues, specifically new organizational forms. Specifically, Simonian ideas allow us to develop a morphology of new organizational forms and to point to some design problems that characterize these forms.Keywords: Herbert...... Simon, problem-solving, new organizational forms. JEL Code: D23, D83......Two of Herbert Simon's best-known papers are "The Architecture of Complexity" and "The Structure of Ill-Structured Problems." We discuss the neglected links between these two papers, highlighting the role of decomposition in the context of problems on which constraints have been imposed...

Alternative Constraint Handling Technique for Four-Bar Linkage Path Generation

Science.gov (United States)

Sleesongsom, S.; Bureerat, S.

2018-03-01

This paper proposes an extension of a new concept for path generation from our previous work by adding a new constraint handling technique. The propose technique was initially designed for problems without prescribed timing by avoiding the timing constraint, while remain constraints are solving with a new constraint handling technique. The technique is one kind of penalty technique. The comparative study is optimisation of path generation problems are solved using self-adaptive population size teaching-learning based optimization (SAP-TLBO) and original TLBO. In this study, two traditional path generation test problem are used to test the proposed technique. The results show that the new technique can be applied with the path generation problem without prescribed timing and gives better results than the previous technique. Furthermore, SAP-TLBO outperforms the original one.

Lot Sizing Based on Stochastic Demand and Service Level Constraint

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hajar shirneshan

2012-06-01

Full Text Available Considering its application, stochastic lot sizing is a significant subject in production planning. Also the concept of service level is more applicable than shortage cost from managers' viewpoint. In this paper, the stochastic multi period multi item capacitated lot sizing problem has been investigated considering service level constraint. First, the single item model has been developed considering service level and with no capacity constraint and then, it has been solved using dynamic programming algorithm and the optimal solution has been derived. Then the model has been generalized to multi item problem with capacity constraint. The stochastic multi period multi item capacitated lot sizing problem is NP-Hard, hence the model could not be solved by exact optimization approaches. Therefore, simulated annealing method has been applied for solving the problem. Finally, in order to evaluate the efficiency of the model, low level criterion has been used .

Approximate Compilation of Constraints into Multivalued Decision Diagrams

DEFF Research Database (Denmark)

Hadzic, Tarik; Hooker, John N.; O’Sullivan, Barry

2008-01-01

We present an incremental refinement algorithm for approximate compilation of constraint satisfaction models into multivalued decision diagrams (MDDs). The algorithm uses a vertex splitting operation that relies on the detection of equivalent paths in the MDD. Although the algorithm is quite gene...

A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles

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Ricardo Soto

2015-01-01

Full Text Available The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling a n2 × n2 grid, composed of n columns, n rows, and n subgrids, each one containing distinct integers from 1 to n2. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with the alldifferent global constraint from the constraint programming world. The alldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.

Parallel Execution of Multi Set Constraint Rewrite Rules

DEFF Research Database (Denmark)

Sulzmann, Martin; Lam, Edmund Soon Lee

2008-01-01

that the underlying constraint rewrite implementation executes rewrite steps in parallel on increasingly popular becoming multi-core architectures. We design and implement efficient algorithms which allow for the parallel execution of multi-set constraint rewrite rules. Our experiments show that we obtain some......Multi-set constraint rewriting allows for a highly parallel computational model and has been used in a multitude of application domains such as constraint solving, agent specification etc. Rewriting steps can be applied simultaneously as long as they do not interfere with each other.We wish...

Constraints and Logic Programming in Grammars and Language Analysis

DEFF Research Database (Denmark)

Christiansen, Henning

2014-01-01

Constraints are an important notion in grammars and language analysis, and constraint programming techniques have been developed concurrently for solving a variety of complex problems. In this chapter we consider the synthesis of these branches into practical and effective methods for language...... methods that combine constraints with logic grammars such as Definite Clause Grammars and CHR Grammars, and show also a direct relationship to abductive reasoning....

Solving multiconstraint assignment problems using learning automata.

Science.gov (United States)

Horn, Geir; Oommen, B John

2010-02-01

This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the

The use of questions as problem-solving strategies during early childhood.

Science.gov (United States)

Legare, Cristine H; Mills, Candice M; Souza, André L; Plummer, Leigh E; Yasskin, Rebecca

2013-01-01

This study examined the strategic use of questions to solve problems across early childhood. Participants (N=54, 4-, 5-, and 6-year-olds) engaged in two tasks: a novel problem-solving question task that required asking questions to an informant to determine which card in an array was located in a box and a cognitive flexibility task that required classifying stimuli by multiple dimensions. The results from the question task indicated that there were age differences in the types of questions asked, with 6-year-olds asking more constraint-seeking questions than 4- and 5-year-olds. The number of constraint-seeking questions asked was the only significant predictor of accuracy. Performance on the cognitive flexibility task correlated with both constraint-seeking strategy use and accuracy in the question task. In sum, our results provide evidence that the capacity to use questions to generate relevant information develops before the capacity to apply this information successfully and consistently to solve complex problems. We propose that the process of using questions as strategic tools is an ideal context for examining how children come to gain active and intentional control over problem solving. Copyright © 2012 Elsevier Inc. All rights reserved.

Solving of L0 norm constrained EEG inverse problem.

Science.gov (United States)

Xu, Peng; Lei, Xu; Hu, Xiao; Yao, Dezhong

2009-01-01

l(0) norm is an effective constraint used to solve EEG inverse problem for a sparse solution. However, due to the discontinuous and un-differentiable properties, it is an open issue to solve the l(0) norm constrained problem, which is usually instead solved by using some alternative functions like l(1) norm to approximate l(0) norm. In this paper, a continuous and differentiable function having the same form as the transfer function of Butterworth low-pass filter is introduced to approximate l(0) norm constraint involved in EEG inverse problem. The new approximation based approach was compared with l(1) norm and LORETA solutions on a realistic head model using simulated sources. The preliminary results show that this alternative approximation to l(0) norm is promising for the estimation of EEG sources with sparse distribution.

Hybrid particle swarm optimization with Cauchy distribution for solving reentrant flexible flow shop with blocking constraint

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Chatnugrob Sangsawang

2016-06-01

Full Text Available This paper addresses a problem of the two-stage flexible flow shop with reentrant and blocking constraints in Hard Disk Drive Manufacturing. This problem can be formulated as a deterministic FFS|stage=2,rcrc, block|Cmax problem. In this study, adaptive Hybrid Particle Swarm Optimization with Cauchy distribution (HPSO was developed to solve the problem. The objective of this research is to find the sequences in order to minimize the makespan. To show their performances, computational experiments were performed on a number of test problems and the results are reported. Experimental results show that the proposed algorithms give better solutions than the classical Particle Swarm Optimization (PSO for all test problems. Additionally, the relative improvement (RI of the makespan solutions obtained by the proposed algorithms with respect to those of the current practice is performed in order to measure the quality of the makespan solutions generated by the proposed algorithms. The RI results show that the HPSO algorithm can improve the makespan solution by averages of 14.78%.

RESEARCH ON HUMAN RESOURCES MOTIVATION AND SATISFACTION

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Zoltan-Bela FARKAS

2014-06-01

Full Text Available Many research studies on the human resources performance of the educational system have proved that pupils/students’ educational success depends, to a high degree, on the level of human resource motivation, as well as on their degree of professional satisfaction. Teachers’ who show a high level of motivation, both intrinsic and extrinsic, invest more into their activity, are more creative and more efficient in problem solving. The paper debates the results of an empirical study regarding the influence of pre-university teachers’ motivation and satisfaction regarding the general work conditions on their work performance by measuring the present motivation and satisfaction level. Furthermore, the determinant factors of their satisfaction with the work place are determined and analyzed. Finally, based on the statistical data process we will conclude and debate on the research hypothesis validation and the empirical model related to motivation – satisfaction – performance interdependences.

Cognitive constraints on high school students' representations of real environmental problems

Science.gov (United States)

Barnes, Ervin Kenneth

One class of juniors and seniors was studied through one semester in the investigation of how students think about, learn from, and solve real environmental problems. The intention was to listen to student voices while researching the features of their representations of these problems, the beliefs they held (tenets), the cognitive processes they employed, and the principles of science, ecology, problem solving, and ethics they held as tenets. The focus was upon two self-selected groups as they perceived, engaged, analyzed, and proposed solutions for problems. Analysis of the student representations involved interpretation of the features to include both the perspective tenets and the envisioning processes. These processes included the intentive and attentive constraints as tenet acquisition and volitive and agential constraints as tenet affirmation. The perspective tenets included a variety of conceptual (basic science, ecological, ethical, and problem-solving) constraints as well as ontological, epistemological, and other cultural (role, status, power, and community) constraints. The perspective tenets were interpreted thematically including the ways populations of people cause and care about environmental problems, the magnitude of environmental problems and the science involved, the expectations and limitations students perceive for themselves, and the importance of community awareness and cooperation to addressing these problems. Some of these tenets were interpreted to be principles in that they were rules that were accepted by some people as true. The perspective tenets, along with the envisioning processes, were perceived to be the constraints that determined the environmental problems and limited the solution possibilities. The students thought about environmental problems in mature and principled ways using a repertoire of cognitive processes. They learned from them as they acquired and affirmed tenets. They solved them through personal choices and

Affect and mathematical problem solving a new perspective

CERN Document Server

Adams, Verna

1989-01-01

Research on cognitive aspects of mathematical problem solving has made great progress in recent years, but the relationship of affective factors to problem-solving performance has been a neglected research area. The purpose of Affect and Mathematical Problem Solving: A New Perspective is to show how the theories and methods of cognitive science can be extended to include the role of affect in mathematical problem solving. The book presents Mandler's theory of emotion and explores its implications for the learning and teaching of mathematical problem solving. Also, leading researchers from mathematics, education, and psychology report how they have integrated affect into their own cognitive research. The studies focus on metacognitive processes, aesthetic influences on expert problem solvers, teacher decision-making, technology and teaching problem solving, and beliefs about mathematics. The results suggest how emotional factors like anxiety, frustration, joy, and satisfaction can help or hinder performance in...

Constraint Embedding Technique for Multibody System Dynamics

Science.gov (United States)

Woo, Simon S.; Cheng, Michael K.

2011-01-01

Multibody dynamics play a critical role in simulation testbeds for space missions. There has been a considerable interest in the development of efficient computational algorithms for solving the dynamics of multibody systems. Mass matrix factorization and inversion techniques and the O(N) class of forward dynamics algorithms developed using a spatial operator algebra stand out as important breakthrough on this front. Techniques such as these provide the efficient algorithms and methods for the application and implementation of such multibody dynamics models. However, these methods are limited only to tree-topology multibody systems. Closed-chain topology systems require different techniques that are not as efficient or as broad as those for tree-topology systems. The closed-chain forward dynamics approach consists of treating the closed-chain topology as a tree-topology system subject to additional closure constraints. The resulting forward dynamics solution consists of: (a) ignoring the closure constraints and using the O(N) algorithm to solve for the free unconstrained accelerations for the system; (b) using the tree-topology solution to compute a correction force to enforce the closure constraints; and (c) correcting the unconstrained accelerations with correction accelerations resulting from the correction forces. This constraint-embedding technique shows how to use direct embedding to eliminate local closure-loops in the system and effectively convert the system back to a tree-topology system. At this point, standard tree-topology techniques can be brought to bear on the problem. The approach uses a spatial operator algebra approach to formulating the equations of motion. The operators are block-partitioned around the local body subgroups to convert them into aggregate bodies. Mass matrix operator factorization and inversion techniques are applied to the reformulated tree-topology system. Thus in essence, the new technique allows conversion of a system with

A constraint-based bottom-up counterpart to definite clause grammars

DEFF Research Database (Denmark)

Christiansen, Henning

2004-01-01

A new grammar formalism, CHR Grammars (CHRG), is proposed that provides a constraint-solving approach to language analysis, built on top of the programming language of Constraint Handling Rules in the same way as Definite Clause Grammars (DCG) on Prolog. CHRG works bottom-up and adds the following......, integrity constraints, operators a la assumption grammars, and to incorporate other constraint solvers. (iv)~Context-sensitive rules that apply for disambiguation, coordination in natural language and tagger-like rules....

Performance and job satisfaction of employees as well as customers satisfaction affect by organizational environment – An applied study on Gumhouria bank, Libya

Directory of Open Access Journals (Sweden)

Mohieddin Almanae

2013-01-01

Full Text Available This study conducted on Gumhouria Bank and dealing with the role played by the organizational environment on performance and functional satisfaction of the employees. The relevant effect on the customer’s satisfaction indicate that the various elements of the organizational environment have effect on the functional performance and satisfaction of the customers. For raising performance and achieving satisfaction of the employees and customers, elements should be taken into consideration and improvement thereof and solving the problems encountering them. The relationship between the organizational environment and the functional performance is progressive and positive. Whenever the organizational environment increases, the functional performance increases, which, in turn, affects the functional satisfaction degree with the employees. The results indicated effect of the organizational environment on the customer’s satisfaction with the banking services provided. This may be resulting from the effect of organizational environment on the job performance and satisfaction (positive or negative which, in turn led to achieving satisfaction or dissatisfaction of the customers.

Solving discretely-constrained MPEC problems with applications in electric power markets

International Nuclear Information System (INIS)

Gabriel, Steven A.; Leuthold, Florian U.

2010-01-01

Many of the European energy markets are characterized by dominant players that own a large share of their respective countries' generation capacities. In addition to that, there is a significant lack of cross-border transmission capacity. Combining both facts justifies the assumption that these dominant players are able to influence the market outcome of an internal European energy market due to strategic behavior. In this paper, we present a mathematical formulation in order to solve a Stackelberg game for a network-constrained energy market using integer programming. The strategic player is the Stackelberg leader and the independent system operator (including the decisions of the competitive fringe firms) acts as follower. We assume that there is one strategic player which results in a mathematical program with equilibrium constraints (MPEC). This MPEC is reformulated as mixed-integer linear program (MILP) by using disjunctive constraints and linearization. The MILP formulation gives the opportunity to solve the problems reliably and paves the way to add discrete constraints to the original MPEC formulation which can be used in order to solve discretely-constrained mathematical programs with equilibrium constraints (DC-MPECs). We report computational results for a small illustrative network as well as a stylized Western European grid with realistic data. (author)

Solving discretely-constrained MPEC problems with applications in electric power markets

Energy Technology Data Exchange (ETDEWEB)

Gabriel, Steven A. [1143 Glenn L. Martin Hall, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742-3021 (United States); Leuthold, Florian U. [Chair of Energy Economics and Public Sector Management, Dresden University of Technology, 01069 Dresden (Germany)

2010-01-15

Many of the European energy markets are characterized by dominant players that own a large share of their respective countries' generation capacities. In addition to that, there is a significant lack of cross-border transmission capacity. Combining both facts justifies the assumption that these dominant players are able to influence the market outcome of an internal European energy market due to strategic behavior. In this paper, we present a mathematical formulation in order to solve a Stackelberg game for a network-constrained energy market using integer programming. The strategic player is the Stackelberg leader and the independent system operator (including the decisions of the competitive fringe firms) acts as follower. We assume that there is one strategic player which results in a mathematical program with equilibrium constraints (MPEC). This MPEC is reformulated as mixed-integer linear program (MILP) by using disjunctive constraints and linearization. The MILP formulation gives the opportunity to solve the problems reliably and paves the way to add discrete constraints to the original MPEC formulation which can be used in order to solve discretely-constrained mathematical programs with equilibrium constraints (DC-MPECs). We report computational results for a small illustrative network as well as a stylized Western European grid with realistic data. (author)

Self-Evaluation Processes in Life Satisfaction: Uncovering Measurement Non-Equivalence and Age-Related Differences

Science.gov (United States)

Heidemeier, Heike; Staudinger, Ursula M.

2012-01-01

This study demonstrates how self-evaluation processes explain subgroup differences in ratings of life satisfaction (population heterogeneity). Life domains differ with regard to the constraints they impose on beliefs in internal control. We hypothesized that these differences are linked with cognitive biases in ratings of life satisfaction. In…

Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets

KAUST Repository

Lenzen, F.; Lellmann, J.; Becker, F.; Schnö rr, C.

2014-01-01

© 2014 Society for Industrial and Applied Mathematics. We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied

Solving a bi-objective vehicle routing problem under uncertainty by a revised multi-choice goal programming approach

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.

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.

The algebraic-hyperbolic approach to the linearized gravitational constraints on a Minkowski background

International Nuclear Information System (INIS)

Winicour, Jeffrey

2017-01-01

An algebraic-hyperbolic method for solving the Hamiltonian and momentum constraints has recently been shown to be well posed for general nonlinear perturbations of the initial data for a Schwarzschild black hole. This is a new approach to solving the constraints of Einstein’s equations which does not involve elliptic equations and has potential importance for the construction of binary black hole data. In order to shed light on the underpinnings of this approach, we consider its application to obtain solutions of the constraints for linearized perturbations of Minkowski space. In that case, we find the surprising result that there are no suitable Cauchy hypersurfaces in Minkowski space for which the linearized algebraic-hyperbolic constraint problem is well posed. (note)

Community Collaborative Problem Solving--Cross-Cultural Lessons.

Science.gov (United States)

Stevens, Georgia L.; Marin-Hernandez, Agueda

1999-01-01

Examples of Midwestern and Honduran community-based collaborative problem solving provide cross-culturally-adaptable suggestions for community coalitions: adapt the process to the culture, recognize structural constraints, understand reciprocity norms, appreciate the validity of avoidance, and remember that communication roadblocks are always…

Testing the master constraint programme for loop quantum gravity: V. Interacting field theories

International Nuclear Information System (INIS)

Dittrich, B; Thiemann, T

2006-01-01

This is the fifth and final paper in our series of five in which we test the master constraint programme for solving the Hamiltonian constraint in loop quantum gravity. Here we consider interacting quantum field theories, specifically we consider the non-Abelian Gauss constraints of Einstein-Yang-Mills theory and 2 + 1 gravity. Interestingly, while Yang-Mills theory in 4D is not yet rigorously defined as an ordinary (Wightman) quantum field theory on Minkowski space, in background-independent quantum field theories such as loop quantum gravity (LQG) this might become possible by working in a new, background-independent representation. While for the Gauss constraint the master constraint can be solved explicitly, for the 2 + 1 theory we are only able to rigorously define the master constraint operator. We show that the, by other methods known, physical Hilbert is contained in the kernel of the master constraint, however, to systematically derive it by only using spectral methods is as complicated as for 3 + 1 gravity and we therefore leave the complete analysis for 3 + 1 gravity

A Production Planning Model for Make-to-Order Foundry Flow Shop with Capacity Constraint

Directory of Open Access Journals (Sweden)

Xixing Li

2017-01-01

Full Text Available The mode of production in the modern manufacturing enterprise mainly prefers to MTO (Make-to-Order; how to reasonably arrange the production plan has become a very common and urgent problem for enterprises’ managers to improve inner production reformation in the competitive market environment. In this paper, a mathematical model of production planning is proposed to maximize the profit with capacity constraint. Four kinds of cost factors (material cost, process cost, delay cost, and facility occupy cost are considered in the proposed model. Different factors not only result in different profit but also result in different satisfaction degrees of customers. Particularly, the delay cost and facility occupy cost cannot reach the minimum at the same time; the two objectives are interactional. This paper presents a mathematical model based on the actual production process of a foundry flow shop. An improved genetic algorithm (IGA is proposed to solve the biobjective problem of the model. Also, the gene encoding and decoding, the definition of fitness function, and genetic operators have been illustrated. In addition, the proposed algorithm is used to solve the production planning problem of a foundry flow shop in a casting enterprise. And comparisons with other recently published algorithms show the efficiency and effectiveness of the proposed algorithm.

The effects of stating problems in bilingual students' first and second languages on solving mathematical word problems.

Science.gov (United States)

Bernardo, Allan B I; Calleja, Marissa O

2005-03-01

Researchers have suggested that among bilinguals, solving word problems in mathematics is influenced by linguistic factors (K. Durkin & B. Shire, 1991; L. Verschaffel, B. Greer, & E. De Corte, 2000). Others have suggested that students exhibit a strong tendency to exclude real-world constraints in solving mathematics word problems (L. Verschaffel, E. De Corte, & S. Lasure, 1994). In the present study, the authors explored the effects of stating word problems in either Filipino or English on how Filipino-English bilingual students solved word problems in which the solution required the application of real-world knowledge. The authors asked bilingual students to solve word problems in either their first or second language. For some of the word problems, real-life constraints prevented straightforward application of mathematical procedures. The authors analyzed the students' solutions to determine whether the language of the word problems affected the tendency to apply real-life constraints in the solution. Results showed that the bilingual students (a) rarely considered real-life constraints in their solutions, (b) were more successful in understanding and solving word problems that were stated in their first language, and (c) were more likely to experience failure in finding a solution to problems stated in their second language. The results are discussed in terms of the relationship between linguistic and mathematical problem-solving processes among bilinguals.

An Approach for Solving Linear Fractional Programming Problems

OpenAIRE

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...

Maintaining Arc Consistency in Non-Binary Dynamic CSPs using Simple Tabular Reduction

DEFF Research Database (Denmark)

Queva, Matthieu Stéphane Benoit; Probst, Christian W.; Ricci, Laurent

2010-01-01

Constraint Satisfaction Problems (CSPs) are well known models used in Artificial Intelligence. In order to represent real world systems, CSPs have been extended to Dynamic CSPs (DCSPs), which support adding and removing constraints at runtime. Some approaches to the NP-complete problem of solving...

Conflict Resolution in Chinese Adolescents' Friendship: Links with Regulatory Focus and Friendship Satisfaction.

Science.gov (United States)

Gao, Qin; Bian, Ran; Liu, Ru-de; He, Yili; Oei, Tian-Po

2017-04-03

It is generally acknowledged that people adopt different resolution strategies when facing conflicts with others. However, the mechanisms of conflict resolution are still unclear and under researched, in particular within the context of Chinese adolescents' same-sex friendship relations. Thus, the present study investigated the mediator role of conflict resolution strategies in the relationship between regulatory foci and friendship satisfaction for the first time. 653 Chinese adolescents completed the regulatory foci, conflict resolution style, and friendship satisfaction measures. The results of the structure equation modeling showed that while promotion focus was positively associated with problem-solving and compliance, prevention focus was positively associated with withdrawal and conflict engagement. In addition, problem-solving mediated the relationship between promotion focus and friendship satisfaction, and conflict engagement mediated the relationship between prevention focus and friendship satisfaction. These findings contribute to understanding Chinese adolescents' use of conflict resolution strategies as well as the relationship between regulatory foci and behavioral strategies in negative situations.

Hyundai’s Customer Satisfaction Analysis in Azerbaijan Market

Directory of Open Access Journals (Sweden)

Khayala Babayeva

2016-12-01

Full Text Available In modern economies, level of customer satisfaction is main indicator which intends to show organization’s position in comparison with its competitors. Determining customer satisfaction level allows any organization to detect the problems and gives a way in order to solve such issues. In this article, the aim is to measure the satisfaction level of Hyundai customers in Azerbaijan and for that a survey has been conducted. The research has been implemented on two basis: customer Satisfaction of Hyundai clients on a the car they drive; and b the service they have paid for repairing their car in the service center. Authors have developed confidence interval and hypothesis testing for each outcome from the survey. In addition to these, NPS level of Hyundai has been computed. Those figures help the authors to measure the real population’s satisfaction level. The results of the analysis claim that ultimate amount of customers are dissatisfied with car’s quality. Furthermore most of drivers’ satisfaction level of services which Hyundai provides is satisfactory.

Application of constraint satisfaction algorithms for conditioning and packing activated control rod assemblies in MOSAIK"R-casks. Application of constraint satisfaction algorithms for conditioning and packaging 160 control rod assemblies

International Nuclear Information System (INIS)

Harding, P.J.

2017-01-01

In the wake of the decommissioning of numerous nuclear power plants in Germany, techniques to reduce the number of costly waste casks or containers are sought after. The large bandwidth of limits (dose rate, mass, individual nuclide activities, chemical composition...) the waste packages have to comply with for both interim storage facilities and the repository Konrad render the manual planning of packaging concepts prohibitive. However, in the past, the planning for packaging has been performed in this way, albeit on the basis of several facilitating assumptions. Surprisingly, to the best of our knowledge, the automated computer-assisted generation of packaging plans for radioactive waste has not been demonstrated previously. In this talk we demonstrate how the conditioning and packing of 160 control rod assemblies was optimised using constraint satisfaction algorithms. These algorithms can be executed by a computer in a few minutes, thus considerably accelerating the generation of packaging plans, while optimising the utilisation of the waste casks and containers with respect to mass, activity, dose rate, etc. This automated and computer-assisted procedure took into account complex logistical boundary conditions present during decommissioning, such as space requirements, the sequence of the waste and the (lack of) availability of suitable waste casks. In addition, packaging concepts based on several scenarios (cask availability, space requirements,...) were easily and automatically generated once the packaging rules had been coded. We demonstrate the successful application of these algorithms to a real packaging campaign of control rod assemblies of a boiling water reactor, for which excellent results were achieved. We also present an outlook of a much larger scale project, in which the logistics and storage of radioactive waste packages is mathematically optimised. Finally, we give prospects on these techniques to others, similar logistical problems currently

Job satisfaction as a matter of time, team, and trust

DEFF Research Database (Denmark)

Uhrenfeldt, Lisbeth; Hall, Elisabeth

2015-01-01

Support and variety regarding work, autonomy, organizational constraints, and promotion opportunities are factors contributing to job satisfaction or lack thereof among hospital nurses together with self-perceived health, education and career orientation. The aim of this study was to explore public...... hospital nurses’ experiences of job satisfaction. This qualitative study was undertaken in a caring theory context. Ten proficient Danish hospital nurses were interviewed twice and data were analysed using a hermeneutic approach. The analysis revealed that time, team, and trust were essential components...... in job satisfaction. Time, team and trust helped the nurses collaborate with patients, care for relatives, and work in teams with other hospital staff members. Lack of job satisfaction occurred when time was to short or quality care was threatened, when the nurses felt alone and had to finish their job...

Level-Set Topology Optimization with Aeroelastic Constraints

Science.gov (United States)

Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia

2015-01-01

Level-set topology optimization is used to design a wing considering skin buckling under static aeroelastic trim loading, as well as dynamic aeroelastic stability (flutter). The level-set function is defined over the entire 3D volume of a transport aircraft wing box. Therefore, the approach is not limited by any predefined structure and can explore novel configurations. The Sequential Linear Programming (SLP) level-set method is used to solve the constrained optimization problems. The proposed method is demonstrated using three problems with mass, linear buckling and flutter objective and/or constraints. A constraint aggregation method is used to handle multiple buckling constraints in the wing skins. A continuous flutter constraint formulation is used to handle difficulties arising from discontinuities in the design space caused by a switching of the critical flutter mode.

Two-agent scheduling in open shops subject to machine availability and eligibility constraints

Directory of Open Access Journals (Sweden)

Ling-Huey Su

2015-09-01

Full Text Available Purpose: The aims of this article are to develop a new mathematical formulation and a new heuristic for the problem of preemptive two-agent scheduling in open shops subject to machine maintenance and eligibility constraints. Design/methodology: Using the ideas of minimum cost flow network and constraint programming, a heuristic and a network based linear programming are proposed to solve the problem. Findings: Computational experiments show that the heuristic generates a good quality schedule with a deviation of 0.25% on average from the optimum and the network based linear programming model can solve problems up to 110 jobs combined with 10 machines without considering the constraint that each operation can be processed on at most one machine at a time. In order to satisfy this constraint, a time consuming Constraint Programming is proposed. For n = 80 and m = 10, the average execution time for the combined models (linear programming model combined with Constraint programming exceeds two hours. Therefore, the heuristic algorithm we developed is very efficient and is in need. Practical implications: Its practical implication occurs in TFT-LCD and E-paper manufacturing wherein units go through a series of diagnostic tests that do not have to be performed in any specified order. Originality/value: The main contribution of the article is to split the time horizon into many time intervals and use the dispatching rule for each time interval in the heuristic algorithm, and also to combine the minimum cost flow network with the Constraint Programming to solve the problem optimally. 

University Course Timetabling using Constraint Programming

Directory of Open Access Journals (Sweden)

Hadi Shahmoradi

2017-03-01

Full Text Available University course timetabling problem is a challenging and time-consuming task on the overall structure of timetable in every academic environment. The problem deals with many factors such as the number of lessons, classes, teachers, students and working time, and these are influenced by some hard and soft constraints. The aim of solving this problem is to assign courses and classes to teachers and students, so that the restrictions are held. In this paper, a constraint programming method is proposed to satisfy maximum constraints and expectation, in order to address university timetabling problem. For minimizing the penalty of soft constraints, a cost function is introduced and AHP method is used for calculating its coefficients. The proposed model is tested on department of management, University of Isfahan dataset using OPL on the IBM ILOG CPLEX Optimization Studio platform. A statistical analysis has been conducted and shows the performance of the proposed approach in satisfying all hard constraints and also the satisfying degree of the soft constraints is on maximum desirable level. The running time of the model is less than 20 minutes that is significantly better than the non-automated ones.

An efficient method for minimizing a convex separable logarithmic function subject to a convex inequality constraint or linear equality constraint

Directory of Open Access Journals (Sweden)

2006-01-01

Full Text Available We consider the problem of minimizing a convex separable logarithmic function over a region defined by a convex inequality constraint or linear equality constraint, and two-sided bounds on the variables (box constraints. Such problems are interesting from both theoretical and practical point of view because they arise in some mathematical programming problems as well as in various practical problems such as problems of production planning and scheduling, allocation of resources, decision making, facility location problems, and so forth. Polynomial algorithms are proposed for solving problems of this form and their convergence is proved. Some examples and results of numerical experiments are also presented.

Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem

Science.gov (United States)

Korayem, L.; Khorsid, M.; Kassem, S. S.

2015-05-01

The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.

Route constraints model based on polychromatic sets

Science.gov (United States)

Yin, Xianjun; Cai, Chao; Wang, Houjun; Li, Dongwu

2018-03-01

With the development of unmanned aerial vehicle (UAV) technology, the fields of its application are constantly expanding. The mission planning of UAV is especially important, and the planning result directly influences whether the UAV can accomplish the task. In order to make the results of mission planning for unmanned aerial vehicle more realistic, it is necessary to consider not only the physical properties of the aircraft, but also the constraints among the various equipment on the UAV. However, constraints among the equipment of UAV are complex, and the equipment has strong diversity and variability, which makes these constraints difficult to be described. In order to solve the above problem, this paper, referring to the polychromatic sets theory used in the advanced manufacturing field to describe complex systems, presents a mission constraint model of UAV based on polychromatic sets.

Low-cost design of next generation SONET/SDH networks with multiple constraints

CSIR Research Space (South Africa)

Karem, TR

2007-07-01

Full Text Available on constraints programming satisfaction technology is proposed. The algorithm is tested in OPNET simulation environment using different network models derived from a hypothetical case study of an optical network design for Bellville area in Cape Town, South...

Multi-area economic dispatch with tie-line constraints employing ...

African Journals Online (AJOL)

user

The economic dispatch problem is frequently solved without considering ... programming algorithm was proposed for the MAED solution with tie-line constraints ..... are the difference between two randomly chosen parameter vectors, a concept.

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.

On the constraints violation in forward dynamics of multibody systems

Energy Technology Data Exchange (ETDEWEB)

Marques, Filipe [University of Minho, Department of Mechanical Engineering (Portugal); Souto, António P. [University of Minho, Department of Textile Engineering (Portugal); Flores, Paulo, E-mail: pflores@dem.uminho.pt [University of Minho, Department of Mechanical Engineering (Portugal)

2017-04-15

It is known that the dynamic equations of motion for constrained mechanical multibody systems are frequently formulated using the Newton–Euler’s approach, which is augmented with the acceleration constraint equations. This formulation results in the establishment of a mixed set of partial differential and algebraic equations, which are solved in order to predict the dynamic behavior of general multibody systems. The classical solution of the equations of motion is highly prone to constraints violation because the position and velocity constraint equations are not fulfilled. In this work, a general and comprehensive methodology to eliminate the constraints violation at the position and velocity levels is offered. The basic idea of the described approach is to add corrective terms to the position and velocity vectors with the intent to satisfy the corresponding kinematic constraint equations. These corrective terms are evaluated as a function of the Moore–Penrose generalized inverse of the Jacobian matrix and of the kinematic constraint equations. The described methodology is embedded in the standard method to solve the equations of motion based on the technique of Lagrange multipliers. Finally, the effectiveness of the described methodology is demonstrated through the dynamic modeling and simulation of different planar and spatial multibody systems. The outcomes in terms of constraints violation at the position and velocity levels, conservation of the total energy and computational efficiency are analyzed and compared with those obtained with the standard Lagrange multipliers method, the Baumgarte stabilization method, the augmented Lagrangian formulation, the index-1 augmented Lagrangian, and the coordinate partitioning method.

Work Hours Constraints: Impacts and Policy Implications

OpenAIRE

Constant, Amelie F.; Otterbach, Steffen

2011-01-01

If individuals reveal their preference as consumers, then they are taken seriously. What happens if individuals, as employees, reveal their preferences in working hours? And what happens if there is a misalignment between actual hours worked and preferred hours, the so-called work hours constraints? How does this affect the productivity of workers, their health, and overall life satisfaction? Labor supply and corresponding demand are fundamental to production. Labor economists know for long t...

On solving distributed CS(O)Ps with privacy

OpenAIRE

Silaghi, Marius Calin

2002-01-01

Cryptographic protocols can enforce privacy in distributed computation of functions [Goldwasser'96] and are a competitor of the distributed constructive search techniques. [Goldreich'87,Chaum'87,Chaum'88,Ben-or'88] show how cryptographic protocols can be compiled from protocols/functions for honest agents. For some combinations of concepts of security and types of attacks, cryptographic protocols obtained this way can be safe. We discuss their application to constraint satisfaction (and optim...

Comparison of passive and active leisure activities and life satisfaction with aging.

Science.gov (United States)

Cho, Dongwook; Post, Jay; Kim, Sung Kyeom

2018-03-01

Many older adults face limitations to participating in active leisure activities as a result of their physical constraints from aging. Passive leisure activities become alternative leisure activities for older adults as a result of limited physical capacity. The present study sought to determine whether there exists a difference in the frequency of participation in passive and active leisure activities, and the effect of participation in passive and active leisure activities on the life satisfaction level of old adults. A total of 460 participants aged 60-95 years were randomly selected from 21 sites in the USA. The Life Satisfaction Index - Z and the Meaningful Activity Participation Assessment were analyzed to examine older adults' life satisfaction and frequency of active or passive activities. The results showed that participation in passive leisure activities, such reading, talking on the telephone and watching TV/listening to the radio, is more frequent among older adults (P = 0.000). The regression coefficient found that club/organization or volunteering (P = 0.008), homemaking/maintenance (P = 0.017) and traveling (P = 0.017) for active leisure activities were statistically significant predictors of Life Satisfaction Index - Z for older adults. The current study shows that older adults spent much more times participating in passive leisure activities, such as radio/watching TV, talking on the phone and reading. The result also showed that active leisure activities, such as club/organization or volunteering, home making/maintenance and traveling, were significant predictors of life satisfaction for older adults controlling for covariates. The current study suggests marketing and programming plans to overcome the constraints that influence older adults' life satisfaction. Geriatr Gerontol Int 2018; 18: 380-386. © 2017 Japan Geriatrics Society.

Navigating contextual constraints in discourse: Design explications in institutional talk

Science.gov (United States)

Herijgers, MLC (Marloes); Maat, HLW (Henk) Pander

2017-01-01

Although institutional discourse is subject to a vast ensemble of constraints, its design is not fixed beforehand. On the contrary, optimizing the satisfaction of these constraints requires considerable discourse design skills from institutional agents. In this article, we analyze how Dutch banks’ mortgage advisors navigate their way through the consultations context. We focus on what we call discourse design explications, that is, stretches of talk in which participants refer to conflicting constraints in the discourse context, at the same time proposing particular discourse designs for dealing with these conflicts. We start by discussing three forms of design explication. Then we will examine the various resolutions they propose for constraint conflicts and show how advisors seek customer consent or cooperation for the proposed designs. Thus our analysis reveals how institutional agents, while providing services, work on demonstrating how the design of these services is optimized and tailored to customers. PMID:28781580

Simon on problem solving

DEFF Research Database (Denmark)

Foss, Kirsten; Foss, Nicolai Juul

2006-01-01

as a general approach to problem solving. We apply these Simonian ideas to organisational issues, specifically new organisational forms. Specifically, Simonian ideas allow us to develop a morphology of new organisational forms and to point to some design problems that characterise these forms.......Two of Herbert Simon's best-known papers are 'The Architecture of Complexity' and 'The Structure of Ill-Structured Problems.' We discuss the neglected links between these two papers, highlighting the role of decomposition in the context of problems on which constraints have been imposed...

A constraint-based approach to intelligent support of nuclear reactor design

International Nuclear Information System (INIS)

Furuta, Kazuo

1993-01-01

Constraint is a powerful representation to formulate and solve problems in design; a constraint-based approach to intelligent support of nuclear reactor design is proposed. We first discuss the features of the approach, and then present the architecture of a nuclear reactor design support system under development. In this design support system, the knowledge base contains constraints useful to structure the design space as object class definitions, and several types of constraint resolvers are provided as design support subsystems. The adopted method of constraint resolution are explained in detail. The usefulness of the approach is demonstrated using two design problems: Design window search and multiobjective optimization in nuclear reactor design. (orig./HP)

A randomized trial of teen online problem solving: efficacy in improving caregiver outcomes after brain injury.

Science.gov (United States)

Wade, Shari L; Walz, Nicolay C; Carey, JoAnne; McMullen, Kendra M; Cass, Jennifer; Mark, Erin; Yeates, Keith Owen

2012-11-01

To examine the results of a randomized clinical trial (RCT) of Teen Online Problem Solving (TOPS), an online problem solving therapy model, in increasing problem-solving skills and decreasing depressive symptoms and global distress for caregivers of adolescents with traumatic brain injury (TBI). Families of adolescents aged 11-18 who sustained a moderate to severe TBI between 3 and 19 months earlier were recruited from hospital trauma registries. Participants were assigned to receive a web-based, problem-solving intervention (TOPS, n = 20), or access to online resources pertaining to TBI (Internet Resource Comparison; IRC; n = 21). Parent report of problem solving skills, depressive symptoms, global distress, utilization, and satisfaction were assessed pre- and posttreatment. Groups were compared on follow-up scores after controlling for pretreatment levels. Family income was examined as a potential moderator of treatment efficacy. Improvement in problem solving was examined as a mediator of reductions in depression and distress. Forty-one participants provided consent and completed baseline assessments, with follow-up assessments completed on 35 participants (16 TOPS and 19 IRC). Parents in both groups reported a high level of satisfaction with both interventions. Improvements in problem solving skills and depression were moderated by family income, with caregivers of lower income in TOPS reporting greater improvements. Increases in problem solving partially mediated reductions in global distress. Findings suggest that TOPS may be effective in improving problem solving skills and reducing depressive symptoms for certain subsets of caregivers in families of adolescents with TBI.

Top-k Based Adaptive Enumeration in Constraint Programming

Directory of Open Access Journals (Sweden)

Ricardo Soto

2015-01-01

order for variables and values is employed along the search. In this paper, we present a new and more lightweight approach for performing adaptive enumeration. We incorporate a powerful classification technique named Top-k in order to adaptively select strategies along the resolution. We report results on a set of well-known benchmarks where the proposed approach noticeably competes with classical and modern adaptive enumeration methods for constraint satisfaction.

Optimal satisfaction degree in energy harvesting cognitive radio networks

International Nuclear Information System (INIS)

Li Zan; Liu Bo-Yang; Si Jiang-Bo; Zhou Fu-Hui

2015-01-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. (paper)

Solving the Frequency Assignment Problem by Site Availability and Constraint Programming

OpenAIRE

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 ...

Occupational therapists' job satisfaction in a changing hospital organisation--a time-geography-based study.

Science.gov (United States)

Bendixen, Hans Jørgen; Ellegård, Kajsa

2014-01-01

To investigate occupational therapists' job satisfaction under a changing regime by using a time-geographic approach focusing on the therapists' everyday working lives. Nine occupational therapists at the Copenhagen University Hospital, Gentofte, Denmark. A mixed-method design was employed. Occupational therapists kept time-geographic diaries, and the results from them were grounded for individual, semi-structured in-depth interviews. Individual reflections on everyday working life were recorded. Transcribed statements from the interviews were analysed to determine factors influencing job satisfaction. The nine therapists kept diaries for one day a month for a total of 70 preselected days over a period of nine months; six participated in individual interviews. Four factors constraining OT job satisfaction were revealed. Economic concerns, new professional paradigms and methods in combination with a new organisational structure for the occupational therapy service caused uncertainty. In addition, decreasing possibilities for supervision by colleagues influenced job satisfaction. Opportunities for experiencing autonomy in everyday working life were described as facilitators for job satisfaction. The time-geographic and interview methods were useful in focusing on the job satisfaction of occupational therapists, who provided individual interpretations of the balance between autonomy and three types of constraints in everyday working life. The constraints related to organisation, power relations and - not least - how the organisational project of the department fitted in with OTs' individual projects. Matching of organisational and individual projects is of crucial importance, not only for OTs but for most workplaces where individuals are employed to serve patients in the healthcare sector.

A one-layer recurrent neural network for non-smooth convex optimization subject to linear inequality constraints

International Nuclear Information System (INIS)

Liu, Xiaolan; Zhou, Mi

2016-01-01

In this paper, a one-layer recurrent network is proposed for solving a non-smooth convex optimization subject to linear inequality constraints. Compared with the existing neural networks for optimization, the proposed neural network is capable of solving more general convex optimization with linear inequality constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds.

Teaching Database Design with Constraint-Based Tutors

Science.gov (United States)

Mitrovic, Antonija; Suraweera, Pramuditha

2016-01-01

Design tasks are difficult to teach, due to large, unstructured solution spaces, underspecified problems, non-existent problem solving algorithms and stopping criteria. In this paper, we comment on our approach to develop KERMIT, a constraint-based tutor that taught database design. In later work, we re-implemented KERMIT as EER-Tutor, and…

Fluence map optimization (FMO) with dose–volume constraints in IMRT using the geometric distance sorting method

International Nuclear Information System (INIS)

Lan Yihua; Li Cunhua; Ren Haozheng; Zhang Yong; Min Zhifang

2012-01-01

A new heuristic algorithm based on the so-called geometric distance sorting technique is proposed for solving the fluence map optimization with dose–volume constraints which is one of the most essential tasks for inverse planning in IMRT. The framework of the proposed method is basically an iterative process which begins with a simple linear constrained quadratic optimization model without considering any dose–volume constraints, and then the dose constraints for the voxels violating the dose–volume constraints are gradually added into the quadratic optimization model step by step until all the dose–volume constraints are satisfied. In each iteration step, an interior point method is adopted to solve each new linear constrained quadratic programming. For choosing the proper candidate voxels for the current dose constraint adding, a so-called geometric distance defined in the transformed standard quadratic form of the fluence map optimization model was used to guide the selection of the voxels. The new geometric distance sorting technique can mostly reduce the unexpected increase of the objective function value caused inevitably by the constraint adding. It can be regarded as an upgrading to the traditional dose sorting technique. The geometry explanation for the proposed method is also given and a proposition is proved to support our heuristic idea. In addition, a smart constraint adding/deleting strategy is designed to ensure a stable iteration convergence. The new algorithm is tested on four cases including head–neck, a prostate, a lung and an oropharyngeal, and compared with the algorithm based on the traditional dose sorting technique. Experimental results showed that the proposed method is more suitable for guiding the selection of new constraints than the traditional dose sorting method, especially for the cases whose target regions are in non-convex shapes. It is a more efficient optimization technique to some extent for choosing constraints than

Fluence map optimization (FMO) with dose-volume constraints in IMRT using the geometric distance sorting method.

Science.gov (United States)

Lan, Yihua; Li, Cunhua; Ren, Haozheng; Zhang, Yong; Min, Zhifang

2012-10-21

A new heuristic algorithm based on the so-called geometric distance sorting technique is proposed for solving the fluence map optimization with dose-volume constraints which is one of the most essential tasks for inverse planning in IMRT. The framework of the proposed method is basically an iterative process which begins with a simple linear constrained quadratic optimization model without considering any dose-volume constraints, and then the dose constraints for the voxels violating the dose-volume constraints are gradually added into the quadratic optimization model step by step until all the dose-volume constraints are satisfied. In each iteration step, an interior point method is adopted to solve each new linear constrained quadratic programming. For choosing the proper candidate voxels for the current dose constraint adding, a so-called geometric distance defined in the transformed standard quadratic form of the fluence map optimization model was used to guide the selection of the voxels. The new geometric distance sorting technique can mostly reduce the unexpected increase of the objective function value caused inevitably by the constraint adding. It can be regarded as an upgrading to the traditional dose sorting technique. The geometry explanation for the proposed method is also given and a proposition is proved to support our heuristic idea. In addition, a smart constraint adding/deleting strategy is designed to ensure a stable iteration convergence. The new algorithm is tested on four cases including head-neck, a prostate, a lung and an oropharyngeal, and compared with the algorithm based on the traditional dose sorting technique. Experimental results showed that the proposed method is more suitable for guiding the selection of new constraints than the traditional dose sorting method, especially for the cases whose target regions are in non-convex shapes. It is a more efficient optimization technique to some extent for choosing constraints than the dose

Occupants' satisfaction on building maintenance of government quarters

Science.gov (United States)

Ismail, Nur'Ain; Ali, Siti Noor Asmiza Md; Othman, Nor A'aini; Jaffar, Nooraidawati

2017-10-01

The satisfaction level of occupants toward the maintenance is very important to know the occupants comfortable with maintenance that was provided at the government quarters. The objective of the research is to determine the level of occupants satisfaction perceived of the maintenance in government quarter and also the level of quality of the maintenance of the government quarters. Data have been collected by using questionnaire in order to achieve the objective of the research. The questionnaires distributed among the occupants government quarters at Hospital Kota Bharu Kelantan. In the end of the research, the result are expected that to show the results on this satisfaction level of the occupants toward the maintenance at government quarters can be solve and the occupants can live more comfortable and get the good quality for maintenance and facilities in their houses.

Solving quantum optimal control problems using Clebsch variables and Lin constraints

Science.gov (United States)

Delgado-Téllez, M.; Ibort, A.; Rodríguez de la Peña, T.

2018-01-01

Clebsch variables (and Lin constraints) are applied to the study of a class of optimal control problems for affine-controlled quantum systems. The optimal control problem will be modelled with controls defined on an auxiliary space where the dynamical group of the system acts freely. The reciprocity between both theories: the classical theory defined by the objective functional and the quantum system, is established by using a suitable version of Lagrange’s multipliers theorem and a geometrical interpretation of the constraints of the system as defining a subspace of horizontal curves in an associated bundle. It is shown how the solutions of the variational problem defined by the objective functional determine solutions of the quantum problem. Then a new way of obtaining explicit solutions for a family of optimal control problems for affine-controlled quantum systems (finite or infinite dimensional) is obtained. One of its main advantages, is the the use of Clebsch variables allows to compute such solutions from solutions of invariant problems that can often be computed explicitly. This procedure can be presented as an algorithm that can be applied to a large class of systems. Finally, some simple examples, spin control, a simple quantum Hamiltonian with an ‘Elroy beanie’ type classical model and a controlled one-dimensional quantum harmonic oscillator, illustrating the main features of the theory, will be discussed.

Computing group cardinality constraint solutions for logistic regression problems.

Science.gov (United States)

Zhang, Yong; Kwon, Dongjin; Pohl, Kilian M

2017-01-01

We derive an algorithm to directly solve logistic regression based on cardinality constraint, group sparsity and use it to classify intra-subject MRI sequences (e.g. cine MRIs) of healthy from diseased subjects. Group cardinality constraint models are often applied to medical images in order to avoid overfitting of the classifier to the training data. Solutions within these models are generally determined by relaxing the cardinality constraint to a weighted feature selection scheme. However, these solutions relate to the original sparse problem only under specific assumptions, which generally do not hold for medical image applications. In addition, inferring clinical meaning from features weighted by a classifier is an ongoing topic of discussion. Avoiding weighing features, we propose to directly solve the group cardinality constraint logistic regression problem by generalizing the Penalty Decomposition method. To do so, we assume that an intra-subject series of images represents repeated samples of the same disease patterns. We model this assumption by combining series of measurements created by a feature across time into a single group. Our algorithm then derives a solution within that model by decoupling the minimization of the logistic regression function from enforcing the group sparsity constraint. The minimum to the smooth and convex logistic regression problem is determined via gradient descent while we derive a closed form solution for finding a sparse approximation of that minimum. We apply our method to cine MRI of 38 healthy controls and 44 adult patients that received reconstructive surgery of Tetralogy of Fallot (TOF) during infancy. Our method correctly identifies regions impacted by TOF and generally obtains statistically significant higher classification accuracy than alternative solutions to this model, i.e., ones relaxing group cardinality constraints. Copyright © 2016 Elsevier B.V. All rights reserved.

An adaptive ES with a ranking based constraint handling strategy

Directory of Open Access Journals (Sweden)

Kusakci Ali Osman

2014-01-01

Full Text Available To solve a constrained optimization problem, equality constraints can be used to eliminate a problem variable. If it is not feasible, the relations imposed implicitly by the constraints can still be exploited. Most conventional constraint handling methods in Evolutionary Algorithms (EAs do not consider the correlations between problem variables imposed by the constraints. This paper relies on the idea that a proper search operator, which captures mentioned implicit correlations, can improve performance of evolutionary constrained optimization algorithms. To realize this, an Evolution Strategy (ES along with a simplified Covariance Matrix Adaptation (CMA based mutation operator is used with a ranking based constraint-handling method. The proposed algorithm is tested on 13 benchmark problems as well as on a real life design problem. The outperformance of the algorithm is significant when compared with conventional ES-based methods.

Exact Methods for Solving the Train Departure Matching Problem

DEFF Research Database (Denmark)

Haahr, Jørgen Thorlund; Bull, Simon Henry

In this paper we consider the train departure matching problem which is an important subproblem of the Rolling Stock Unit Management on Railway Sites problem introduced in the ROADEF/EURO Challenge 2014. The subproblem entails matching arriving train units to scheduled departing trains at a railway...... site while respecting multiple physical and operational constraints. In this paper we formally define that subproblem, prove its NP- hardness, and present two exact method approaches for solving the problem. First, we present a compact Mixed Integer Program formulation which we solve using a MIP solver...

Interrelationship of motivation for and perceived constraints to physical activity participation and the well-being of senior center participants

Science.gov (United States)

Motoko Miyake; Ellen Rodgers

2009-01-01

This study investigated the relationship of motivation for and perceived constraints to physical activity (PA) participation and the well-being of senior center participants. A survey instrument made up of modified versions of the Sport Motivation and Perceived Constraints Scales, the Life Satisfaction Index-Z, and the Geriatric Depression Scale was administered at the...

Procedural Design of Exterior Lighting for Buildings with Complex Constraints

KAUST Repository

Schwarz, Michael

2014-10-01

We present a system for the lighting design of procedurally modeled buildings. The design is procedurally specified as part of the ordinary modeling workflow by defining goals for the illumination that should be attained and locations where luminaires may be installed to realize these goals. Additionally, constraints can be modeled that make the arrangement of the installed luminaires respect certain aesthetic and structural considerations. From this specification, the system automatically generates a lighting solution for any concrete model instance. The underlying, intricate joint optimization and constraint satisfaction problem is approached with a stochastic scheme that operates directly in the complex subspace where all constraints are observed. To navigate this subspace efficaciously, the actual lighting situation is taken into account. We demonstrate our system on multiple examples spanning a variety of architectural structures and lighting designs. Copyright held by the Owner/Author.

[Personal resources and nursing work: a research on coping strategies and job satisfaction].

Science.gov (United States)

Formentin, Silvia; Dallago, Lorenza; Negrisolo, Adriana

2009-01-01

The coping (ability to face a difficult situation), is an essential resource for nurses, because it increases the effective functioning in the working environment, job satisfaction and individual level of wellness. The aim of this study is to explore the relationship between coping strategies and job satisfaction. A self report questionnaire was administered to all the nurses working in health services and hospitals of Padua province and to free lance nurses members of the College of Nurses, to collect information on coping strategies and job satisfaction. 2264 questionnaires were returned (71%). Active coping strategies are adopted mainly from older nurses while avoiding strategies are prevalent among younger. An association was observed between job satisfaction and active coping strategies, aimed at problem solving: active strategies increase job satisfaction while avoiding strategies descrease it. Individual coping strategies implemented to face difficult situations are associated to job satisfaction.

An efficient computational method for a stochastic dynamic lot-sizing problem under service-level constraints

NARCIS (Netherlands)

Tarim, S.A.; Ozen, U.; Dogru, M.K.; Rossi, R.

2011-01-01

We provide an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman [8] for solving a stochastic lot-sizing problem with service level constraints under the static–dynamic uncertainty strategy. The effectiveness of the proposed method

Problem-Solving Management Training Effects on Sales Productivity and Job Satisfaction.

Science.gov (United States)

Ross, Paul C.; And Others

Research suggests that effective organizational change must be led by line personnel rather than by outside consultants. The Performance Management Program (PMP) implemented in two Bell Telephone companies is a line-led, self-help program in which managers participate in problem-solving activities within their own jobs. Marketing and sales…

Integrated case management for work-related upper-extremity disorders: impact of patient satisfaction on health and work status.

Science.gov (United States)

Feuerstein, Michael; Huang, Grant D; Ortiz, Jose M; Shaw, William S; Miller, Virginia I; Wood, Patricia M

2003-08-01

An integrated case management (ICM) approach (ergonomic and problem-solving intervention) to work-related upper-extremity disorders was examined in relation to patient satisfaction, future symptom severity, function, and return to work (RTW). Federal workers with work-related upper-extremity disorder workers' compensation claims (n = 205) were randomly assigned to usual care or ICM intervention. Patient satisfaction was assessed after the 4-month intervention period. Questionnaires on clinical outcomes and ergonomic exposure were administered at baseline and at 6- and 12-months postintervention. Time from intervention to RTW was obtained from an administrative database. ICM group assignment was significantly associated with greater patient satisfaction. Regression analyses found higher patient satisfaction levels predicted decreased symptom severity and functional limitations at 6 months and a shorter RTW. At 12 months, predictors of positive outcomes included male gender, lower distress, lower levels of reported ergonomic exposure, and receipt of ICM. Findings highlight the utility of targeting workplace ergonomic and problem solving skills.

Problem solving skills for schizophrenia.

Science.gov (United States)

Xia, J; Li, Chunbo

2007-04-18

The severe and long-lasting symptoms of schizophrenia are often the cause of severe disability. Environmental stress such as life events and the practical problems people face in their daily can worsen the symptoms of schizophrenia. Deficits in problem solving skills in people with schizophrenia affect their independent and interpersonal functioning and impair their quality of life. As a result, therapies such as problem solving therapy have been developed to improve problem solving skills for people with schizophrenia. To review the effectiveness of problem solving therapy compared with other comparable therapies or routine care for those with schizophrenia. We searched the Cochrane Schizophrenia Group's Register (September 2006), which is based on regular searches of BIOSIS, CENTRAL, CINAHL, EMBASE, MEDLINE and PsycINFO. We inspected references of all identified studies for further trials. We included all clinical randomised trials comparing problem solving therapy with other comparable therapies or routine care. We extracted data independently. For homogenous dichotomous data we calculated random effects, relative risk (RR), 95% confidence intervals (CI) and, where appropriate, numbers needed to treat (NNT) on an intention-to-treat basis. For continuous data, we calculated weighted mean differences (WMD) using a random effects statistical model. We included only three small trials (n=52) that evaluated problem solving versus routine care, coping skills training or non-specific interaction. Inadequate reporting of data rendered many outcomes unusable. We were unable to undertake meta-analysis. Overall results were limited and inconclusive with no significant differences between treatment groups for hospital admission, mental state, behaviour, social skills or leaving the study early. No data were presented for global state, quality of life or satisfaction. We found insufficient evidence to confirm or refute the benefits of problem solving therapy as an additional

The Effect of Some Constraints on Mathematics Instructors' Problem ...

African Journals Online (AJOL)

This study was designed to examine the effect of perceived constraints on four universities mathematics department instructors' classroom practices of problem solving in teaching mathematics. To this end, the target population of the study includes mathematics instructors in the Amhara Regional state universities. From a ...

An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

Science.gov (United States)

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.

A convex optimization approach for solving large scale linear systems

Directory of Open Access Journals (Sweden)

Debora Cores

2017-01-01

Full Text Available The well-known Conjugate Gradient (CG method minimizes a strictly convex quadratic function for solving large-scale linear system of equations when the coefficient matrix is symmetric and positive definite. In this work we present and analyze a non-quadratic convex function for solving any large-scale linear system of equations regardless of the characteristics of the coefficient matrix. For finding the global minimizers, of this new convex function, any low-cost iterative optimization technique could be applied. In particular, we propose to use the low-cost globally convergent Spectral Projected Gradient (SPG method, which allow us to extend this optimization approach for solving consistent square and rectangular linear system, as well as linear feasibility problem, with and without convex constraints and with and without preconditioning strategies. Our numerical results indicate that the new scheme outperforms state-of-the-art iterative techniques for solving linear systems when the symmetric part of the coefficient matrix is indefinite, and also for solving linear feasibility problems.

Solving Inventory Routing Problems Using Location Based Heuristics

Directory of Open Access Journals (Sweden)

Paweł Hanczar

2014-01-01

Full Text Available Inventory routing problems (IRPs occur where vendor managed inventory replenishment strategies are implemented in supply chains. These problems are characterized by the presence of both transportation and inventory considerations, either as parameters or constraints. The research presented in this paper aims at extending IRP formulation developed on the basis of location based heuristics proposed by Bramel and Simchi-Levi and continued by Hanczar. In the first phase of proposed algorithms, mixed integer programming is used to determine the partitioning of customers as well as dates and quantities of deliveries. Then, using 2-opt algorithm for solving the traveling sales-person problem the optimal routes for each partition are determined. In the main part of research the classical formulation is extended by additional constraints (visit spacing, vehicle filling rate, driver (vehicle consistency, and heterogeneous fleet of vehicles as well as the additional criteria are discussed. Then the impact of using each of proposed extensions for solution possibilities is evaluated. The results of computational tests are presented and discussed. Obtained results allow to conclude that the location based heuristics should be considered when solving real life instances of IRP. (original abstract

Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

Science.gov (United States)

Masternak, Tadeusz J.

This research determines temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method with a Non-Linear Programming (NLP) solver. The vehicle is assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom scramjet aircraft model is adapted from previous work and includes flight dynamics, aerodynamics, and thermal constraints. Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. To solve the optimal control formulation, a MATLAB-based package called General Pseudospectral Optimal Control Software (GPOPS-II) is used, which transcribes continuous time optimal control problems into an NLP problem. In addition, since a mission profile can have varying vehicle dynamics and en-route imposed constraints, the optimal control problem formulation can be broken up into several "phases" with differing dynamics and/or varying initial/final constraints. Optimal trajectories are developed using several different performance costs in the optimal control formulation: minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for larger-scale operational and campaign planning and execution.

How Do Severe Constraints Affect the Search Ability of Multiobjective Evolutionary Algorithms in Water Resources?

Science.gov (United States)

Clarkin, T. J.; Kasprzyk, J. R.; Raseman, W. J.; Herman, J. D.

2015-12-01

This study contributes a diagnostic assessment of multiobjective evolutionary algorithm (MOEA) search on a set of water resources problem formulations with different configurations of constraints. Unlike constraints in classical optimization modeling, constraints within MOEA simulation-optimization represent limits on acceptable performance that delineate whether solutions within the search problem are feasible. Constraints are relevant because of the emergent pressures on water resources systems: increasing public awareness of their sustainability, coupled with regulatory pressures on water management agencies. In this study, we test several state-of-the-art MOEAs that utilize restricted tournament selection for constraint handling on varying configurations of water resources planning problems. For example, a problem that has no constraints on performance levels will be compared with a problem with several severe constraints, and a problem with constraints that have less severe values on the constraint thresholds. One such problem, Lower Rio Grande Valley (LRGV) portfolio planning, has been solved with a suite of constraints that ensure high reliability, low cost variability, and acceptable performance in a single year severe drought. But to date, it is unclear whether or not the constraints are negatively affecting MOEAs' ability to solve the problem effectively. Two categories of results are explored. The first category uses control maps of algorithm performance to determine if the algorithm's performance is sensitive to user-defined parameters. The second category uses run-time performance metrics to determine the time required for the algorithm to reach sufficient levels of convergence and diversity on the solution sets. Our work exploring the effect of constraints will better enable practitioners to define MOEA problem formulations for real-world systems, especially when stakeholders are concerned with achieving fixed levels of performance according to one or

Constraints and Dedication as Drivers for Relationship Commitment: An Empirical Study in a Health-Care Context

OpenAIRE

Gaby Odekerken-Schröder; Bloemer Josée

2002-01-01

The objective of this study is to empirically determine the role of constraints and dedication as drivers of relationship commitment as most of the existing work is of a conceptual nature only. We assess how and to which extent these two drivers fit into the established relationships between overall service quality, satisfaction, trust and commitment. Using LISREL, we estimate the conceptual model based on a sample of customers of health-care centers. The results indicate that both constraint...

Solving ptychography with a convex relaxation

Science.gov (United States)

Horstmeyer, Roarke; Chen, Richard Y.; Ou, Xiaoze; Ames, Brendan; Tropp, Joel A.; Yang, Changhuei

2015-05-01

Ptychography is a powerful computational imaging technique that transforms a collection of low-resolution images into a high-resolution sample reconstruction. Unfortunately, algorithms that currently solve this reconstruction problem lack stability, robustness, and theoretical guarantees. Recently, convex optimization algorithms have improved the accuracy and reliability of several related reconstruction efforts. This paper proposes a convex formulation of the ptychography problem. This formulation has no local minima, it can be solved using a wide range of algorithms, it can incorporate appropriate noise models, and it can include multiple a priori constraints. The paper considers a specific algorithm, based on low-rank factorization, whose runtime and memory usage are near-linear in the size of the output image. Experiments demonstrate that this approach offers a 25% lower background variance on average than alternating projections, the ptychographic reconstruction algorithm that is currently in widespread use.

A complete solution of the Bianchi identities in superspace with supergravity constraints

International Nuclear Information System (INIS)

Grimm, R.; Wess, J.; Zumino, B.

1979-01-01

A short discussion of the superspace formulation of supergravity is given and the Bianchi identities are derived. The supergravity constraints are imposed and the identities are solved in terms of superfields and their covariant derivatives. (Auth.)

Improved Monkey-King Genetic Algorithm for Solving Large Winner Determination in Combinatorial Auction

Science.gov (United States)

Li, Yuzhong

Using GA solve the winner determination problem (WDP) with large bids and items, run under different distribution, because the search space is large, constraint complex and it may easy to produce infeasible solution, would affect the efficiency and quality of algorithm. This paper present improved MKGA, including three operator: preprocessing, insert bid and exchange recombination, and use Monkey-king elite preservation strategy. Experimental results show that improved MKGA is better than SGA in population size and computation. The problem that traditional branch and bound algorithm hard to solve, improved MKGA can solve and achieve better effect.

Constraint Logic Programming approach to protein structure prediction

Directory of Open Access Journals (Sweden)

Fogolari Federico

2004-11-01

Full Text Available Abstract Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

Constraint Logic Programming approach to protein structure prediction.

Science.gov (United States)

Dal Palù, Alessandro; Dovier, Agostino; Fogolari, Federico

2004-11-30

The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

Theory of Perturbed Equilibria for Solving the Grad-Shafranov Equation

International Nuclear Information System (INIS)

Pletzer, A.; Zakharov, L.E.

1999-01-01

The theory of perturbed magnetohydrodynamic equilibria is presented for different formulations of the tokamak equilibrium problem. For numerical codes, it gives an explicit Newton scheme for solving the Grad-Shafranov equation subject to different constraints. The problem of stability of axisymmetric modes is shown to be a particular case of the equilibrium perturbation theory

An effortless hybrid method to solve economic load dispatch problem in power systems

International Nuclear Information System (INIS)

Pourakbari-Kasmaei, M.; Rashidi-Nejad, M.

2011-01-01

Highlights: → We proposed a fast method to get feasible solution and avoid futile search. → The method dramatically improves search efficiency and solution quality. → Applied to solve constrained ED problems of power systems with 6 and 15 unit. → Superiority of this method in both aspects of financial and CPU time is remarkable. - Abstract: This paper proposes a new approach and coding scheme for solving economic dispatch problems (ED) in power systems through an effortless hybrid method (EHM). This novel coding scheme can effectively prevent futile searching and also prevents obtaining infeasible solutions through the application of stochastic search methods, consequently dramatically improves search efficiency and solution quality. The dominant constraint of an economic dispatch problem is power balance. The operational constraints, such as generation limitations, ramp rate limits, prohibited operating zones (POZ), network loss are considered for practical operation. Firstly, in the EHM procedure, the output of generator is obtained with a lambda iteration method and without considering POZ and later in a genetic based algorithm this constraint is satisfied. To demonstrate its efficiency, feasibility and fastness, the EHM algorithm was applied to solve constrained ED problems of power systems with 6 and 15 units. The simulation results obtained from the EHM were compared to those achieved from previous literature in terms of solution quality and computational efficiency. Results reveal that the superiority of this method in both aspects of financial and CPU time.

Optimal satisfaction degree in energy harvesting cognitive radio networks

Science.gov (United States)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

Science.gov (United States)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

Embedded System Synthesis under Memory Constraints

DEFF Research Database (Denmark)

Madsen, Jan; Bjørn-Jørgensen, Peter

1999-01-01

This paper presents a genetic algorithm to solve the system synthesis problem of mapping a time constrained single-rate system specification onto a given heterogeneous architecture which may contain irregular interconnection structures. The synthesis is performed under memory constraints, that is......, the algorithm takes into account the memory size of processors and the size of interface buffers of communication links, and in particular the complicated interplay of these. The presented algorithm is implemented as part of the LY-COS cosynthesis system....

Analysis of Space Tourism Constraints

Science.gov (United States)

Bonnal, Christophe

2002-01-01

Space tourism appears today as a new Eldorado in a relatively near future. Private operators are already proposing services for leisure trips in Low Earth Orbit, and some happy few even tested them. But are these exceptional events really marking the dawn of a new space age ? The constraints associated to the space tourism are severe : - the economical balance of space tourism is tricky; development costs of large manned - the technical definition of such large vehicles is challenging, mainly when considering - the physiological aptitude of passengers will have a major impact on the mission - the orbital environment will also lead to mission constraints on aspects such as radiation, However, these constraints never appear as show-stoppers and have to be dealt with pragmatically: - what are the recommendations one can make for future research in the field of space - which typical roadmap shall one consider to develop realistically this new market ? - what are the synergies with the conventional missions and with the existing infrastructure, - how can a phased development start soon ? The paper proposes hints aiming at improving the credibility of Space Tourism and describes the orientations to follow in order to solve the major hurdles found in such an exciting development.

Serious Leisure and People with Orthopedic Impairment: Benefits and Constraints

OpenAIRE

Manolya AKSATAN; Zehra Gökçe SEL

2017-01-01

There are many people around the world who have different types of disabilities. Understanding their needs is the first step of developing policies to increase their quality of life and satisfaction. Leisure is an essential need of disabled people and it plays an important role in disabled people’s lives. The purpose of this study is to gain a deep understanding on the serious leisure activities of people with orthopedic impairment, and also both benefits and constraints ...

Sleep Does Not Promote Solving Classical Insight Problems and Magic Tricks

Science.gov (United States)

Schönauer, Monika; Brodt, Svenja; Pöhlchen, Dorothee; Breßmer, Anja; Danek, Amory H.; Gais, Steffen

2018-01-01

During creative problem solving, initial solution attempts often fail because of self-imposed constraints that prevent us from thinking out of the box. In order to solve a problem successfully, the problem representation has to be restructured by combining elements of available knowledge in novel and creative ways. It has been suggested that sleep supports the reorganization of memory representations, ultimately aiding problem solving. In this study, we systematically tested the effect of sleep and time on problem solving, using classical insight tasks and magic tricks. Solving these tasks explicitly requires a restructuring of the problem representation and may be accompanied by a subjective feeling of insight. In two sessions, 77 participants had to solve classical insight problems and magic tricks. The two sessions either occurred consecutively or were spaced 3 h apart, with the time in between spent either sleeping or awake. We found that sleep affected neither general solution rates nor the number of solutions accompanied by sudden subjective insight. Our study thus adds to accumulating evidence that sleep does not provide an environment that facilitates the qualitative restructuring of memory representations and enables problem solving. PMID:29535620

The Impact of Short-Sale Constraints on Asset Allocation Strategies via the Backward Markov Chain Approximation Method

OpenAIRE

Carl Chiarella; Chih-Ying Hsiao

2005-01-01

This paper considers an asset allocation strategy over a finite period under investment uncertainty and short-sale constraints as a continuous time stochastic control problem. Investment uncertainty is characterised by a stochastic interest rate and inflation risk. If there are no short-sale constraints, the optimal asset allocation strategy can be solved analytically. We consider several kinds of short-sale constraints and employ the backward Markov chain approximation method to explore the ...

Finite-life fatigue constraints in 2D topology optimization of continua

DEFF Research Database (Denmark)

Oest, Jacob; Lund, Erik

2017-01-01

of fatigue damage are estimated using the stress-based Sines fatigue criterion and S − N curves, while the accumulated damage is estimated using Palmgren-Miner’s rule. The method is a natural extension of classical density-based topology optimization with static stress constraints, and thus utilizes many......Topology optimization of 2D continua with the objective of minimizing the mass while considering finite-life fatigue constraint is considered. The structure is subjected to proportional variable-amplitude loading. The topology optimization problem is solved using the density approach. The fractions...

A balancing domain decomposition method by constraints for advection-diffusion problems

Energy Technology Data Exchange (ETDEWEB)

Tu, Xuemin; Li, Jing

2008-12-10

The balancing domain decomposition methods by constraints are extended to solving nonsymmetric, positive definite linear systems resulting from the finite element discretization of advection-diffusion equations. A pre-conditioned GMRES iteration is used to solve a Schur complement system of equations for the subdomain interface variables. In the preconditioning step of each iteration, a partially sub-assembled finite element problem is solved. A convergence rate estimate for the GMRES iteration is established, under the condition that the diameters of subdomains are small enough. It is independent of the number of subdomains and grows only slowly with the subdomain problem size. Numerical experiments for several two-dimensional advection-diffusion problems illustrate the fast convergence of the proposed algorithm.

Bayesian Optimization Under Mixed Constraints with A Slack-Variable Augmented Lagrangian

Energy Technology Data Exchange (ETDEWEB)

Picheny, Victor; Gramacy, Robert B.; Wild, Stefan M.; Le Digabel, Sebastien

2016-12-05

An augmented Lagrangian (AL) can convert a constrained optimization problem into a sequence of simpler (e.g., unconstrained) problems, which are then usually solved with local solvers. Recently, surrogate-based Bayesian optimization (BO) sub-solvers have been successfully deployed in the AL framework for a more global search in the presence of inequality constraints; however, a drawback was that expected improvement (EI) evaluations relied on Monte Carlo. Here we introduce an alternative slack variable AL, and show that in this formulation the EI may be evaluated with library routines. The slack variables furthermore facilitate equality as well as inequality constraints, and mixtures thereof. We show our new slack “ALBO” compares favorably to the original. Its superiority over conventional alternatives is reinforced on several mixed constraint examples.

May heavy neutrinos solve underground and cosmic-ray puzzles?

International Nuclear Information System (INIS)

Belotsky, K. M.; Fargion, D.; Khlopov, M. Yu.; Konoplich, R. V.

2008-01-01

Primordial heavy neutrinos of the fourth generation might explain different astrophysical puzzles. The simplest fourth-neutrino scenario is consistent with known fourth-neutrino physics, cosmic ray antimatter, cosmic gamma fluxes, and positive signals in underground detectors for a very narrow neutrino mass window (46–47 GeV). However, accounting for the constraint of underground experiment CDMS prohibits solution of cosmic-ray puzzles in this scenario. We have analyzed extended heavy-neutrino models related to the clumpiness of neutrino density, new interactions in heavy-neutrino annihilation, neutrino asymmetry, and neutrino decay. We found that, in these models, the cosmic-ray imprint may fit the positive underground signals in DAMA/Nal experiment in the entire mass range 46–70 GeV allowed from uncertainties of electroweak parameters, while satisfaction of the CDMS constraint reduces the mass range to around 50 GeV, where all data can come to consent in the framework of the considered hypothesis.

May heavy neutrinos solve underground and cosmic-ray puzzles?

International Nuclear Information System (INIS)

Belotsky, K. M.; Fargion, D.; Khlopov, M. Yu.; Konoplich, R. V.

2008-01-01

Primordial heavy neutrinos of the fourth generation might explain different astrophysical puzzles. The simplest fourth-neutrino scenario is consistent with known fourth-neutrino physics, cosmic ray antimatter, cosmic gamma fluxes, and positive signals in underground detectors for a very narrow neutrino mass window (46-47 GeV). However, accounting for the constraint of underground experiment CDMS prohibits solution of cosmic-ray puzzles in this scenario. We have analyzed extended heavy-neutrino models related to the clumpiness of neutrino density, new interactions in heavy-neutrino annihilation, neutrino asymmetry, and neutrino decay. We found that, in these models, the cosmic-ray imprint may fit the positive underground signals in DAMA/Nal experiment in the entire mass range 46-70 GeV allowed from uncertainties of electroweak parameters, while satisfaction of the CDMS constraint reduces the mass range to around 50 GeV, where all data can come to consent in the framework of the considered hypothesis

Exploring direct and indirect influences of physical work environment on job satisfaction for early-career registered nurses employed in hospitals.

Science.gov (United States)

Djukic, Maja; Kovner, Christine T; Brewer, Carol S; Fatehi, Farida; Greene, William H

2014-08-01

We explored direct and indirect influences of physical work environment on job satisfaction in a nationally representative sample of 1,141 early-career registered nurses. In the fully specified model, physical work environment had a non-significant direct effect on job satisfaction. The path analysis used to test multiple indirect effects showed that physical work environment had a positive indirect effect (p nurse-physician relations, quantitative workload, organizational constraints, distributive justice, promotional opportunity, local and non-local job opportunities. The findings make important contributions to the understanding of the relationship between physical work environment and job satisfaction. The results can inform health care leaders' insight about how physical work environment influences nurses' job satisfaction. © 2014 Wiley Periodicals, Inc.

Optimal Design of Composite Structures Under Manufacturing Constraints

DEFF Research Database (Denmark)

Marmaras, Konstantinos

algorithms to perform the global optimization. The efficiency of the proposed models is examined on a set of well–defined discrete multi material and thickness optimization problems originating from the literature. The inclusion of manufacturing limitations along with structural considerations in the early...... mixed integer 0–1 programming problems. The manufacturing constraints have been treated by developing explicit models with favorable properties. In this thesis we have developed and implemented special purpose global optimization methods and heuristic techniques for solving this class of problems......This thesis considers discrete multi material and thickness optimization of laminated composite structures including local failure criteria and manufacturing constraints. Our models closely follow an immediate extension of the Discrete Material Optimization scheme, which allows simultaneous...

Finer Distinctions: Variability in Satisfied Older Couples' Problem-Solving Behaviors.

Science.gov (United States)

Rauer, Amy; Williams, Leah; Jensen, Jakob

2017-06-01

This study utilized observational and self-report data from 64 maritally satisfied and stable older couples to explore if there were meaningful differences in how couples approached marital disagreements. Using a typology approach to classify couples based on their behaviors in a 15-minute problem-solving interaction, findings revealed four types of couples: (1) problem solvers (characterized by both spouses' higher problem-solving skills and warmth), (2) supporters (characterized by both spouses' notable warmth), (3) even couples (characterized by both spouses' moderate problem-solving skills and warmth), and (4) cool couples (characterized by both spouses' greater negativity and lower problem-solving skills and warmth). Despite the differences in these behaviors, all couples had relatively high marital satisfaction and functioning. However, across nearly all indices, spouses in the cool couple cluster reported poorer marital functioning, particularly when compared to the problem solvers and supporters. These findings suggest that even modest doses of negativity (e.g., eye roll) may be problematic for some satisfied couples later in life. The implications of these typologies are discussed as they pertain to practitioners' efforts to tailor their approaches to a wider swath of the population. © 2015 Family Process Institute.

Coalitions and family problem solving with preadolescents in referred, at-risk, and comparison families.

Science.gov (United States)

Vuchinich, S; Wood, B; Vuchinich, R

1994-12-01

This study tested the hypothesis that the mother-father coalition, parent-child coalitions, and parental warmth expressed toward the child are associated with family problem solving in families with a preadolescent child referred for treatment of behavior problems (n = 30), families with a child at-risk for conduct disorder (n = 68), and a sample of comparison families (n = 90). Referred and at-risk families displayed less effective problem solving. A regression analysis, which controlled for gender of the child, family structure, family income, marital satisfaction, and severity of child problems, showed that strong parental coalitions were linked to low levels of family problem solving in at-risk and referred families. Parent-child coalitions had little apparent impact while parental warmth was highly correlated with better family problem solving. The results may be interpreted as evidence for a tendency for parents in at-risk and referred families to "scapegoat" a preadolescent during family problem-solving sessions. This may undermine progress on family problem solutions and may complicate family-based prevention and treatment programs that use family problem-solving sessions.

Minimization of the root of a quadratic functional under a system of affine equality constraints with application to portfolio management

Science.gov (United States)

Landsman, Zinoviy

2008-10-01

We present an explicit closed form solution of the problem of minimizing the root of a quadratic functional subject to a system of affine constraints. The result generalizes Z. Landsman, Minimization of the root of a quadratic functional under an affine equality constraint, J. Comput. Appl. Math. 2007, to appear, see sciencedirect.com/science/journal/03770427>, articles in press, where the optimization problem was solved under only one linear constraint. This is of interest for solving significant problems pertaining to financial economics as well as some classes of feasibility and optimization problems which frequently occur in tomography and other fields. The results are illustrated in the problem of optimal portfolio selection and the particular case when the expected return of finance portfolio is certain is discussed.

Optimal Pricing and Production Master Planning in a Multiperiod Horizon Considering Capacity and Inventory Constraints

Directory of Open Access Journals (Sweden)

Neale R. Smith

2009-01-01

Full Text Available We formulate and solve a single-item joint pricing and master planning optimization problem with capacity and inventory constrains. The objective is to maximize profits over a discrete-time multiperiod horizon. The solution process consists of two steps. First, we solve the single-period problem exactly. Second, using the exact solution of the single-period problem, we solve the multiperiod problem using a dynamic programming approach. The solution process and the importance of considering both capacity and inventory constraints are illustrated with numerical examples.

A Strongly and Superlinearly Convergent SQP Algorithm for Optimization Problems with Linear Complementarity Constraints

International Nuclear Information System (INIS)

Jian Jinbao; Li Jianling; Mo Xingde

2006-01-01

This paper discusses a kind of optimization problem with linear complementarity constraints, and presents a sequential quadratic programming (SQP) algorithm for solving a stationary point of the problem. The algorithm is a modification of the SQP algorithm proposed by Fukushima et al. [Computational Optimization and Applications, 10 (1998),5-34], and is based on a reformulation of complementarity condition as a system of linear equations. At each iteration, one quadratic programming and one system of equations needs to be solved, and a curve search is used to yield the step size. Under some appropriate assumptions, including the lower-level strict complementarity, but without the upper-level strict complementarity for the inequality constraints, the algorithm is proved to possess strong convergence and superlinear convergence. Some preliminary numerical results are reported

Hybrid Discrete Differential Evolution Algorithm for Lot Splitting with Capacity Constraints in Flexible Job Scheduling

Directory of Open Access Journals (Sweden)

Xinli Xu

2013-01-01

Full Text Available A two-level batch chromosome coding scheme is proposed to solve the lot splitting problem with equipment capacity constraints in flexible job shop scheduling, which includes a lot splitting chromosome and a lot scheduling chromosome. To balance global search and local exploration of the differential evolution algorithm, a hybrid discrete differential evolution algorithm (HDDE is presented, in which the local strategy with dynamic random searching based on the critical path and a random mutation operator is developed. The performance of HDDE was experimented with 14 benchmark problems and the practical dye vat scheduling problem. The simulation results showed that the proposed algorithm has the strong global search capability and can effectively solve the practical lot splitting problems with equipment capacity constraints.

A decomposition method for network-constrained unit commitment with AC power flow constraints

International Nuclear Information System (INIS)

Bai, Yang; Zhong, Haiwang; Xia, Qing; Kang, Chongqing; Xie, Le

2015-01-01

To meet the increasingly high requirement of smart grid operations, considering AC power flow constraints in the NCUC (network-constrained unit commitment) is of great significance in terms of both security and economy. This paper proposes a decomposition method to solve NCUC with AC power flow constraints. With conic approximations of the AC power flow equations, the master problem is formulated as a MISOCP (mixed integer second-order cone programming) model. The key advantage of this model is that the active power and reactive power are co-optimised, and the transmission losses are considered. With the AC optimal power flow model, the AC feasibility of the UC result of the master problem is checked in subproblems. If infeasibility is detected, feedback constraints are generated based on the sensitivity of bus voltages to a change in the unit reactive power generation. They are then introduced into the master problem in the next iteration until all AC violations are eliminated. A 6-bus system, a modified IEEE 30-bus system and the IEEE 118-bus system are used to validate the performance of the proposed method, which provides a satisfactory solution with approximately 44-fold greater computational efficiency. - Highlights: • A decomposition method is proposed to solve the NCUC with AC power flow constraints • The master problem considers active power, reactive power and transmission losses. • OPF-based subproblems check the AC feasibility using parallel computing techniques. • An effective feedback constraint interacts between the master problem and subproblem. • Computational efficiency is significantly improved with satisfactory accuracy

Finding the optimal Bayesian network given a constraint graph

Directory of Open Access Journals (Sweden)

Jacob M. Schreiber

2017-07-01

Full Text Available Despite recent algorithmic improvements, learning the optimal structure of a Bayesian network from data is typically infeasible past a few dozen variables. Fortunately, domain knowledge can frequently be exploited to achieve dramatic computational savings, and in many cases domain knowledge can even make structure learning tractable. Several methods have previously been described for representing this type of structural prior knowledge, including global orderings, super-structures, and constraint rules. While super-structures and constraint rules are flexible in terms of what prior knowledge they can encode, they achieve savings in memory and computational time simply by avoiding considering invalid graphs. We introduce the concept of a “constraint graph” as an intuitive method for incorporating rich prior knowledge into the structure learning task. We describe how this graph can be used to reduce the memory cost and computational time required to find the optimal graph subject to the encoded constraints, beyond merely eliminating invalid graphs. In particular, we show that a constraint graph can break the structure learning task into independent subproblems even in the presence of cyclic prior knowledge. These subproblems are well suited to being solved in parallel on a single machine or distributed across many machines without excessive communication cost.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

Science.gov (United States)

Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Total-variation regularization with bound constraints

International Nuclear Information System (INIS)

Chartrand, Rick; Wohlberg, Brendt

2009-01-01

We present a new algorithm for bound-constrained total-variation (TV) regularization that in comparison with its predecessors is simple, fast, and flexible. We use a splitting approach to decouple TV minimization from enforcing the constraints. Consequently, existing TV solvers can be employed with minimal alteration. This also makes the approach straightforward to generalize to any situation where TV can be applied. We consider deblurring of images with Gaussian or salt-and-pepper noise, as well as Abel inversion of radiographs with Poisson noise. We incorporate previous iterative reweighting algorithms to solve the TV portion.

Modeling Network Transition Constraints with Hypergraphs

DEFF Research Database (Denmark)

Harrod, Steven

2011-01-01

Discrete time dynamic graphs are frequently used to model multicommodity flows or activity paths through constrained resources, but simple graphs fail to capture the interaction effects of resource transitions. The resulting schedules are not operationally feasible, and return inflated objective...... values. A directed hypergraph formulation is derived to address railway network sequencing constraints, and an experimental problem sample solved to estimate the magnitude of objective inflation when interaction effects are ignored. The model is used to demonstrate the value of advance scheduling...... of train paths on a busy North American railway....

The roles of constraint-based and dedication-based influences on user's continued online shopping behavior.

Science.gov (United States)

Chang, Su-Chao; Chou, Chi-Min

2012-11-01

The objective of this study was to determine empirically the role of constraint-based and dedication-based influences as drivers of the intention to continue using online shopping websites. Constraint-based influences consist of two variables: trust and perceived switching costs. Dedication-based influences consist of three variables: satisfaction, perceived usefulness, and trust. The current results indicate that both constraint-based and dedication-based influences are important drivers of the intention to continue using online shopping websites. The data also shows that trust has the strongest total effect on online shoppers' intention to continue using online shopping websites. In addition, the results indicate that the antecedents of constraint-based influences, technical bonds (e.g., perceived operational competence and perceived website interactivity) and social bonds (e.g., perceived relationship investment, community building, and intimacy) have indirect positive effects on the intention to continue using online shopping websites. Based on these findings, this research suggests that online shopping websites should build constraint-based and dedication-based influences to enhance user's continued online shopping behaviors simultaneously.

Determinants of job satisfaction for novice nurse managers employed in hospitals.

Science.gov (United States)

Djukic, Maja; Jun, Jin; Kovner, Christine; Brewer, Carol; Fletcher, Jason

Numbering close to 300,000 nurse managers represent the largest segment of the health care management workforce. Their effectiveness is, in part, influenced by their job satisfaction. We examined factors associated with job satisfaction of novice frontline nurse managers. We used a cross-sectional, correlational survey design. The sample consisted of responders to the fifth wave of a multiyear study of new nurses in 2013 (N = 1,392; response rate of 69%) who reported working as managers (n = 209). The parent study sample consisted of registered nurses who were licensed for the first time by exam 6-18 months prior in 1 of 51 selected metropolitan statistical areas and 9 rural areas across 34 U.S. states and the District of Columbia. We examined bivariate correlations between job satisfaction and 31 personal and structural variables. All variables significantly related to job satisfaction in bivariate analysis were included in a multivariate linear regression model. In addition, we tested the interaction effects of procedural justice and negative affectivity, autonomy, and organizational constraints on job satisfaction. The Cronbach's alphas for all multi-item scales ranged from .74 to .96. In the multivariate analysis, negative affectivity (β = -.169; p = .006) and procedural justice (β = .210; p = .016) were significantly correlated with job satisfaction. The combination of predictors in the model accounted for half of the variability in job satisfaction ratings (R = .51, adjusted R = .47; p <. 001). Health care executives who want to cultivate an effective novice frontline nurse manager workforce can best ensure their satisfaction by creating an organization with strong procedural justice. This could be achieved by involving managers in decision-making processes and ensuring transparency about how decisions that affect nursing are made.

Exploring a Structure for Mathematics Lessons That Foster Problem Solving and Reasoning

Science.gov (United States)

Sullivan, Peter; Walker, Nadia; Borcek, Chris; Rennie, Mick

2015-01-01

While there is widespread agreement on the importance of incorporating problem solving and reasoning into mathematics classrooms, there is limited specific advice on how this can best happen. This is a report of an aspect of a project that is examining the opportunities and constraints in initiating learning by posing challenging mathematics tasks…

Coping mediates the influence of personality on life satisfaction in patients with rheumatic diseases.

Science.gov (United States)

Vollmann, Manja; Pukrop, Jörg; Salewski, Christel

2016-04-01

A rheumatic disease can severely impair a person's quality of life. The degree of impairment, however, is not closely related to objective indicators of disease severity. This study investigated the influence and the interplay of core psychological factors, i.e., personality and coping, on life satisfaction in patients with rheumatic diseases. Particularly, it was tested whether coping mediates the effects of personality on life satisfaction. In a cross-sectional design, 158 patients diagnosed with a rheumatic disease completed questionnaires assessing the Big 5 personality traits (BFI-10), several disease-related coping strategies (EFK) and life satisfaction (HSWBS). Data were analyzed using a complex multiple mediation analysis with the Big 5 personality traits as predictors, coping strategies as mediators and life satisfaction as outcome. All personality traits and seven of the nine coping strategies were associated with life satisfaction (rs > |0.16|, ps ≤ 0.05). The mediation analysis revealed that personality traits had no direct, but rather indirect effects on life satisfaction through coping. Neuroticism had a negative indirect effect on life satisfaction through less active problem solving and more depressive coping (indirect effects > -0.03, ps  0.06, ps rheumatic diseases. The interplay of these variables should be considered in psychological interventions for patients with rheumatic diseases.

Null Space Integration Method for Constrained Multibody Systems with No Constraint Violation

International Nuclear Information System (INIS)

Terze, Zdravko; Lefeber, Dirk; Muftic, Osman

2001-01-01

A method for integrating equations of motion of constrained multibody systems with no constraint violation is presented. A mathematical model, shaped as a differential-algebraic system of index 1, is transformed into a system of ordinary differential equations using the null-space projection method. Equations of motion are set in a non-minimal form. During integration, violations of constraints are corrected by solving constraint equations at the position and velocity level, utilizing the metric of the system's configuration space, and projective criterion to the coordinate partitioning method. The method is applied to dynamic simulation of 3D constrained biomechanical system. The simulation results are evaluated by comparing them to the values of characteristic parameters obtained by kinematics analysis of analyzed motion based unmeasured kinematics data

Financial satisfaction and financial stressors in marital satisfaction.

Science.gov (United States)

Archuleta, Kristy L; Britt, Sonya L; Tonn, Teresa J; Grable, John E

2011-04-01

Using a sample of 310 married respondents from one U.S. Midwestern state, a test was conducted to examine the association of financial satisfaction and financial stressors in a spouse's decision to stay married to the same person or leave the relationship. The role of demographic and socioeconomic variables, religiosity, psychological constructs, financial satisfaction, and financial stressors as factors influencing marital satisfaction was tested. Financial stressors were measured using a list of financial stressors adapted from the literature. Financial satisfaction was measured with a one-item scale. The Kansas Marital Satisfaction Scale was used as a validation tool to assess whether individuals would marry or not marry again. Religiosity and financial satisfaction were positively associated with marital satisfaction. A negative interaction between financial satisfaction and financial stressors was also noted. Findings suggest that respondents who are financially satisfied tend to be more stable in their marriages.

Invalid-point removal based on epipolar constraint in the structured-light method

Science.gov (United States)

Qi, Zhaoshuai; Wang, Zhao; Huang, Junhui; Xing, Chao; Gao, Jianmin

2018-06-01

In structured-light measurement, there unavoidably exist many invalid points caused by shadows, image noise and ambient light. According to the property of the epipolar constraint, because the retrieved phase of the invalid point is inaccurate, the corresponding projector image coordinate (PIC) will not satisfy the epipolar constraint. Based on this fact, a new invalid-point removal method based on the epipolar constraint is proposed in this paper. First, the fundamental matrix of the measurement system is calculated, which will be used for calculating the epipolar line. Then, according to the retrieved phase map of the captured fringes, the PICs of each pixel are retrieved. Subsequently, the epipolar line in the projector image plane of each pixel is obtained using the fundamental matrix. The distance between the corresponding PIC and the epipolar line of a pixel is defined as the invalidation criterion, which quantifies the satisfaction degree of the epipolar constraint. Finally, all pixels with a distance larger than a certain threshold are removed as invalid points. Experiments verified that the method is easy to implement and demonstrates better performance than state-of-the-art measurement systems.

Solving an inverse eigenvalue problem with triple constraints on eigenvalues, singular values, and diagonal elements

Science.gov (United States)

Wu, Sheng-Jhih; Chu, Moody T.

2017-08-01

An inverse eigenvalue problem usually entails two constraints, one conditioned upon the spectrum and the other on the structure. This paper investigates the problem where triple constraints of eigenvalues, singular values, and diagonal entries are imposed simultaneously. An approach combining an eclectic mix of skills from differential geometry, optimization theory, and analytic gradient flow is employed to prove the solvability of such a problem. The result generalizes the classical Mirsky, Sing-Thompson, and Weyl-Horn theorems concerning the respective majorization relationships between any two of the arrays of main diagonal entries, eigenvalues, and singular values. The existence theory fills a gap in the classical matrix theory. The problem might find applications in wireless communication and quantum information science. The technique employed can be implemented as a first-step numerical method for constructing the matrix. With slight modification, the approach might be used to explore similar types of inverse problems where the prescribed entries are at general locations.

Solving an inverse eigenvalue problem with triple constraints on eigenvalues, singular values, and diagonal elements

International Nuclear Information System (INIS)

Wu, Sheng-Jhih; Chu, Moody T

2017-01-01

An inverse eigenvalue problem usually entails two constraints, one conditioned upon the spectrum and the other on the structure. This paper investigates the problem where triple constraints of eigenvalues, singular values, and diagonal entries are imposed simultaneously. An approach combining an eclectic mix of skills from differential geometry, optimization theory, and analytic gradient flow is employed to prove the solvability of such a problem. The result generalizes the classical Mirsky, Sing–Thompson, and Weyl-Horn theorems concerning the respective majorization relationships between any two of the arrays of main diagonal entries, eigenvalues, and singular values. The existence theory fills a gap in the classical matrix theory. The problem might find applications in wireless communication and quantum information science. The technique employed can be implemented as a first-step numerical method for constructing the matrix. With slight modification, the approach might be used to explore similar types of inverse problems where the prescribed entries are at general locations. (paper)

Stochastic optimization under risk constraint and utility functions

International Nuclear Information System (INIS)

Seck, B.

2008-09-01

In a context of concurrence and emergence of energy markets, the production of electricity is affected by the new sources of risks which are the price variations on the energy markets. These new sources of risks generate a new risk: the market risk. In this research, the author explores the possibility of introducing constraints, expressed by measurements of risk, into the process of optimization of electricity production when financial contracts are signed on the energy market. The author makes the distinction between the engineering approach (taking the risk into account by risk measurements) and the economist approach (taking the risk into account by utility functions). After an overview of these both approaches in a static framework, he gives an economical formulation (a Maccheroni type one) for a static optimization problem under a risk constraint when the risk measurement is written under the form of an expected infimum like the variance, the 'conditional value at risk', and so on. The obtained results are then extended to a dynamic optimization framework under risk constraints. A numerical application of this approach is presented to solve a problem of electricity production management under a constraint of 'conditional value at risk' on a middle term

Satisfaction

NARCIS (Netherlands)

van der Voordt, Theo; Brunia, Sandra; Appel - Meulenbroek, Rianne; Jensen, P.A.; van der Voordt, T.

2016-01-01

This chapter presents some findings from surveys on employee satisfaction in different work environments in the Netherlands and various other European countries. It first discusses why employee satisfaction is relevant for organisations and which factors may influence employee satisfaction. Then the

An integrated approach for solving a MCDM problem, Combination of Entropy Fuzzy and F-PROMETHEE techniques

Directory of Open Access Journals (Sweden)

Amin Shahmardan

2013-09-01

Full Text Available Purpose: The intention of this paper is the presentation of a new integrated approach for solving a multi attribute decision making problem by the use of Entropy Fuzzy and F- PROMETHEE (fuzzy preference ranking method for enrichment evaluation techniques. Design/methodology/approach: In these sorts of multi attribute decision making problem, a number of criteria and alternatives are put forward as input data. Ranking of these alternatives according to mentioned criteria is regarded as the outcome of solving these kinds of problems. Initially, weights of criteria are determined by implementation of Entropy Fuzzy method. According to determined weights, F-PROMETHEE method is exerted to rank these alternatives in terms of desirability of DM (decision maker. Findings: Being in an uncertain environment and vagueness of DM’s judgments, lead us to implement an algorithm which can deal with these constraints properly. This technique namely called Entropy Fuzzy as a weighting method and F-PROMETHEE is performed to fulfill this approach more precisely according to tangible and intangible aspects. The main finding of applied approach is the final ranking of alternatives helping DM to have a more reliable decision. Originality/Value: The main contribution of this approach is the giving real significance to DM’s attitudes about mentioned criteria in determined alternatives which is not elucidate in former approaches like Analytical Hierarchy Process (AHP. Furthermore, previous methods like Shanon Entropy do not pay attention sufficiently to satisfaction degree of each criterion in proposed alternatives, regarding to DM’s statements. Comprehensive explanations about these procedures have been made in miscellaneous sections of this article.

An improved Pattern Search based algorithm to solve the Dynamic Economic Dispatch problem with valve-point effect

International Nuclear Information System (INIS)

Alsumait, J.S.; Qasem, M.; Sykulski, J.K.; Al-Othman, A.K.

2010-01-01

In this paper, an improved algorithm based on Pattern Search method (PS) to solve the Dynamic Economic Dispatch is proposed. The algorithm maintains the essential unit ramp rate constraint, along with all other necessary constraints, not only for the time horizon of operation (24 h), but it preserves these constraints through the transaction period to the next time horizon (next day) in order to avoid the discontinuity of the power system operation. The Dynamic Economic and Emission Dispatch problem (DEED) is also considered. The load balance constraints, operating limits, valve-point loading and network losses are included in the models of both DED and DEED. The numerical results clarify the significance of the improved algorithm and verify its performance.

Chance-Constrained Guidance With Non-Convex Constraints

Science.gov (United States)

Ono, Masahiro

2011-01-01

Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of

Optimal Stopping with Information Constraint

International Nuclear Information System (INIS)

Lempa, Jukka

2012-01-01

We study the optimal stopping problem proposed by Dupuis and Wang (Adv. Appl. Probab. 34:141–157, 2002). In this maximization problem of the expected present value of the exercise payoff, the underlying dynamics follow a linear diffusion. The decision maker is not allowed to stop at any time she chooses but rather on the jump times of an independent Poisson process. Dupuis and Wang (Adv. Appl. Probab. 34:141–157, 2002), solve this problem in the case where the underlying is a geometric Brownian motion and the payoff function is of American call option type. In the current study, we propose a mild set of conditions (covering the setup of Dupuis and Wang in Adv. Appl. Probab. 34:141–157, 2002) on both the underlying and the payoff and build and use a Markovian apparatus based on the Bellman principle of optimality to solve the problem under these conditions. We also discuss the interpretation of this model as optimal timing of an irreversible investment decision under an exogenous information constraint.

Pengaruh Customer Experience Quality Terhadap Customer Satisfaction & Customer Loyalty Di Kafe Excelso Tunjungan Plaza Surabaya: Perspektif B2C

OpenAIRE

Senjaya, Vivie

2013-01-01

This study discusses about the quality of the customer experience, which is thought to affect customer satisfaction at Cafe Excelso Tunjungan Plaza Surabaya. In this study, the variable of the customer experience quality is measured through the dimensions of accessibility, competence, customer recognition, helpfulness, personalization, problem solving, promise fulfillment, and value for time. Each of these dimensions will be partially tested how it affects customer satisfaction and customer l...

Big bang nucleosynthesis constraints on bulk neutrinos

International Nuclear Information System (INIS)

Goh, H.S.; Mohapatra, R.N.

2002-01-01

We examine the constraints imposed by the requirement of successful nucleosynthesis on models with one large extra hidden space dimension and a single bulk neutrino residing in this dimension. We solve the Boltzmann kinetic equation for the thermal distribution of the Kaluza-Klein modes and evaluate their contribution to the energy density at the big bang nucleosynthesis epoch to constrain the size of the extra dimension R -1 ≡μ and the parameter sin 2 2θ which characterizes the mixing between the active and bulk neutrinos

Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm

Directory of Open Access Journals (Sweden)

M. Balasubbareddy

2015-12-01

Full Text Available A novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, emission, and total power losses as objectives. The proposed method is a hybridization of the conventional cuckoo search algorithm and arithmetic crossover operations. Thus, the non-linear, non-convex objective function can be solved under practical constraints. The effectiveness of the proposed algorithm is analyzed for various cases to illustrate the effect of practical constraints on the objectives' optimization. Two and three objective multi-objective optimization problems are formulated and solved using the proposed non-dominated sorting-based hybrid cuckoo search algorithm. The effectiveness of the proposed method in confining the Pareto front solutions in the solution region is analyzed. The results for single and multi-objective optimization problems are physically interpreted on standard test functions as well as the IEEE-30 bus test system with supporting numerical and graphical results and also validated against existing methods.

Core Self-Evaluations, life satisfaction, and sport satisfaction

OpenAIRE

Antón Aluja

2014-01-01

We investigated the association between Core Self-Evaluations (CSE) and life and sport satisfaction to assess whether the Core Self-Evaluations scale was a better predictor of life satisfaction or sport satisfaction. The study included three hundred and thirteen athletes (231 men and 82 women; age range to 47 years (Mage=22.9 years, SDage=5.9 years)). Participants completed the French language version of the CSE scale, the Satisfaction with Life Scale, and the Satisfaction with Sport Scale. A...

Relationship of Life Satisfaction and Job Satisfaction among Pakistani Army Soldiers

Directory of Open Access Journals (Sweden)

Summaira Naz

2015-03-01

Full Text Available The present study had two main objectives; first, to discover the relationships between job satisfaction and life satisfaction in Pakistani army soldiers, second, to find out the age, salary, marital status, and education differences on job satisfaction and life satisfaction in Pakistani army soldiers. In the present study two questionnaires; Job Satisfaction Scale JSS (Macdonald & Maclntyre, 1997 and Satisfaction With Life Scale (Diener, et al., 1985; were administered to a sample (N=400 along with a demographic sheet. The results of the study revealed a significant positive correlation between job satisfaction and life satisfaction of Pakistani army soldiers. The findings of the study also showed a significant age, education, salary, and marital status differences in job satisfaction and life satisfaction. Age, marital status, and salary variables had positive correlation with job satisfaction and life satisfaction but education had a negative association with job satisfaction and life satisfaction

Job stress and job satisfaction: home care workers in a consumer-directed model of care.

Science.gov (United States)

Delp, Linda; Wallace, Steven P; Geiger-Brown, Jeanne; Muntaner, Carles

2010-08-01

To investigate determinants of job satisfaction among home care workers in a consumer-directed model. Analysis of data collected from telephone interviews with 1,614 Los Angeles home care workers on the state payroll in 2003. Multivariate logistic regression analysis was used to determine the odds of job satisfaction using job stress model domains of demands, control, and support. Abuse from consumers, unpaid overtime hours, and caring for more than one consumer as well as work-health demands predict less satisfaction. Some physical and emotional demands of the dyadic care relationship are unexpectedly associated with greater job satisfaction. Social support and control, indicated by job security and union involvement, have a direct positive effect on job satisfaction. Policies that enhance the relational component of care may improve workers' ability to transform the demands of their job into dignified and satisfying labor. Adequate benefits and sufficient authorized hours of care can minimize the stress of unpaid overtime work, caring for multiple consumers, job insecurity, and the financial constraints to seeking health care. Results have implications for the structure of consumer-directed models of care and efforts to retain long-term care workers.

Solving Assembly Sequence Planning using Angle Modulated Simulated Kalman Filter

Science.gov (United States)

Mustapa, Ainizar; Yusof, Zulkifli Md.; Adam, Asrul; Muhammad, Badaruddin; Ibrahim, Zuwairie

2018-03-01

This paper presents an implementation of Simulated Kalman Filter (SKF) algorithm for optimizing an Assembly Sequence Planning (ASP) problem. The SKF search strategy contains three simple steps; predict-measure-estimate. The main objective of the ASP is to determine the sequence of component installation to shorten assembly time or save assembly costs. Initially, permutation sequence is generated to represent each agent. Each agent is then subjected to a precedence matrix constraint to produce feasible assembly sequence. Next, the Angle Modulated SKF (AMSKF) is proposed for solving ASP problem. The main idea of the angle modulated approach in solving combinatorial optimization problem is to use a function, g(x), to create a continuous signal. The performance of the proposed AMSKF is compared against previous works in solving ASP by applying BGSA, BPSO, and MSPSO. Using a case study of ASP, the results show that AMSKF outperformed all the algorithms in obtaining the best solution.

Infrared Constraint on Ultraviolet Theories

Energy Technology Data Exchange (ETDEWEB)

Tsai, Yuhsin [Cornell Univ., Ithaca, NY (United States)

2012-08-01

While our current paradigm of particle physics, the Standard Model (SM), has been extremely successful at explaining experiments, it is theoretically incomplete and must be embedded into a larger framework. In this thesis, we review the main motivations for theories beyond the SM (BSM) and the ways such theories can be constrained using low energy physics. The hierarchy problem, neutrino mass and the existence of dark matter (DM) are the main reasons why the SM is incomplete . Two of the most plausible theories that may solve the hierarchy problem are the Randall-Sundrum (RS) models and supersymmetry (SUSY). RS models usually suffer from strong flavor constraints, while SUSY models produce extra degrees of freedom that need to be hidden from current experiments. To show the importance of infrared (IR) physics constraints, we discuss the flavor bounds on the anarchic RS model in both the lepton and quark sectors. For SUSY models, we discuss the difficulties in obtaining a phenomenologically allowed gaugino mass, its relation to R-symmetry breaking, and how to build a model that avoids this problem. For the neutrino mass problem, we discuss the idea of generating small neutrino masses using compositeness. By requiring successful leptogenesis and the existence of warm dark matter (WDM), we can set various constraints on the hidden composite sector. Finally, to give an example of model independent bounds from collider experiments, we show how to constrain the DM–SM particle interactions using collider results with an effective coupling description.

Employee satisfaction and employee retention: catalysts to patient satisfaction.

Science.gov (United States)

Collins, Kevin S; Collins, Sandra K; McKinnies, Richard; Jensen, Steven

2008-01-01

Over the last few years, most health care facilities have become intensely aware of the need to increase patient satisfaction. However, with today's more consumer-driven market, this can be a daunting task for even the most experienced health care manager. Recent studies indicate that focusing on employee satisfaction and subsequent employee retention may be strong catalysts to patient satisfaction. This study offers a review of how employee satisfaction and retention correlate with patient satisfaction and also examines the current ways health care organizations are focusing on employee satisfaction and retention.

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...

Comparison of a constraint directed search to a genetic algorithm in a scheduling application

International Nuclear Information System (INIS)

Abbott, L.

1993-01-01

Scheduling plutonium containers for blending is a time-intensive operation. Several constraints must be taken into account; including the number of containers in a dissolver run, the size of each dissolver run, and the size and target purity of the blended mixture formed from these runs. Two types of algorithms have been used to solve this problem: a constraint directed search and a genetic algorithm. This paper discusses the implementation of these two different approaches to the problem and the strengths and weaknesses of each algorithm

Content validity and satisfaction with a caregiver-integrated web-based rehabilitation intervention for persons with stroke.

Science.gov (United States)

Blanton, Sarah; Dunbar, Sandra; Clark, Patricia C

2018-04-01

Background Family members provide valuable contributions during rehabilitation after stroke, but frequently report higher incidences of burden, depression, and social isolation during caregiving. Thus, effective interventions to reduce stroke impact on the family are needed. Objectives To evaluate the content validity and satisfaction of a caregiver-focused web-based intervention designed to improve stroke survivor physical function while reducing caregiver negative outcomes. Methods Caregivers of individuals with stroke (N = 6) and expert rehabilitation researchers (N = 4) were presented with a novel, web-based intervention (CARE-CITE) designed to foster problem-solving and skill-building while facilitating caregiver involvement during constraint-induced movement therapy. Caregivers rated CARE-CITE for usefulness, ease of use, acceptability, and time to complete. Rehabilitation experts evaluated content for accuracy, feasibility, acceptability, problem relevance and ease of use. Ratings were assessed using a five-point Likert-type response scales (1 = strongly disagree to 5 = strongly agree). Results On average, all caregivers agreed or strongly agreed that the modules were useful (4.42), easy to use (4.60), and acceptable (4.41). Mean total satisfaction score was 4.45, and average review time was 15 min per module. Expert reviewers agreed or strongly agreed that each module was accurate (4.95), feasible (4.8), easy to use (4.86), acceptable (4.96), and had appropriate problem relevance (4.65). Conclusions The CARE-CITE intervention may be a viable program for caregivers of patients with stroke. Currently a pilot study is underway to evaluate the impact of the intervention on caregiver mental health, family conflict around stroke recovery and stroke survivor upper extremity function.

Model-based verification method for solving the parameter uncertainty in the train control system

International Nuclear Information System (INIS)

Cheng, Ruijun; Zhou, Jin; Chen, Dewang; Song, Yongduan

2016-01-01

This paper presents a parameter analysis method to solve the parameter uncertainty problem for hybrid system and explore the correlation of key parameters for distributed control system. For improving the reusability of control model, the proposed approach provides the support for obtaining the constraint sets of all uncertain parameters in the abstract linear hybrid automata (LHA) model when satisfying the safety requirements of the train control system. Then, in order to solve the state space explosion problem, the online verification method is proposed to monitor the operating status of high-speed trains online because of the real-time property of the train control system. Furthermore, we construct the LHA formal models of train tracking model and movement authority (MA) generation process as cases to illustrate the effectiveness and efficiency of the proposed method. In the first case, we obtain the constraint sets of uncertain parameters to avoid collision between trains. In the second case, the correlation of position report cycle and MA generation cycle is analyzed under both the normal and the abnormal condition influenced by packet-loss factor. Finally, considering stochastic characterization of time distributions and real-time feature of moving block control system, the transient probabilities of wireless communication process are obtained by stochastic time petri nets. - Highlights: • We solve the parameters uncertainty problem by using model-based method. • We acquire the parameter constraint sets by verifying linear hybrid automata models. • Online verification algorithms are designed to monitor the high-speed trains. • We analyze the correlation of key parameters and uncritical parameters. • The transient probabilities are obtained by using reliability analysis.

Analisa Pengaruh Customer Experience Quality Terhadap Customer Satisfaction Di Hotel Bintang 3 Surabaya

OpenAIRE

Njoto, Mellisa Oktaviani; Tjahyadi, Nency Lifia; Aprillia, Adriana

2016-01-01

Customer experience quality merupakan penilaian yang dirasakan konsumen tentang keunggulan atau superioritas dari pengalaman yang didapatkan oleh konsumen. Dalam penelitian kali ini, peneliti menetapkan customer experience quality sebagai variabel yang mempengaruhi customer satisfaction. Customer experience quality memiliki 8 dimensi, yaitu helpfulness, value for time, customer recognition, promise fulfillment, problem solving, personalization, competence, dan accessibility. Penelitian ini be...

Working with Manchester triage -- job satisfaction in nursing.

Science.gov (United States)

Forsgren, Susanne; Forsman, Berit; Carlström, Eric D

2009-10-01

This article covers nurses' job satisfaction during triage at emergency departments in Western Sweden. Data was collected from 74 triage nurses using a questionnaire containing 37 short form open questions. The answers were analyzed descriptively and by measuring the covariance. The open questions were analyzed by content analysis. The results showed a high degree of job satisfaction (88%). Triage as a method, the interesting nature of the work, and a certain freedom in connection with the triage tasks contributed to job satisfaction (R(2) = 0.40). The nurses found their work interesting and stimulating, although some reported job dissatisfaction due to a heavy workload and lack of competence. Most of the nurses thought that Manchester triage (MTS) was a clear and straightforward method but in need of development. The rational modelling structure by which the triage method is constructed is unable to distinguish all the parameters that an experienced nurse takes into account. When the model is allowed to take precedence over experience, it can be of hindrance and contribute to certain estimates not corresponding with the patient's needs. The participants requested regular exercises solving and discussing patient scenarios. They also wanted to participate on a regular basis in the development of the instrument.

New constraints for canonical general relativity

International Nuclear Information System (INIS)

Reisenberger, M.P.

1995-01-01

Ashtekar's canonical theory of classical complex Euclidean GR (no Lorentzian reality conditions) is found to be invariant under the full algebra of infinitesimal 4-diffeomorphisms, but non-invariant under some finite proper 4-diffeos when the densitized dreibein, E a i , is degenerate. The breakdown of 4-diffeo invariance appears to be due to the inability of the Ashtekar Hamiltonian to generate births and deaths of E flux loops (leaving open the possibility that a new 'causality condition' forbidding the birth of flux loops might justify the non-invariance of the theory).A fully 4-diffeo invariant canonical theory in Ashtekar's variables, derived from Plebanski's action, is found to have constraints that are stronger than Ashtekar's for rank E< 2. The corresponding Hamiltonian generates births and deaths of E flux loops.It is argued that this implies a finite amplitude for births and deaths of loops in the physical states of quantum GR in the loop representation, thus modifying this (partly defined) theory substantially.Some of the new constraints are second class, leading to difficulties in quantization in the connection representation. This problem might be overcome in a very nice way by transforming to the classical loop variables, or the 'Faraday line' variables of Newman and Rovelli, and then solving the offending constraints.Note that, though motivated by quantum considerations, the present paper is classical in substance. (orig.)

Efficient Solution of a Class of Quantified Constraints with Quantifier Prefix Exists-Forall

Czech Academy of Sciences Publication Activity Database

Hladík, M.; Ratschan, Stefan

2014-01-01

Roč. 8, 3-4 (2014), s. 329-340 ISSN 1661-8289 R&D Projects: GA ČR GCP202/12/J060 Grant - others:GA ČR(CZ) GA13-10660S Institutional support: RVO:67985807 Keywords : constraint solving * decision procedures * interval computation Subject RIV: IN - Informatics, Computer Sci ence

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

Science.gov (United States)

Luo, Yabo; Waden, Yongo P.

2017-06-01

Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

Relationship of Life Satisfaction and Job Satisfaction among Pakistani Army Soldiers

OpenAIRE

Summaira Naz

2015-01-01

The present study had two main objectives; first, to discover the relationships between job satisfaction and life satisfaction in Pakistani army soldiers, second, to find out the age, salary, marital status, and education differences on job satisfaction and life satisfaction in Pakistani army soldiers. In the present study two questionnaires; Job Satisfaction Scale JSS (Macdonald & Maclntyre, 1997) and Satisfaction With Life Scale (Diener, ...

Serious Leisure and People with Orthopedic Impairment: Benefits and Constraints

Directory of Open Access Journals (Sweden)

Manolya AKSATAN

2017-12-01

Full Text Available There are many people around the world who have different types of disabilities. Understanding their needs is the first step of developing policies to increase their quality of life and satisfaction. Leisure is an essential need of disabled people and it plays an important role in disabled people’s lives. The purpose of this study is to gain a deep understanding on the serious leisure activities of people with orthopedic impairment, and also both benefits and constraints involved with serious leisure. Therefore, semi-structured in-depth interviews were conducted with 17 people who have orthopedic impairment. The data collected through interviews was analyzed by using a coding process. Findings of the study indicate that people with orthopedic impairment pursue many leisure activities. The research revealed that the participants were aware of significant individual and community benefits of serious leisure activities. Although the benefits of leisure for private and community life are obvious for people with orthopedic impairment, it is not always easy for them to pursue serious leisure activities. Disabled people recognize that there are many constraints involved with serious leisure. Based on the findings, these constraints are explained as psychological factors, family support, level of orthopedic impairment, community awareness and environmental factors, work and income.

Survey of pay satisfaction, job satisfaction and employee turnover in ...

African Journals Online (AJOL)

Survey of pay satisfaction, job satisfaction and employee turnover in selected business organisations in Lagos, Nigeria. ... Global Journal of Social Sciences ... The study was an attempt at investigating the relatedness of pay satisfaction, job satisfaction and employee turnover in business organizations in Lagos Nigeria.

Role Overload, Job Satisfaction, Leisure Satisfaction, and Psychological Health among Employed Women

Science.gov (United States)

Pearson, Quinn M.

2008-01-01

Role overload, job satisfaction, leisure satisfaction, and psychological health were measured for 155 women who were employed full time. Role overload was negatively correlated with psychological health, job satisfaction, and leisure satisfaction. Job satisfaction and leisure satisfaction were positively correlated with psychological health.…

Design and Application of Interactive Simulations in Problem-Solving in University-Level Physics Education

Science.gov (United States)

Ceberio, Mikel; Almudí, José Manuel; Franco, Ángel

2016-08-01

In recent years, interactive computer simulations have been progressively integrated in the teaching of the sciences and have contributed significant improvements in the teaching-learning process. Practicing problem-solving is a key factor in science and engineering education. The aim of this study was to design simulation-based problem-solving teaching materials and assess their effectiveness in improving students' ability to solve problems in university-level physics. Firstly, we analyze the effect of using simulation-based materials in the development of students' skills in employing procedures that are typically used in the scientific method of problem-solving. We found that a significant percentage of the experimental students used expert-type scientific procedures such as qualitative analysis of the problem, making hypotheses, and analysis of results. At the end of the course, only a minority of the students persisted with habits based solely on mathematical equations. Secondly, we compare the effectiveness in terms of problem-solving of the experimental group students with the students who are taught conventionally. We found that the implementation of the problem-solving strategy improved experimental students' results regarding obtaining a correct solution from the academic point of view, in standard textbook problems. Thirdly, we explore students' satisfaction with simulation-based problem-solving teaching materials and we found that the majority appear to be satisfied with the methodology proposed and took on a favorable attitude to learning problem-solving. The research was carried out among first-year Engineering Degree students.

Bin-packing problems with load balancing and stability constraints

DEFF Research Database (Denmark)

Trivella, Alessio; Pisinger, David

apper in a wide range of disciplines, including transportation and logistics, computer science, engineering, economics and manufacturing. The problem is well-known to be N P-hard and difficult to solve in practice, especially when dealing with the multi-dimensional cases. Closely connected to the BPP...... realistic constraints related to e.g. load balancing, cargo stability and weight limits, in the multi-dimensional BPP. The BPP poses additional challenges compared to the CLP due to the supplementary objective of minimizing the number of bins. In particular, in section 2 we discuss how to integrate bin......-packing and load balancing of items. The problem has only been considered in the literature in simplified versions, e.g. balancing a single bin or introducing a feasible region for the barycenter. In section 3 we generalize the problem to handle cargo stability and weight constraints....

A Problem Solving Intervention for hospice caregivers: a pilot study.

Science.gov (United States)

Demiris, George; Oliver, Debra Parker; Washington, Karla; Fruehling, Lynne Thomas; Haggarty-Robbins, Donna; Doorenbos, Ardith; Wechkin, Hope; Berry, Donna

2010-08-01

The Problem Solving Intervention (PSI) is a structured, cognitive-behavioral intervention that provides people with problem-solving coping skills to help them face major negative life events and daily challenges. PSI has been applied to numerous settings but remains largely unexplored in the hospice setting. The aim of this pilot study was to demonstrate the feasibility of PSI targeting informal caregivers of hospice patients. We enrolled hospice caregivers who were receiving outpatient services from two hospice agencies. The intervention included three visits by a research team member. The agenda for each visit was informed by the problem-solving theoretical framework and was customized based on the most pressing problems identified by the caregivers. We enrolled 29 caregivers. Patient's pain was the most frequently identified problem. On average, caregivers reported a higher quality of life and lower level of anxiety postintervention than at baseline. An examination of the caregiver reaction assessment showed an increase of positive esteem average and a decrease of the average value of lack of family support, impact on finances, impact on schedules, and on health. After completing the intervention, caregivers reported lower levels of anxiety, improved problem solving skills, and a reduced negative impact of caregiving. Furthermore, caregivers reported high levels of satisfaction with the intervention, perceiving it as a platform to articulate their challenges and develop a plan to address them. Findings demonstrate the value of problem solving as a psycho-educational intervention in the hospice setting and call for further research in this area.

Patient satisfaction

Directory of Open Access Journals (Sweden)

Bhanu Prakash

2010-01-01

Full Text Available Patient satisfaction is an important and commonly used indicator for measuring the quality in health care. Patient satisfaction affects clinical outcomes, patient retention, and medical malpractice claims. It affects the timely, efficient, and patient-centered delivery of quality health care. Patient satisfaction is thus a proxy but a very effective indicator to measure the success of doctors and hospitals. This article discusses as to how to ensure patient satisfaction in dermatological practice.

Patient satisfaction.

Science.gov (United States)

Prakash, Bhanu

2010-09-01

Patient satisfaction is an important and commonly used indicator for measuring the quality in health care. Patient satisfaction affects clinical outcomes, patient retention, and medical malpractice claims. It affects the timely, efficient, and patient-centered delivery of quality health care. Patient satisfaction is thus a proxy but a very effective indicator to measure the success of doctors and hospitals. This article discusses as to how to ensure patient satisfaction in dermatological practice.

A column generation approach for solving the patient admission scheduling problem

DEFF Research Database (Denmark)

Range, Troels Martin; Lusby, Richard Martin; Larsen, Jesper

2014-01-01

, different variants of this problem. In this paper we consider one such variant and propose an optimization-based heuristic building on branch-and-bound, column generation, and dynamic constraint aggregation to solve it. We achieve tighter lower bounds than previously reported in the literature and......, in addition, we are able to produce new best known solutions for five out of twelve instances from a publicly available repository. © 2013 Elsevier B.V. All rights reserved....

Nurse Leadership Style, Nurse Satisfaction, and Patient Satisfaction: A Systematic Review.

Science.gov (United States)

McCay, Rebecca; Lyles, Annmarie A; Larkey, Linda

2017-12-20

The purpose of this systematic review was to synthesize current evidence on nursing leadership styles, nurse satisfaction, and patient satisfaction. Results suggest that relational leadership traits contribute to greater nurse satisfaction whereas task-oriented styles may decrease nurse satisfaction. Minimal information for the connection between nursing leadership and patient satisfaction was found.

Healthcare workers satisfaction and patient satisfaction – where is the linkage?

OpenAIRE

Janicijevic, I; Seke, K; Djokovic, A; Filipovic, T

2013-01-01

Background: This study aims to assess at what level healthcare worker satisfaction affects patient satisfaction, as well as which elements of healthcare worker satisfaction affect health service quality and patient satisfaction.

A constraint logic programming approach to associate 1D and 3D structural components for large protein complexes.

Science.gov (United States)

Dal Palù, Alessandro; Pontelli, Enrico; He, Jing; Lu, Yonggang

2007-01-01

The paper describes a novel framework, constructed using Constraint Logic Programming (CLP) and parallelism, to determine the association between parts of the primary sequence of a protein and alpha-helices extracted from 3D low-resolution descriptions of large protein complexes. The association is determined by extracting constraints from the 3D information, regarding length, relative position and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. Parallelism is employed to enhance performance on large proteins. The framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.

Romantic Relationship Satisfaction Moderates the Etiology of Adult Personality

Science.gov (United States)

South, Susan C.; Krueger, Robert F.; Elkins, Irene; Iacono, William G.; McGue, Matt

2015-01-01

The heritability of major normative domains of personality is well-established, with approximately half the proportion of variance attributed to genetic differences. In the current study, we examine the possibility of gene x environment interaction (GxE) for adult personality using the environmental context of intimate romantic relationship functioning. Personality and relationship satisfaction are significantly correlated phenotypically, but to date no research has examined how the genetic and environmental components of variance for personality differ as a function of romantic relationship satisfaction. Given the importance of personality for myriad outcomes from work productivity to psychopathology, it is vital to identify variables present in adulthood that may affect the etiology of personality. In the current study, quantitative models of GxE were used to determine whether the genetic and environmental influences on personality differ as a function of relationship satisfaction. We drew from a sample of now-adult twins followed longitudinally from adolescence through age 29. All participants completed the Multidimensional Personality Questionnaire (MPQ) and an abbreviated version of the Dyadic Adjustment Scale (DAS). Biometric moderation was found for eight of the eleven MPQ scales examined: Well-Being, Social Potency, Negative Emotionality, Alienation, Aggression, Constraint, Traditionalism, and Absorption. The pattern of findings differed, suggesting that the ways in which relationship quality moderates the etiology of personality may depend on the personality trait. PMID:26581694

Job satisfaction

OpenAIRE

PODROUŽKOVÁ, Lucie

2013-01-01

Bachelor thesis deals with job satisfaction. It is often given to a context with the attitude to work which is very much connected to job satisfaction. Thesis summarises all the pieces of information about job satisfacion, factors that affect it negatively and positively, interconnection of work satisfaction and work motivation, work behaviour and performance of workers, relationship of a man and work and at last general job satisfaction and its individual aspects. In the thesis I shortly pay...

Registered nurse job satisfaction and satisfaction with the professional practice model.

Science.gov (United States)

McGlynn, Karen; Griffin, Mary Quinn; Donahue, Moreen; Fitzpatrick, Joyce J

2012-03-01

This paper describes the initial assessment of job satisfaction and satisfaction with the professional practice environment of registered nurses working on units where a professional practice model was implemented and the relationship between these two variables. The nursing shortage has been linked to overall job satisfaction and specifically to nurses' satisfaction with the professional practice environment. Initiatives to increase retention and recruitment and decrease turnover have been linked to work satisfaction among nurses. A descriptive, cross-sectional design was used with participants (N = 101) from four patient care units; this represented a 55% response rate. The nurses were moderately satisfied with the professional practice environment but had overall low job satisfaction. There was a significant negative relationship between overall work satisfaction and satisfaction with the professional practice environment (P job satisfaction that were not being met. Thus, the nurses may have become more knowledgeable about the potential needs in these areas. Nurse managers and leaders must recognize that job satisfaction consists of many dimensions, and each of these dimensions is important to nurse retention. Implementation of a professional practice model may heighten awareness of the missing components within a practice environment and lead to decreased overall satisfaction. A broader understanding of characteristics associated with increased satisfaction may aid in development of organizational change necessary to retain and attract nurses. © 2012 Blackwell Publishing Ltd.

Solving Multi-Resource Constrained Project Scheduling Problem using Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Hsiang-Hsi Huang

2015-01-01

Full Text Available This paper applied Ant Colony Optimization (ACO to develop a resource constraints scheduling model to achieve the resource allocation optimization and the shortest completion time of a project under resource constraints and the activities precedence requirement for projects. Resource leveling is also discussed and has to be achieved under the resource allocation optimization in this research. Testing cases and examples adopted from the international test bank were studied for verifying the effectiveness of the proposed model. The results showed that the solutions of different cases all have a better performance within a reasonable time. These can be obtained through ACO algorithm under the same constrained conditions. A program was written for the proposed model that is able to automatically produce the project resource requirement figure after the project duration is solved.

Construct of Dialysis Employee Satisfaction: Acquiring Satisfaction Factors and Their Contributions.

Science.gov (United States)

Gu, Xiuzhu; Itoh, Kenji

2015-10-01

We developed a construct of dialysis employees' satisfaction as an assessment framework and identified the crucial factors that contribute to overall job satisfaction. We also seek to capture some important characteristics of dialysis professionals' job satisfaction/dissatisfaction in Japan. A questionnaire was developed, including 35 facet-specific job-related satisfaction and 10 general satisfaction items in closed-ended questions. A questionnaire-based survey was conducted between August and October 2013. A total of 799 valid responses (87% of response rate) were collected from 46 physicians, 470 nurses and 251 technologists in the dialysis department of 43 facilities in Japan. Five satisfaction factors were derived by applying principal component analysis with 61% of cumulative variance accounted for. Physicians, nurses and technologists in the dialysis department shared a similar trend of job satisfaction that they were more satisfied with leadership, and communication and teamwork among the five factors, whereas their satisfaction level was relatively low with salary and welfare conditions. Physicians expressed the strongest satisfaction with any factor while nurses were the least satisfied. Nurses' and technologists' overall job satisfaction was mostly determined by satisfaction with self-actualization, and work demands and workload. A five-factor construct of dialysis employee satisfaction was identified. Overall job satisfaction of dialysis nurses and technologists were not overly high in Japan, and this seems to be caused by their relatively low satisfaction with self-actualization and with work demands and workload. Therefore, it is suggested that their work conditions and environment must be improved to support their self-actualization and to reduce their workload. © 2015 The Authors. Therapeutic Apheresis and Dialysis © 2015 International Society for Apheresis.

Constraint Differentiation

DEFF Research Database (Denmark)

Mödersheim, Sebastian Alexander; Basin, David; Viganò, Luca

2010-01-01

We introduce constraint differentiation, a powerful technique for reducing search when model-checking security protocols using constraint-based methods. Constraint differentiation works by eliminating certain kinds of redundancies that arise in the search space when using constraints to represent...... results show that constraint differentiation substantially reduces search and considerably improves the performance of OFMC, enabling its application to a wider class of problems....

Optimal Multiuser Zero Forcing with Per-Antenna Power Constraints for Network MIMO Coordination

Directory of Open Access Journals (Sweden)

Kaviani Saeed

2011-01-01

Full Text Available We consider a multicell multiple-input multiple-output (MIMO coordinated downlink transmission, also known as network MIMO, under per-antenna power constraints. We investigate a simple multiuser zero-forcing (ZF linear precoding technique known as block diagonalization (BD for network MIMO. The optimal form of BD with per-antenna power constraints is proposed. It involves a novel approach of optimizing the precoding matrices over the entire null space of other users' transmissions. An iterative gradient descent method is derived by solving the dual of the throughput maximization problem, which finds the optimal precoding matrices globally and efficiently. The comprehensive simulations illustrate several network MIMO coordination advantages when the optimal BD scheme is used. Its achievable throughput is compared with the capacity region obtained through the recently established duality concept under per-antenna power constraints.

A solid criterion based on strict LMI without invoking equality constraint for stabilization of continuous singular systems.

Science.gov (United States)

Zhang, Xuefeng; Chen, YangQuan

2017-11-01

The paper considers the stabilization issue of linear continuous singular systems by dealing with strict linear matrix inequalities (LMIs) without invoking equality constraint and proposes a complete and effective solved LMIs formulation. The criterion is necessary and sufficient condition and can be directly solved the feasible solutions with LMI toolbox and is much more tractable and reliable in numerical simulation than existing results, which involve positive semi-definite LMIs with equality constraints. The most important property of the criterion proposed in the paper is that it can overcome the drawbacks of the invalidity caused by the singularity of Ω=PE T +SQ for stabilization of singular systems. Two counterexamples are presented to avoid the disadvantages of the existing condition of stabilization of continuous singular systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The results of STEM education methods for enhancing critical thinking and problem solving skill in physics the 10th grade level

Science.gov (United States)

Soros, P.; Ponkham, K.; Ekkapim, S.

2018-01-01

This research aimed to: 1) compare the critical think and problem solving skills before and after learning using STEM Education plan, 2) compare student achievement before and after learning about force and laws of motion using STEM Education plan, and 3) the satisfaction of learning by using STEM Education. The sample used were 37 students from grade 10 at Borabu School, Borabu District, Mahasarakham Province, semester 2, Academic year 2016. Tools used in this study consist of: 1) STEM Education plan about the force and laws of motion for grade 10 students of 1 schemes with total of 14 hours, 2) The test of critical think and problem solving skills with multiple-choice type of 5 options and 2 option of 30 items, 3) achievement test on force and laws of motion with multiple-choice of 4 options of 30 items, 4) satisfaction learning with 5 Rating Scale of 20 items. The statistics used in data analysis were percentage, mean, standard deviation, and t-test (Dependent). The results showed that 1) The student with learning using STEM Education plan have score of critical think and problem solving skills on post-test higher than pre-test with statistically significant level .01. 2) The student with learning using STEM Education plan have achievement score on post-test higher than pre-test with statistically significant level of .01. 3) The student'level of satisfaction toward the learning by using STEM Education plan was at a high level (X ¯ = 4.51, S.D=0.56).

Conflict with Mothers-in-Law and Taiwanese Women's Marital Satisfaction: The Moderating Role of Husband Support

Science.gov (United States)

Wu, Tsui-Feng; Yeh, Kuang-Hui; Cross, Susan E.; Larson, Lisa M.; Wang, Yi-Chao; Tsai, Yi-Lin

2010-01-01

This study applies social support theory to the question of whether four types of husband behavior (taking the wife's side, problem solving, ignoring conflict, and taking the mother's side) moderate the association between conflict with the mother-in-law and a Taiwanese woman's marital satisfaction. Data were collected from 125 married Taiwanese…

Impact of Context-Rich, Multifaceted Problems on Students' Attitudes Towards Problem-Solving

Science.gov (United States)

Ogilvie, Craig

2008-04-01

Young scientists and engineers need strong problem-solving skills to enable them to address the broad challenges they will face in their careers. These challenges will likely be ill-defined and open-ended with either unclear goals, insufficient constraints, multiple possible solutions, and different criteria for evaluating solutions so that our young scientists and engineers must be able to make judgments and defend their proposed solutions. In contrast, many students believe that problem-solving is being able to apply set procedures or algorithms to tasks and that their job as students is to master an ever-increasing list of procedures. This gap between students' beliefs and the broader, deeper approaches of experts is a strong barrier to the educational challenge of preparing students to succeed in their future careers. To start to address this gap, we have used multi-faceted, context-rich problems in a sophomore calculus-based physics course. To assess whether there was any change in students' attitudes or beliefs towards problem-solving, students were asked to reflect on their problem-solving at the beginning and at the end of the semester. These reflections were coded as containing one or more problem-solving ideas. The change in students' beliefs will be shown in this talk.

Comparison of AI techniques to solve combined economic emission dispatch problem with line flow constraints

Energy Technology Data Exchange (ETDEWEB)

Jacob Raglend, I. [School of Electrical Sciences, Noorul Islam University, Kumaracoil 629 180 (India); Veeravalli, Sowjanya; Sailaja, Kasanur; Sudheera, B. [School of Electrical Sciences, Vellore Institute of Technology, Vellore 632 004 (India); Kothari, D.P. [FNAE, FNASC, SMIEEE, Vellore Institute of Technology University, Vellore 632 014 (India)

2010-07-15

A comparative study has been made on the solutions obtained using combined economic emission dispatch (CEED) problem considering line flow constraints using different intelligent techniques for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of the paper is to minimize the total production cost of the power generation. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost of generating units. Combined economic emission dispatch (CEED) is obtained by considering both the economic and emission objectives. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. In this paper, intelligent techniques such as genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE) are applied to obtain CEED solutions for the IEEE 30-bus system and 15-unit system. This proposed algorithm introduces an efficient CEED approach that obtains the minimum operating cost satisfying unit, emission and network constraints. The proposed algorithm has been tested on two sample systems viz the IEEE 30-bus system and a 15-unit system. The results obtained by the various artificial intelligent techniques are compared with respect to the solution time, total production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic emission environment. The algorithm and simulation are carried out using Matlab software. (author)

Comparison of AI techniques to solve combined economic emission dispatch problem with line flow constraints

International Nuclear Information System (INIS)

Jacob Raglend, I.; Veeravalli, Sowjanya; Sailaja, Kasanur; Sudheera, B.; Kothari, D.P.

2010-01-01

A comparative study has been made on the solutions obtained using combined economic emission dispatch (CEED) problem considering line flow constraints using different intelligent techniques for the regulated power system to ensure a practical, economical and secure generation schedule. The objective of the paper is to minimize the total production cost of the power generation. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost of generating units. Combined economic emission dispatch (CEED) is obtained by considering both the economic and emission objectives. This bi-objective CEED problem is converted into single objective function using price penalty factor approach. In this paper, intelligent techniques such as genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE) are applied to obtain CEED solutions for the IEEE 30-bus system and 15-unit system. This proposed algorithm introduces an efficient CEED approach that obtains the minimum operating cost satisfying unit, emission and network constraints. The proposed algorithm has been tested on two sample systems viz the IEEE 30-bus system and a 15-unit system. The results obtained by the various artificial intelligent techniques are compared with respect to the solution time, total production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic emission environment. The algorithm and simulation are carried out using Matlab software. (author)

Basic psychological need satisfaction in leisure activities and adolescents' life satisfaction.

Science.gov (United States)

Leversen, Ingrid; Danielsen, Anne G; Birkeland, Marianne S; Samdal, Oddrun

2012-12-01

Participation in leisure activities is an important arena for the positive psychological development of adolescents. The present study set out to examine the relationship between adolescents' satisfaction of the psychological needs for competence, relatedness, and autonomy in their participation in leisure activities and their perceived life satisfaction. The aim was to identify the extent to which satisfaction of the three needs explained the relationship between participation in leisure activities and life satisfaction. These proposed mechanisms were based on previous empirical work and the theoretical frameworks of self-determination theory, and were tested in a nationally representative sample of Norwegian adolescents (N = 3,273) aged 15 and 16 years (51.8 % boys). The structural equation analysis showed that competence and relatedness satisfaction fully mediated the association between participation in activities and life satisfaction. Autonomy satisfaction had a direct positive effect on life satisfaction but did not show any mediation effect. The positive processes of psychological need satisfaction, and especially the need for competence and relatedness, experienced in the leisure activity domain thus seem to be beneficial for adolescents' well-being. These findings add to previous research investigating the positive impact of need satisfaction in other important domains in the lives of children and adolescents.

Freedom as Satisfaction?

DEFF Research Database (Denmark)

Rostbøll, Christian Fogh

2004-01-01

with harmony in one's entire volitional system, Frankfurt may solve the infi nite regress objection but he does so at the cost of ending up with a description of freedom, which comes very close to being identical to his own description of the wanton. Frankfurt's account leaves open the question of whether......This article is a critical assessment of Harry Frankfurt's hierarchical theory of freedom. It spells out and distinguishes several different and irreconcilable conceptions of freedom present in Frankfurt's work. I argue that Frankfurt is ambiguous in his early formulation as to what conception...... of freedom of the will the hierarchical theory builds on, an avoidability or a satisfaction conception. This ambiguity causes problems in his later attempts to respond to the objections of wantonness of second-order desires and of infi nite regress. With his more recent idea of freedom as being satisfi ed...

Short run hydrothermal coordination with network constraints using an interior point method

International Nuclear Information System (INIS)

Lopez Lezama, Jesus Maria; Gallego Pareja, Luis Alfonso; Mejia Giraldo, Diego

2008-01-01

This paper presents a lineal optimization model to solve the hydrothermal coordination problem. The main contribution of this work is the inclusion of the network constraints to the hydrothermal coordination problem and its solution using an interior point method. The proposed model allows working with a system that can be completely hydraulic, thermal or mixed. Results are presented on the IEEE 14 bus test system

The Relationship between Satisfaction with Workplace Training and Overall Job Satisfaction

Science.gov (United States)

Schmidt, Steven W.

2007-01-01

Opportunities for training and development are paramount in decisions regarding employee career choices. Despite the importance, many research studies on job satisfaction do not address satisfaction with workplace training as an element of overall job satisfaction, and many job satisfaction survey instruments do not include a "satisfaction…

Assessing the Effects of Service Quality of Government and Student Satisfaction in Education’s Field

Science.gov (United States)

Purwaningsih, D.

2017-03-01

The aim of the research is to analyze how the service quality of Indonesian government affect student’s satisfaction in the education field. Data collection was conducted in September 2016 through distributing questionnaires to 132 students at private universities in south Tangerang city. Sampling used incidental sampling method, while data analysis is descriptive, qualitative and quantitative, which were analyzed with the Importance Performance Analysis. The survey results revealed that the satisfaction level of the students of South Tangerang good enough to service of the Government in higher education sector with a value of 83.61 using Customer Satisfaction Index (CSI). Nevertheless, there are several factors that should be prioritized for immediate enhanced, namely: government’s ability to respond effectively to solve the problems in the academic world, fairness of the government in providing assistance to both state and private universities and attention of the government to higher education.

A modified artificial bee colony based on chaos theory for solving non-convex emission/economic dispatch

International Nuclear Information System (INIS)

Shayeghi, H.; Ghasemi, A.

2014-01-01

Highlights: • This paper presents a developed multi objective CIABC based on CLS theory for solving EED problem. • The EED problem is formulated as a non-convex multi objective optimization problem. • Considered three test systems to demonstrate its efficiency including practical constrains. • The significant improvement in the results comparing the reported literature. - Abstract: In this paper, a modified ABC based on chaos theory namely CIABC is comprehensively enhanced and effectively applied for solving a multi-objective EED problem to minimize three conflicting objective functions with non-smooth and non-convex generator fuel cost characteristics while satisfying the operation constraints. The proposed method uses a Chaotic Local Search (CLS) to enhance the self searching ability of the original ABC algorithm for finding feasible optimal solutions of the EED problem. Also, many linear and nonlinear constraints, such as generation limits, transmission line loss, security constraints and non-smooth cost functions are considered as dynamic operational constraints. Moreover, a method based on fuzzy set theory is employed to extract one of the Pareto-optimal solutions as the best compromise one. The proposed multi objective evolutionary method has been applied to the standard IEEE 30 bus six generators, fourteen generators and 40 thermal generating units, respectively, as small, medium and large test power system. The numerical results obtained with the proposed method based on tables and figures compared with other evolutionary algorithm of scientific literatures. The results regards that the proposed CIABC algorithm surpasses the other available methods in terms of computational efficiency and solution quality

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads......This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... to a significant decrease in makespan compared to the strategy currently implemented....

Calculation of Pareto-optimal solutions to multiple-objective problems using threshold-of-acceptability constraints

Science.gov (United States)

Giesy, D. P.

1978-01-01

A technique is presented for the calculation of Pareto-optimal solutions to a multiple-objective constrained optimization problem by solving a series of single-objective problems. Threshold-of-acceptability constraints are placed on the objective functions at each stage to both limit the area of search and to mathematically guarantee convergence to a Pareto optimum.

Examining Relationships Among Well-being, Leisure Satisfaction, Life Satisfaction, and Happiness

Directory of Open Access Journals (Sweden)

Metin Argan

2018-04-01

Full Text Available Interaction between well-being and happiness has received an increasing interest worldwide due to its positive impact on people’s lives. The aim of this study was to propose a theoretical model to examine the relationships among wellbeing, leisure satisfaction, life satisfaction and happiness. The results from a survey of 1230 respondent in Turkey indicate that there were significant relationships among national well-being, personal well-being, leisure satisfaction, life satisfaction and happiness. The results support the hypothesized relationships, suggesting that well-being as antecedents, directly affecting leisure, life satisfaction and indirectly affecting happiness. Consistent with previous empirical studies, the findings of this study suggest that leisure satisfaction and life satisfaction are the moderators of dimension of happiness, and significantly mediates the effect of national well-being on happiness.

Is the job satisfaction of primary care team members associated with patient satisfaction?

Science.gov (United States)

Goetz, Katja; Campbell, Stephen; Broge, Bjoern; Reuschenbach, Bernd; Wensing, Michel

2011-01-01

Background Previous research has shown a correlation between physician job satisfaction and patient satisfaction with quality of care, but the connection between job satisfaction of other primary care team members and patient satisfaction is yet unclear. Objective To evaluate whether there is an association between patient satisfaction and job satisfaction of the members of patient care teams. Design The study was based on data from the European Practice Assessment and used an observational design. Setting 676 primary care practices in Germany. Participants 47 168 patients, 676 general practitioners (practice principals), 305 physician colleagues (trainees and permanently employed physicians) and 3011 non-physician practice members (nurses, secretaries). Main outcome measures Patient evaluation was measured using the 23-item EUROPEP questionnaire. Job satisfaction was measured using the 10-item Warr–Cook–Wall job satisfaction scale and further items relating to practice structure. Bivariate correlations were applied in which factors of patient satisfaction and practice structure were compared with physicians and non-physicians satisfaction. Results Patient satisfaction correlates positively with the general job satisfaction of the non-physician (r=0.25, ppatient satisfaction was higher than the correlation between satisfaction of physicians and patients. Patients seem to be sensitive to aspects of practice structure. PMID:21262790

Improved differential evolution algorithms for handling economic dispatch optimization with generator constraints

International Nuclear Information System (INIS)

Coelho, Leandro dos Santos; Mariani, Viviana Cocco

2007-01-01

Global optimization based on evolutionary algorithms can be used as the important component for many engineering optimization problems. Evolutionary algorithms have yielded promising results for solving nonlinear, non-differentiable and multi-modal optimization problems in the power systems area. Differential evolution (DE) is a simple and efficient evolutionary algorithm for function optimization over continuous spaces. It has reportedly outperformed search heuristics when tested over both benchmark and real world problems. This paper proposes improved DE algorithms for solving economic load dispatch problems that take into account nonlinear generator features such as ramp rate limits and prohibited operating zones in the power system operation. The DE algorithms and its variants are validated for two test systems consisting of 6 and 15 thermal units. Various DE approaches outperforms other state of the art algorithms reported in the literature in solving load dispatch problems with generator constraints

Localization of a Vehicle: A Dynamic Interval Constraint Satisfaction Problem-Based Approach

Directory of Open Access Journals (Sweden)

Kangni Kueviakoe

2018-01-01

Full Text Available This paper introduces a new interval constraint propagation (ICP approach dealing with the real-time vehicle localization problem. Bayesian methods like extended Kalman filter (EKF are classically used to achieve vehicle localization. ICP is an alternative which provides guaranteed localization results rather than probabilities. Our approach assumes that all models and measurement errors are bounded within known limits without any other hypotheses on the probability distribution. The proposed algorithm uses a low-level consistency algorithm and has been validated with an outdoor vehicle equipped with a GPS receiver, a gyro, and odometers. Results have been compared to EKF and other ICP methods such as hull consistency (HC4 and 3-bound (3B algorithms. Both consistencies of EKF and our algorithm have been experimentally studied.

Back-feed power restoration using distributed constraint optimization in smart distribution grids clustered into microgrids

International Nuclear Information System (INIS)

El-Sharafy, M. Zaki; Farag, Hany E.Z.

2017-01-01

Highlights: •Introducing three types of energy transfer between neighboring microgrids. •Incorporating droop-based power flow model of islanded microgrids in restoration. •Optimizing droop settings of DGs in islanded mode to maximize restored load. •Decomposing restoration into two distributed constraint optimization problems. •Using OPTAPO to solve the formulated problems in a multiagent environment. -- Abstract: In this paper, an optimization problem is formulated for the automatic back-feed service restoration in smart distribution grids. The formulated problem relies on the structure of smart distribution grids, clustered into multi-microgrids, capable of operating in both grid-connected and islanded modes of operation. To that end, three types of power transfer between the neighboring microgrids, during the restoration processes are introduced: load transfer, distributed generation (DG) transfer, and combined load–DG transfer. The formulated optimization problem takes into account the ability of forming new, not predefined islanded microgrids, in the post-restoration configuration, to maximize service restoration. To obviate the need for a central unit, the optimization problem is reformulated, in this work, as a distributed constraint optimization problem, in which the variables and constraints are distributed among automated agents. To reduce the problem complexity, the restoration problem is decomposed into two sequential and interdependent distributed sub-problems: supply adequacy, and optimal reconfiguration. The proposed algorithm adopts the Optimal Asynchronous Partial Overlay (OPTAPO) technique, which is based on the distributed constraint agent search to solve distributed sub-problems in a multi-agent environment. Several case studies have been carried out to evaluate the effectiveness and robustness of the proposed algorithm.

Strict Constraint Feasibility in Analysis and Design of Uncertain Systems

Science.gov (United States)

Crespo, Luis G.; Giesy, Daniel P.; Kenny, Sean P.

2006-01-01

This paper proposes a methodology for the analysis and design optimization of models subject to parametric uncertainty, where hard inequality constraints are present. Hard constraints are those that must be satisfied for all parameter realizations prescribed by the uncertainty model. Emphasis is given to uncertainty models prescribed by norm-bounded perturbations from a nominal parameter value, i.e., hyper-spheres, and by sets of independently bounded uncertain variables, i.e., hyper-rectangles. These models make it possible to consider sets of parameters having comparable as well as dissimilar levels of uncertainty. Two alternative formulations for hyper-rectangular sets are proposed, one based on a transformation of variables and another based on an infinity norm approach. The suite of tools developed enable us to determine if the satisfaction of hard constraints is feasible by identifying critical combinations of uncertain parameters. Since this practice is performed without sampling or partitioning the parameter space, the resulting assessments of robustness are analytically verifiable. Strategies that enable the comparison of the robustness of competing design alternatives, the approximation of the robust design space, and the systematic search for designs with improved robustness characteristics are also proposed. Since the problem formulation is generic and the solution methods only require standard optimization algorithms for their implementation, the tools developed are applicable to a broad range of problems in several disciplines.

Constraints on the braneworld from compact stars

Energy Technology Data Exchange (ETDEWEB)

Felipe, R.G. [Instituto Politecnico de Lisboa, ISEL, Instituto Superior de Engenharia de Lisboa, Lisboa (Portugal); Instituto Superior Tecnico, Universidade de Lisboa, Departamento de Fisica, Centro de Fisica Teorica de Particulas, CFTP, Lisboa (Portugal); Paret, D.M. [Universidad de la Habana, Departamento de Fisica General, Facultad de Fisica, La Habana (Cuba); Martinez, A.P. [Instituto de Cibernetica, Matematica y Fisica (ICIMAF), La Habana (Cuba); Universidad Nacional Autonoma de Mexico, Instituto de Ciencias Nucleares, Mexico, Distrito Federal (Mexico)

2016-06-15

According to the braneworld idea, ordinary matter is confined on a three-dimensional space (brane) that is embedded in a higher-dimensional space-time where gravity propagates. In this work, after reviewing the limits coming from general relativity, finiteness of pressure and causality on the brane, we derive observational constraints on the braneworld parameters from the existence of stable compact stars. The analysis is carried out by solving numerically the brane-modified Tolman-Oppenheimer-Volkoff equations, using different representative equations of state to describe matter in the star interior. The cases of normal dense matter, pure quark matter and hybrid matter are considered. (orig.)

A new algorithm for combined dynamic economic emission dispatch with security constraints

International Nuclear Information System (INIS)

Arul, R.; Velusami, S.; Ravi, G.

2015-01-01

The primary objective of CDEED (combined dynamic economic emission dispatch) problem is to determine the optimal power generation schedule for the online generating units over a time horizon considered and simultaneously minimizing the emission level and satisfying the generators and system constraints. The CDEED problem is bi-objective optimization problem, where generation cost and emission are considered as two competing objective functions. This bi-objective CDEED problem is represented as a single objective optimization problem by assigning different weights for each objective functions. The weights are varied in steps and for each variation one compromise solution are generated and finally fuzzy based selection method is used to select the best compromise solution from the set of compromise solutions obtained. In order to reflect the test systems considered as real power system model, the security constraints are also taken into account. Three new versions of DHS (differential harmony search) algorithms have been proposed to solve the CDEED problems. The feasibility of the proposed algorithms is demonstrated on IEEE-26 and IEEE-39 bus systems. The result obtained by the proposed CSADHS (chaotic self-adaptive differential harmony search) algorithm is found to be better than EP (evolutionary programming), DHS, and the other proposed algorithms in terms of solution quality, convergence speed and computation time. - Highlights: • In this paper, three new algorithms CDHS, SADHS and CSADHS are proposed. • To solve DED with emission, poz's, spinning reserve and security constraints. • Results obtained by the proposed CSADHS algorithm are better than others. • The proposed CSADHS algorithm has fast convergence characteristic than others

Optimal Power Allocation for Downstream xDSL With Per-Modem Total Power Constraints: Broadcast Channel Optimal Spectrum Balancing (BC-OSB)

Science.gov (United States)

Le Nir, Vincent; Moonen, Marc; Verlinden, Jan; Guenach, Mamoun

2009-02-01

Recently, the duality between Multiple Input Multiple Output (MIMO) Multiple Access Channels (MAC) and MIMO Broadcast Channels (BC) has been established under a total power constraint. The same set of rates for MAC can be achieved in BC exploiting the MAC-BC duality formulas while preserving the total power constraint. In this paper, we describe the BC optimal power allo- cation applying this duality in a downstream x-Digital Subscriber Lines (xDSL) context under a total power constraint for all modems over all tones. Then, a new algorithm called BC-Optimal Spectrum Balancing (BC-OSB) is devised for a more realistic power allocation under per-modem total power constraints. The capacity region of the primal BC problem under per-modem total power constraints is found by the dual optimization problem for the BC under per-modem total power constraints which can be rewritten as a dual optimization problem in the MAC by means of a precoder matrix based on the Lagrange multipliers. We show that the duality gap between the two problems is zero. The multi-user power allocation problem has been solved for interference channels and MAC using the OSB algorithm. In this paper we solve the problem of multi-user power allocation for the BC case using the OSB algorithm as well and we derive a computational efficient algorithm that will be referred to as BC-OSB. Simulation results are provided for two VDSL2 scenarios: the first one with Differential-Mode (DM) transmission only and the second one with both DM and Phantom- Mode (PM) transmissions.

An On-Campus Botanical Tour to Promote Student Satisfaction and Learning in a University Level Biodiversity or General Biology Course

Science.gov (United States)

Ratnayaka, Harish H.

2017-01-01

Outdoor, hands-on and experiential learning, as opposed to instruction-based learning in classroom, increases student satisfaction and motivation leading to a deeper understanding of the subject. However, the use of outdoor exercises in undergraduate biology courses is declining due to a variety of constraints. Thus, the goal of this paper is to…

Three-Dimensional Dynamic Topology Optimization with Frequency Constraints Using Composite Exponential Function and ICM Method

Directory of Open Access Journals (Sweden)

Hongling Ye

2015-01-01

Full Text Available The dynamic topology optimization of three-dimensional continuum structures subject to frequency constraints is investigated using Independent Continuous Mapping (ICM design variable fields. The composite exponential function (CEF is selected to be a filter function which recognizes the design variables and to implement the changing process of design variables from “discrete” to “continuous” and back to “discrete.” Explicit formulations of frequency constraints are given based on filter functions, first-order Taylor series expansion. And an improved optimal model is formulated using CEF and the explicit frequency constraints. Dual sequential quadratic programming (DSQP algorithm is used to solve the optimal model. The program is developed on the platform of MSC Patran & Nastran. Finally, numerical examples are given to demonstrate the validity and applicability of the proposed method.

Multicriteria vehicle routing problem solved by artificial immune system

Directory of Open Access Journals (Sweden)

Bogna MRÓWCZYŃSKA

2015-09-01

Full Text Available Vehicles route planning in large transportation companies, where drivers are workers, usually takes place on the basis of experience or intuition of the employees. Because of the cost and environmental protection, it is important to save fuel, thus planning routes in an optimal way. In this article an example of the problem is presented solving delivery vans route planning taking into account the distance and travel time within the constraints of vehicle capacities, restrictions on working time of drivers and having varying degrees of movement. An artificial immune system was used for the calculations.

IMITATOR II: A Tool for Solving the Good Parameters Problem in Timed Automata

Directory of Open Access Journals (Sweden)

Étienne André

2010-10-01

Full Text Available We present here Imitator II, a new version of Imitator, a tool implementing the "inverse method" for parametric timed automata: given a reference valuation of the parameters, it synthesizes a constraint such that, for any valuation satisfying this constraint, the system behaves the same as under the reference valuation in terms of traces, i.e., alternating sequences of locations and actions. Imitator II also implements the "behavioral cartography algorithm", allowing us to solve the following good parameters problem: find a set of valuations within a given bounded parametric domain for which the system behaves well. We present new features and optimizations of the tool, and give results of applications to various examples of asynchronous circuits and communication protocols.

Construct exploit constraint in crash analysis by bypassing canary

Science.gov (United States)

Huang, Ning; Huang, Shuguang; Huang, Hui; Chang, Chao

2017-08-01

Selective symbolic execution is a common program testing technology. Developed on the basis of it, some crash analysis systems are often used to test the fragility of the program by constructing exploit constraints, such as CRAX. From the study of crash analysis based on symbolic execution, this paper find that this technology cannot bypass the canary stack protection mechanisms. This paper makes the improvement uses the API hook in Linux. Experimental results show that the use of API hook can effectively solve the problem that crash analysis cannot bypass the canary protection.

Constraints and Hamiltonian in light-front quantized field theory

International Nuclear Information System (INIS)

Srivastava, P.P.

1993-01-01

Self-consistent hamiltonian formulation of scalar theory on the null plane is constructed and quantized following the Dirac procedure. The theory contains also constraint equations which would give, if solved, to a nonlocal Hamiltonian. In contrast to the equal-time formulation we obtain a different description of the spontaneous symmetry breaking in the continuum and the symmetry generators are found to annihilate the light-front vacuum. Two examples are given where the procedure cannot be applied self-consistently. The corresponding theories are known to be ill-defined from the equal-time quantization. (author)

Satisfaction with life and job satisfaction of employees in Slovenian army

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Tjaša Dimec

2008-12-01

Full Text Available The purpose of this study was to investigate satisfaction with life and job satisfaction in the Slovenian army. For this purpose we used Satisfaction With Life Scale (Diener, Emmons, Larsen, & Griffin, 1985 and Pogačnik's (2003 Job Satisfaction Scale. This research involved 168 employees of the Slovenian army: 68 soldiers, 60 officers, and 40 noncommissioned officers. The results showed that employees in Slovenian army are more satisfied than unsatisfied with their lives. Officers are the most satisfied with their life. We found out that appraisals on job satisfaction are rather low and indicate middle level of job satisfaction. The highest level of work satisfaction was expressed in the area of relations with co-workers. Participants were least satisfied with their salary and other material facilities. Individuals with subordinate co-workers showed higher level of satisfaction with work conditions, possibilities for promotion, salary and other material facilities, and also higher level of satisfaction about informing in the army, possibilities for professional development, independence and autonomy at work, work reputation, creativeness at work and also taking part in decision-making. Analysis of differences showed that officers gave the highest score to indicators of work satisfaction, with exception of independence and autonomy at work, work reputation, and pretentiousness of work. Based on the examination of the actual state, to the level the research was enabling, we identified some necessary changes, improvements or measures for improvement of the recognized weak areas.

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....

THE IMPACTS OF CORPORATE REPUTATION AND SERVICE QUALITY ON CUSTOMER SATISFACTION: A RESEARCH AT SHOPPING MALLS IN ISTANBUL

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Adnan Duygun

2016-08-01

Full Text Available Retailing, with the growing number of Shopping Malls, is a booming sector. The main purpose of this study is to develop and test a model to reveal the influence of corporate reputation and service quality on customer satisfaction in retail sector. The study employs RepTrak scale to measure the corporate reputation and retail service quality scale (RSQS to measure the retail service quality. The results reveal that corporate reputation has no effect on customer satisfaction. Physical appearance and materials, communication and problem solving that factors of retail service quality, are proved to have an effect on customer satisfaction. Moreover, the results exhibit that there ise a significant and positive relationsihip between corporate reputation and retail service quality. The study also makes recomandations and suggestions for further researchs.

A Simulation Model for Measuring Customer Satisfaction through Employee Satisfaction

Science.gov (United States)

Zondiros, Dimitris; Konstantopoulos, Nikolaos; Tomaras, Petros

2007-12-01

Customer satisfaction is defined as a measure of how a firm's product or service performs compared to customer's expectations. It has long been a subject of research due to its importance for measuring marketing and business performance. A lot of models have been developed for its measurement. This paper propose a simulation model using employee satisfaction as one of the most important factors leading to customer satisfaction (the others being expectations and disconfirmation of expectations). Data obtained from a two-year survey in customers of banks in Greece were used. The application of three approaches regarding employee satisfaction resulted in greater customer satisfaction when there is serious effort to keep employees satisfied.

REPAIR SHOP JOB SCHEDULING WITH PARALLEL OPERATORS AND MULTIPLE CONSTRAINTS USING SIMULATED ANNEALING

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N. Shivasankaran

2013-04-01

Full Text Available Scheduling problems are generally treated as NP andash; complete combinatorial optimization problems which is a multi-objective and multi constraint one. Repair shop Job sequencing and operator allocation is one such NP andash; complete problem. For such problems, an efficient technique is required that explores a wide range of solution space. This paper deals with Simulated Annealing Technique, a Meta - heuristic to solve the complex Car Sequencing and Operator Allocation problem in a car repair shop. The algorithm is tested with several constraint settings and the solution quality exceeds the results reported in the literature with high convergence speed and accuracy. This algorithm could be considered as quite effective while other heuristic routine fails.

Goldratt's thinking process applied to the budget constraints of a Texas MHMR facility.

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Taylor, Lloyd J; Churchwell, Lana

2004-01-01

Managers for years have known that the best way to run a business is to constantly be looking for ways to improve the way to do business. The barrier has been the ability to identify and solve the right problems. Eliyahu Goldratt (1992c), in his book The Goal, uses a love story format to illustrate his "Theory of Constraints." In Goldratt's (1994) next book, It's Not Luck, he further illustrates this powerful technique called "The Thinking Process" which is based on the Socratic method, using the "if ... then" reasoning process, The first step is to identify UDEs or undesirable effects within the organization and then use these UDEs to create a Current Reality Tree (CRT) which helps to identify the core problem. Next, use an Evaporating Cloud to come up with ideas and a way to break the constraint. Finally, use the injections in the Evaporating Cloud to create a Future Reality Tree, further validating the idea and making sure it does not create any negative effects. In this article, the "Thinking Process" will be used to identify and solve problems related to the General Medical Department of an MHMR State Hospital.

Satisfaction with nursing education, job satisfaction, and work intentions of new graduate nurses.

Science.gov (United States)

Kenny, Patricia; Reeve, Rebecca; Hall, Jane

2016-01-01

In the context of predictions of future shortages of nurses, retaining new graduate nurses in the nursing workforce is essential to ensure sufficient nurses in the future. This paper investigates the links between satisfaction with nursing education and job satisfaction, and job dissatisfaction and intentions to leave a nursing job. It uses survey data from a cohort study of nursing students recruited through two Australian universities and followed after graduation and workforce entry. Structural equation modeling (SEM) was used to simultaneously estimate the impact of educational satisfaction (work preparation component) on job satisfaction and the impact of job satisfaction on the expectation of leaving the current job. Two job satisfaction sub-scales were identified: 1) work environment satisfaction and 2) work hours and wages satisfaction. Work preparation satisfaction was significantly and positively associated with both job satisfaction scales but only work environment satisfaction was significantly associated with the expectation to stay in the job; a one standard deviation increase in work environment satisfaction was associated with a 13.5 percentage point reduction in the probability of expecting to leave. The estimated effect of satisfaction with education on expecting to leave, occurring indirectly through job satisfaction, was small (reducing the probability by less than 3 percentage points for a 1 point increase in work preparation satisfaction). Participating in a graduate transition program had the largest effect, reducing the probability of expecting to leave by 26 percentage points, on average. The study results suggest policies which focus on improving satisfaction with the work environment would be more effective at retaining nurses early in their career than improvements to conditions such as work hours and wages. Investment in new graduate transition programs would potentially have the largest impact on retention. Copyright © 2015 Elsevier

F John's stability conditions versus A Carasso's SECB constraint for backward parabolic problems

International Nuclear Information System (INIS)

Lee, Jinwoo; Sheen, Dongwoo

2009-01-01

In order to solve backward parabolic problems John (1960 Commun. Pure. Appl. Math.13 551–85) introduced the two constraints ||u(T)|| ≤ M and ||u(0) − g|| ≤ δ where u(t) satisfies the backward heat equation for t in (0, T) with the initial data u(0). The slow evolution from the continuation boundary (SECB) constraint was introduced by Carasso (1994 SIAM J. Numer. Anal. 31 1535–57) to attain continuous dependence on data for backward parabolic problems even at the continuation boundary t = T. The additional 'SECB constraint' guarantees a significant improvement in stability up to t = T. In this paper, we prove that the same type of stability can be obtained by using only two constraints among the three. More precisely, we show that the a priori boundedness condition ||u(T)|| ≤ M is redundant. This implies that Carasso's SECB condition can be used to replace the a priori boundedness condition of John with an improved stability estimate. Also, a new class of regularized solutions is introduced for backward parabolic problems with an SECB constraint. The new regularized solutions are optimally stable and we also provide a constructive scheme to compute. Finally, numerical examples are provided

Swarm based mean-variance mapping optimization (MVMOS) for solving economic dispatch

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Khoa, T. H.; Vasant, P. M.; Singh, M. S. Balbir; Dieu, V. N.

2014-10-01

The economic dispatch (ED) is an essential optimization task in the power generation system. It is defined as the process of allocating the real power output of generation units to meet required load demand so as their total operating cost is minimized while satisfying all physical and operational constraints. This paper introduces a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS). The technique is the extension of the original single particle mean-variance mapping optimization (MVMO). Its features make it potentially attractive algorithm for solving optimization problems. The proposed method is implemented for three test power systems, including 3, 13 and 20 thermal generation units with quadratic cost function and the obtained results are compared with many other methods available in the literature. Test results have indicated that the proposed method can efficiently implement for solving economic dispatch.

Solving the dial-a-ride problem using agent-based simulation

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Campbell, Ian

2016-11-01

Full Text Available The ‘dial-a-ride problem’ (DARP requires a set of customers to be transported by a limited fleet of vehicles between unique origins and destinations under several service constraints, including within defined time windows. The problem is considered NP-hard, and has typically been solved using metaheuristic methods. An agent-based simulation (ABS model was developed, where each vehicle bids to service customers based on a weighted objective function that considers the cost to service the customer and the time quality of the service that would be achieved. The approach applied a pre- processing technique to reduce the search space, given the service time window constraints. Tests of the model showed significantly better customer transit and waiting times than the benchmark datasets. The ABS was able to obtain solutions for much larger problem sizes than the benchmark solutions, with this work being the first known application of ABS to the DARP.

Simulated annealing algorithm for solving chambering student-case assignment problem

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Ghazali, Saadiah; Abdul-Rahman, Syariza

2015-12-01

The problem related to project assignment problem is one of popular practical problem that appear nowadays. The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased. This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem. The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. The problem of assigning chambering students to cases has never been addressed in the literature before. For the proposed problem, it is essential for law graduates to peruse in chambers before they are qualified to become legal counselor. Thus, assigning the chambering students to cases is a critically needed especially when involving many preferences. Hence, this study presents a preliminary study of the proposed project assignment problem. The objective of the study is to minimize the total completion time for all students in solving the given cases. This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution. The search then is preceded with a simulated annealing algorithm for further improvement of solution quality. The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. Hence, this research has demonstrated the advantages of solving project assignment problem by using metaheuristic techniques.

Optimal residential smart appliances scheduling considering distribution network constraints

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Yu-Ree Kim

2016-01-01

Full Text Available As smart appliances (SAs are more widely adopted within distribution networks, residential consumers can contribute to electricity market operations with demand response resources and reduce their electricity bill. However, if the schedules of demand response resources are determined only by the economic electricity rate signal, the schedule can be unfeasible due to the distribution network constraints. Furthermore, it is impossible for consumers to understand the complex physical characteristics and reflect them in their everyday behaviors. This paper introduces the concept of load coordinating retailer (LCR that deals with demand responsive appliances to reduce electrical consumption for the given distribution network constraints. The LCR can play the role of both conventional retailer and aggregated demand response provider for residential customers. It determines the optimal schedules for the aggregated neighboring SAs according to their types within each distribution feeder. The optimization algorithms are developed using Mixed Integer Linear Programming, and the distribution network is solved by the Newton–Raphson AC power flow.

Revisiting Mathematical Problem Solving and Posing in the Digital Era: Toward Pedagogically Sound Uses of Modern Technology

Science.gov (United States)

Abramovich, S.

2014-01-01

The availability of sophisticated computer programs such as "Wolfram Alpha" has made many problems found in the secondary mathematics curriculum somewhat obsolete for they can be easily solved by the software. Against this background, an interplay between the power of a modern tool of technology and educational constraints it presents is…

Is the job satisfaction of primary care team members associated with patient satisfaction?

OpenAIRE

Szecsenyi, Joachim; Goetz, Katja; Campbell, Stephen; Broge, Bjoern; Reuschenbach, Bernd; Wensing, Michel

2011-01-01

Background Previous research has shown a correlation between physician job satisfaction and patient satisfaction with quality of care, but the connection between job satisfaction of other primary care team members and patient satisfaction is yet unclear. Objective To evaluate whether there is an association between patient satisfaction and job satisfaction of the members of patient care teams. Design The study was based on data from the European Practice Assessment and used an observational d...

Time-varying acceleration coefficients IPSO for solving dynamic economic dispatch with non-smooth cost function

International Nuclear Information System (INIS)

Mohammadi-ivatloo, Behnam; Rabiee, Abbas; Ehsan, Mehdi

2012-01-01

Highlights: ► New approach to solve power systems dynamic economic dispatch. ► Considering Valve-point effect, prohibited operation zones. ► Proposing TVAC-IPSO algorithm. - Abstract: The objective of the dynamic economic dispatch (DED) problem is to schedule power generation for the online units for a given time horizon economically, satisfying various operational constraints. Due to the effect of valve-point effects and prohibited operating zones (POZs) in the generating units cost functions, DED problem is a highly non-linear and non-convex optimization problem. The DED problem even may be more complicated if transmission losses and ramp-rate constraints are taken into account. This paper presents a novel and heuristic algorithm to solve DED problem of generating units, by employing time varying acceleration coefficients iteration particle swarm optimization (TVAC-IPSO) method. The effectiveness of the proposed method is examined and validated by carrying out extensive tests on different test systems, i.e. 5-unit and 10-unit test systems. Valve-point effects, POZs and ramp-rate constraints along with transmission losses are considered. To examine the efficiency of the proposed TVAC-IPSO algorithm, comprehensive studies are carried out, which compare convergence properties of the proposed TVAC-IPSO approach with conventional PSO algorithm, in addition to the other recently reported approaches. Numerical results show that the TVAC-IPSO method has good convergence properties and the generation costs resulted from the proposed method are lower than other algorithms reported in recent literature.

Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

Science.gov (United States)

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results. PMID:24991645

Firefly algorithm for cardinality constrained mean-variance portfolio optimization problem with entropy diversity constraint.

Science.gov (United States)

Bacanin, Nebojsa; Tuba, Milan

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results.

Projective-Dual Method for Solving Systems of Linear Equations with Nonnegative Variables

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Ganin, B. V.; Golikov, A. I.; Evtushenko, Yu. G.

2018-02-01

In order to solve an underdetermined system of linear equations with nonnegative variables, the projection of a given point onto its solutions set is sought. The dual of this problem—the problem of unconstrained maximization of a piecewise-quadratic function—is solved by Newton's method. The problem of unconstrained optimization dual of the regularized problem of finding the projection onto the solution set of the system is considered. A connection of duality theory and Newton's method with some known algorithms of projecting onto a standard simplex is shown. On the example of taking into account the specifics of the constraints of the transport linear programming problem, the possibility to increase the efficiency of calculating the generalized Hessian matrix is demonstrated. Some examples of numerical calculations using MATLAB are presented.

Intuitionistic Fuzzy Goal Programming Technique for Solving Non-Linear Multi-objective Structural Problem

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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.

Ant system for reliability optimization of a series system with multiple-choice and budget constraints

International Nuclear Information System (INIS)

Nahas, Nabil; Nourelfath, Mustapha

2005-01-01

Many researchers have shown that insect colonies behavior can be seen as a natural model of collective problem solving. The analogy between the way ants look for food and combinatorial optimization problems has given rise to a new computational paradigm, which is called ant system. This paper presents an application of ant system in a reliability optimization problem for a series system with multiple-choice constraints incorporated at each subsystem, to maximize the system reliability subject to the system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. This problem is solved by developing and demonstrating a problem-specific ant system algorithm. In this algorithm, solutions of the reliability optimization problem are repeatedly constructed by considering the trace factor and the desirability factor. A local search is used to improve the quality of the solutions obtained by each ant. A penalty factor is introduced to deal with the budget constraint. Simulations have shown that the proposed ant system is efficient with respect to the quality of solutions and the computing time

Singular vectors and topological theories from Virasoro constraints via the Kontsevich-Miwa transform

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Gato-Rivera, B.

1993-01-01

We use the Kontsevich-Miwa transform to relate the different pictures describing matter coupled to topological gravity in two dimensions: topological theories, Virasoro constraints on integrable hierarchies, and a DDK-type formalism. With the help of the Kontsevich-Miwa transform, we solve the Virasoro constraints on the KP hierarchy in terms of minimal models dressed with a (free) Liouville-like scalar. The dressing prescription originates in a topological (twisted N=2) theory. The Virasoro constraints are thus related to essentially the N=2 null state decoupling equations. The N=2 generators are constructed out of matter, the `Liouville' scalar, and $c=-2$ ghosts. By a `dual' construction involving the reparametrization $c=-26$ ghosts, the DDK dressing prescription is reproduced from the N=2 symmetry. As a by-product we thus observe that there are two ways to dress arbitrary $d\\leq1$ or $d\\geq25$ matter theory, that allow its embedding into a topological theory. By th e Kontsevich-Miwa transform, which intr...

Life Domain Satisfactions as Predictors of Overall Life Satisfaction Among Workers: Evidence from Chile.

Science.gov (United States)

Loewe, Nicolas; Bagherzadeh, Mehdi; Araya-Castillo, Luis; Thieme, Claudio; Batista-Foguet, Joan Manuel

2014-01-01

This article examines the subjective antecedents of life satisfaction of workers. Adopting a 'bottom-up' perspective, we assessed the unique influence that satisfaction with multiple life domains have on evaluative judgments of overall life satisfaction. Based on a nationwide sample of 530 Chilean workers, we simultaneously tested the effects of seven life domain satisfactions that have been consistently included in extant models of life satisfaction and subjective well-being. These were satisfaction with health, financial situation, social relationships, one's self-worth, leisure-time, family, and work. Having controlled for age and gender, results showed that satisfaction with one's financial situation was the dominant predictor of overall life satisfaction of workers, with a weight of .36. Satisfaction with family, work, and health had effects of .25, .14, and .14, respectively. Interestingly, satisfaction with one's self-worth, leisure-time, and social relationships did not have statistically significant effects on life satisfaction, although the first two showed t values near the critical value.

Longitudinal Associations Among Relationship Satisfaction, Sexual Satisfaction, and Frequency of Sex in Early Marriage.

Science.gov (United States)

McNulty, James K; Wenner, Carolyn A; Fisher, Terri D

2016-01-01

The current research used two 8-wave longitudinal studies spanning the first 4-5 years of 207 marriages to examine the potential bidirectional associations among marital satisfaction, sexual satisfaction, and frequency of sex. All three variables declined over time, though the rate of decline in each variable became increasingly less steep. Controlling for these changes, own marital and sexual satisfaction were bidirectionally positively associated with one another; higher levels of marital satisfaction at one wave of assessment predicted more positive changes in sexual satisfaction from that assessment to the next and higher levels of sexual satisfaction at one wave of assessment predicted more positive changes in marital satisfaction from that assessment to the next. Likewise, own sexual satisfaction and frequency of sex were bidirectionally positively associated with one another. Additionally, partner sexual satisfaction positively predicted changes in frequency of sex and own sexual satisfaction among husbands, yet partner marital satisfaction negatively predicted changes in both frequency of sex and own sexual satisfaction. Controlling these associations, marital satisfaction did not directly predict changes in frequency of sex or vice versa. Only the association between partner sexual satisfaction and changes in own sexual satisfaction varied across men and women and none of the key effects varied across the studies. These findings suggest that sexual and relationship satisfaction are intricately intertwined and thus that interventions to treat and prevent marital distress may benefit by targeting the sexual relationship and interventions to treat and prevent sexual distress in marriage may benefit by targeting the marital relationship.

Modifier constraint in alkali borophosphate glasses using topological constraint theory

Energy Technology Data Exchange (ETDEWEB)

Li, Xiang [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Zeng, Huidan, E-mail: hdzeng@ecust.edu.cn [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Jiang, Qi [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Zhao, Donghui [Unifrax Corporation, Niagara Falls, NY 14305 (United States); Chen, Guorong [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China); Wang, Zhaofeng; Sun, Luyi [Department of Chemical & Biomolecular Engineering and Polymer Program, Institute of Materials Science, University of Connecticut, Storrs, CT 06269 (United States); Chen, Jianding [Key Laboratory for Ultrafine Materials of Ministry of Education, School of Materials Science and Engineering, East China University of Science and Technology, Shanghai 200237 (China)

2016-12-01

In recent years, composition-dependent properties of glasses have been successfully predicted using the topological constraint theory. The constraints of the glass network are derived from two main parts: network formers and network modifiers. The constraints of the network formers can be calculated on the basis of the topological structure of the glass. However, the latter cannot be accurately calculated in this way, because of the existing of ionic bonds. In this paper, the constraints of the modifier ions in phosphate glasses were thoroughly investigated using the topological constraint theory. The results show that the constraints of the modifier ions are gradually increased with the addition of alkali oxides. Furthermore, an improved topological constraint theory for borophosphate glasses is proposed by taking the composition-dependent constraints of the network modifiers into consideration. The proposed theory is subsequently evaluated by analyzing the composition dependence of the glass transition temperature in alkali borophosphate glasses. This method is supposed to be extended to other similar glass systems containing alkali ions.

The relationship between leisure satisfaction and life satisfaction of adolescents concerning online games.

Science.gov (United States)

Wang, Edward Shih-Tse; Chen, Lily Shui-Lian; Lin, Julia Ying-Chao; Wang, Michael Chih-Hung

2008-01-01

Increasing evidence indicates adolescents are likely to occupy their leisure time with online games. This study investigates the influences of leisure satisfaction on life satisfaction among adolescent online gamers. The self-completed market survey questionnaire employed is comprised of two sections: the first is Internet usage frequency, while the second employs two measures-the Leisure Satisfaction Scale (LSS) and the Satisfaction with Life Scale (SWLS), Data were gathered in a medium-sized metropolitan section of north Taiwan and interviews took place at a Cyber Café. Youths (totaling 134) between the ages of 13 and 18 voluntarily participated in the research. Results revealed significant positive relationships between physiological and aesthetic dimensions of leisure satisfaction and life satisfaction. However, the educational dimension of leisure satisfaction has a significant negative influence on life satisfaction. Findings also reveal a significant negative relationship between web surfing frequency and life satisfaction in adolescents. This suggests possible explanations for these results and discusses the implications.

A HYBRID ALGORITHM FOR THE ROBUST GRAPH COLORING PROBLEM

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Román Anselmo Mora Gutiérrez

2016-08-01

Full Text Available A hybridalgorithm which combines mathematical programming techniques (Kruskal’s algorithm and the strategy of maintaining arc consistency to solve constraint satisfaction problem “CSP” and heuristic methods (musical composition method and DSATUR to resolve the robust graph coloring problem (RGCP is proposed in this paper. Experimental result shows that this algorithm is better than the other algorithms presented on the literature.

Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints

Science.gov (United States)

Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.

2018-02-01

This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.

Customer satisfaction measurement

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Maričić Branko R.

2012-01-01

Full Text Available Customer satisfaction is important in business management as a basis for long-term profitability of a single line of products and services and the company as a whole. Customer satisfaction in modern market conditions is characterized by a large number of alternatives that can satisfy the same need or desire of consumers, and are a prerequisite for the retention, loyalty, and positive verbal communication between companies and vendors on one hand and consumers on the other. Companies are investing more and more investment and management efforts in improving customer satisfaction. Improving customer satisfaction and its measurement involves the taking of appropriate marketing strategies and tactics, as well as corrective measures. This paper presents the well-known attempts to measure customers' satisfaction at the macro and micro level of marketing analysis. The index of consumer satisfaction is an important indicator of achieved quality and market performance of companies and can be measured on a micro and macro level. National customer satisfaction indexes are useful framework for analyzing the competitiveness of national economies, industries and individual companies and are used for a variety of other aspects of observation and analysis. Standardization of consumer satisfaction indexes in different countries allows comparability of the data, giving a new quality of analysis in the era of globalization and internationalization of business.

A Hybrid Soft Computing Approach for Subset Problems

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Broderick Crawford

2013-01-01

Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints

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Shu-Min Lu

2017-01-01

Full Text Available An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function (TVBLF is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network (RBFNN is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness.

Solution of underdetermined systems of equations with gridded a priori constraints.

Science.gov (United States)

Stiros, Stathis C; Saltogianni, Vasso

2014-01-01

The TOPINV, Topological Inversion algorithm (or TGS, Topological Grid Search) initially developed for the inversion of highly non-linear redundant systems of equations, can solve a wide range of underdetermined systems of non-linear equations. This approach is a generalization of a previous conclusion that this algorithm can be used for the solution of certain integer ambiguity problems in Geodesy. The overall approach is based on additional (a priori) information for the unknown variables. In the past, such information was used either to linearize equations around approximate solutions, or to expand systems of observation equations solved on the basis of generalized inverses. In the proposed algorithm, the a priori additional information is used in a third way, as topological constraints to the unknown n variables, leading to an R(n) grid containing an approximation of the real solution. The TOPINV algorithm does not focus on point-solutions, but exploits the structural and topological constraints in each system of underdetermined equations in order to identify an optimal closed space in the R(n) containing the real solution. The centre of gravity of the grid points defining this space corresponds to global, minimum-norm solutions. The rationale and validity of the overall approach are demonstrated on the basis of examples and case studies, including fault modelling, in comparison with SVD solutions and true (reference) values, in an accuracy-oriented approach.

High-Precision Registration of Point Clouds Based on Sphere Feature Constraints

Directory of Open Access Journals (Sweden)

Junhui Huang

2016-12-01

Full Text Available Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.

FGP Approach for Solving Multi-level Multi-objective Quadratic Fractional Programming Problem with Fuzzy parameters

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.

Sensitivity theory for general non-linear algebraic equations with constraints

International Nuclear Information System (INIS)

Oblow, E.M.

1977-04-01

Sensitivity theory has been developed to a high state of sophistication for applications involving solutions of the linear Boltzmann equation or approximations to it. The success of this theory in the field of radiation transport has prompted study of possible extensions of the method to more general systems of non-linear equations. Initial work in the U.S. and in Europe on the reactor fuel cycle shows that the sensitivity methodology works equally well for those non-linear problems studied to date. The general non-linear theory for algebraic equations is summarized and applied to a class of problems whose solutions are characterized by constrained extrema. Such equations form the basis of much work on energy systems modelling and the econometrics of power production and distribution. It is valuable to have a sensitivity theory available for these problem areas since it is difficult to repeatedly solve complex non-linear equations to find out the effects of alternative input assumptions or the uncertainties associated with predictions of system behavior. The sensitivity theory for a linear system of algebraic equations with constraints which can be solved using linear programming techniques is discussed. The role of the constraints in simplifying the problem so that sensitivity methodology can be applied is highlighted. The general non-linear method is summarized and applied to a non-linear programming problem in particular. Conclusions are drawn in about the applicability of the method for practical problems

SOLVING CUSTOMER COMPLAINTS: A STUDY OF MULTIPLE COMMERCIAL SETTINGS

Directory of Open Access Journals (Sweden)

Gurau Calin

2012-12-01

Full Text Available Theme: Many reports stress the importance of solving customer complaints in order to maintain customer satisfaction, but also to learn from mistakes and further improve the customer service. However, relatively few empirical studies have been conducted regarding the effect of complains handling activities on customer satisfaction and on company-customer relationships. Objectives of research: This paper attempts to identify the main elements of the complaints handling strategy that are considered essential for customers, and their effect on customer satisfaction. Literature analysis/previous research: Previous studies define a complaint as a conflict between a consumer and a business organisation in which the fairness of the resolution procedures, the interpersonal communication and behaviour, and the outcome of the complaint resolution process are the principal evaluative criteria used by the customer. In our opinion, a complaint is not necessary a conflict, however, it can create a conflict between a customer and a business organisation, when the answer to the consumer’s complaint is not satisfactory. Therefore, the way in which business organisations deal with consumer complaints can significantly influence the consumers’ level of satisfaction and loyalty. Research methodology: The empirical analysis of primary data collected through face-to-face interviews with 150 French customers provides a detailed picture of the specific elements of complains handling which are perceived as important in four different settings defined in relation to the perceived importance of the product or service, and the emergency of the experienced problem. Results: The identified elements of the complaint-handling procedure have a variable importance from one element to the other, and in the context of various complaint situations. This finding highlights the fact that, depending on each situation, the factors that will determine customer

[Job satisfaction among Norwegian doctors].

Science.gov (United States)

Nylenna, Magne; Aasland, Olaf Gjerløw

2010-05-20

Doctors' job satisfaction has been discussed internationally in recent years based on reports of increasing professional dissatisfaction. We have studied Norwegian doctors' job satisfaction and their general satisfaction with life. A survey was conducted among a representative sample of practicing Norwegian doctors in 2008. The validated 10-item Job Satisfaction Scale was used to assess job satisfaction. 1,072 (65 %) doctors responded. They reported a mean job satisfaction of 5.3 on a scale from 1 (very dissatisfied) to 7 (very satisfied). Job satisfaction increased with increasing age. Private practice specialists reported the highest level of job satisfaction (5.8), and general practitioners reported higher job satisfaction (5.5) than hospital doctors (5.1). Among specialty groups, community doctors scored highest (5.6) and doctors in surgical disciplines lowest (5.0). While long working hours was negatively correlated with job satisfaction, the perception of being professionally updated and having part-time affiliation(s) in addition to a regular job were positively correlated with job satisfaction. 52.9 % of doctors reported a very high general satisfaction. Norwegian doctors have a high level of job satisfaction. Satisfaction with life in general is also high and at least in line with that in the Norwegian population.

Graph-based stochastic control with constraints: A unified approach with perfect and imperfect measurements

KAUST Repository

Agha-mohammadi, Ali-akbar

2013-06-01

This paper is concerned with the problem of stochastic optimal control (possibly with imperfect measurements) in the presence of constraints. We propose a computationally tractable framework to address this problem. The method lends itself to sampling-based methods where we construct a graph in the state space of the problem, on which a Dynamic Programming (DP) is solved and a closed-loop feedback policy is computed. The constraints are seamlessly incorporated to the control policy selection by including their effect on the transition probabilities of the graph edges. We present a unified framework that is applicable both in the state space (with perfect measurements) and in the information space (with imperfect measurements).

Is the job satisfaction of primary care team members associated with patient satisfaction?

NARCIS (Netherlands)

Szecsenyi, J.; Goetz, K.; Campbell, S.M.; Broge, B.; Reuschenbach, B.; Wensing, M.J.P.

2011-01-01

BACKGROUND Previous research has shown a correlation between physician job satisfaction and patient satisfaction with quality of care, but the connection between job satisfaction of other primary care team members and patient satisfaction is yet unclear. OBJECTIVE To evaluate whether there is an

Tightness of Semidefinite Programming Relaxation to Robust Transmit Beamforming with SINR Constraints

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Yanjun Wang

2013-01-01

Full Text Available This paper considers a multiuser transmit beamforming problem under uncertain channel state information (CSI subject to SINR constraints in a downlink multiuser MISO system. A robust transmit beamforming formulation is proposed. This robust formulation is to minimize the transmission power subject to worst-case signal-to-interference-plus-noise ratio (SINR constraints on the receivers. The challenging problem is that the worst-case SINR constraints correspond to an infinite number of nonconvex quadratic constraints. In this paper, a natural semidifinite programming (SDP relaxation problem is proposed to solve the robust beamforming problem. The main contribution of this paper is to establish the tightness of the SDP relaxation problem under proper assumption, which means that the SDP relaxation problem definitely yields rank-one solutions under the assumption. Then the SDP relaxation problem provides globally optimum solutions of the primal robust transmit beamforming problem under proper assumption and norm-constrained CSI errors. Simulation results show the correctness of the proposed theoretical results and also provide a counterexample whose solutions are not rank one. The existence of counterexample shows that the guess that the solutions of the SDP relaxation problem must be rank one is wrong, except that some assumptions (such as the one proposed in this paper hold.

Solving Differential Equations in R: Package deSolve

Science.gov (United States)

In this paper we present the R package deSolve to solve initial value problems (IVP) written as ordinary differential equations (ODE), differential algebraic equations (DAE) of index 0 or 1 and partial differential equations (PDE), the latter solved using the method of lines appr...

A Research on Patient Satisfaction with Primary Health Care in the Center of Afyonkarahisar

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Nazli Sensoy

2013-10-01

Full Text Available Aim: Patient satisfaction is an important indicator to evaluate the quality of primary health care service. It is also significant to improve the quality of medical care, expectation from health staff, priority of patient needs, views and feedbacks about medical services in primary health care. Our objective in this study is to determine the patient satisfaction and the factors effecting this aspect in the evaluation of primary health care quality. Material and Method: This research was carried out in one Mother and Child Health and Family Planning Centre and nine Health Centers in January 2009 at Afyonkarahisar center. The questionnaire was performed to investigate the degree of satisfaction about health services, and socio-demographic characteristics of patients admitted to primary health care by face to face interview method. The data was evaluated by SPSS 15.00.Results: 1227 patients participating in the study, 809 women and 418 were male, married 878, 290 were single.Their education level was 408 graduated from primary school. At the same time, their job distributions were 596 housewives, 133 retired. When the patients had health problems, the most preferable institutione was health center, the choice of the reasons they were satisfied with the services in general, determined as to obtain quick results and confidence in solving problems.75% of the patients waiting time for admission and registration procedures were 0-5minutes. The admission reasons were mostly physical examination and prescription. Patients who are male, aged above 50 years and low educated had much higher satisfaction levels. Discussion: As a result, decreased satisfaction with higher education level, satisfaction increased with increasing age and a short waiting period for the application-registration and examination procedures were being influenced patient satisfaction.

Application of Heuristic and Metaheuristic Algorithms in Solving Constrained Weber Problem with Feasible Region Bounded by Arcs

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Igor Stojanović

2017-01-01

Full Text Available The continuous planar facility location problem with the connected region of feasible solutions bounded by arcs is a particular case of the constrained Weber problem. This problem is a continuous optimization problem which has a nonconvex feasible set of constraints. This paper suggests appropriate modifications of four metaheuristic algorithms which are defined with the aim of solving this type of nonconvex optimization problems. Also, a comparison of these algorithms to each other as well as to the heuristic algorithm is presented. The artificial bee colony algorithm, firefly algorithm, and their recently proposed improved versions for constrained optimization are appropriately modified and applied to the case study. The heuristic algorithm based on modified Weiszfeld procedure is also implemented for the purpose of comparison with the metaheuristic approaches. Obtained numerical results show that metaheuristic algorithms can be successfully applied to solve the instances of this problem of up to 500 constraints. Among these four algorithms, the improved version of artificial bee algorithm is the most efficient with respect to the quality of the solution, robustness, and the computational efficiency.

Improve Problem Solving Skills through Adapting Programming Tools

Science.gov (United States)

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.

Solving Differential Equations in R: Package deSolve

NARCIS (Netherlands)

Soetaert, K.E.R.; Petzoldt, T.; Setzer, R.W.

2010-01-01

In this paper we present the R package deSolve to solve initial value problems (IVP) written as ordinary differential equations (ODE), differential algebraic equations (DAE) of index 0 or 1 and partial differential equations (PDE), the latter solved using the method of lines approach. The

Preconditioning for Allen–Cahn variational inequalities with non-local constraints

KAUST Repository

Blank, Luise

2012-06-01

The solution of Allen-Cahn variational inequalities with mass constraints is of interest in many applications. This problem can be solved both in its scalar and vector-valued form as a PDE-constrained optimization problem by means of a primal-dual active set method. At the heart of this method lies the solution of linear systems in saddle point form. In this paper we propose the use of Krylov-subspace solvers and suitable preconditioners for the saddle point systems. Numerical results illustrate the competitiveness of this approach. © 2012 Elsevier Inc.

Theory and algorithms for solving large-scale numerical problems. Application to the management of electricity production

International Nuclear Information System (INIS)

Chiche, A.

2012-01-01

This manuscript deals with large-scale optimization problems, and more specifically with solving the electricity unit commitment problem arising at EDF. First, we focused on the augmented Lagrangian algorithm. The behavior of that algorithm on an infeasible convex quadratic optimization problem is analyzed. It is shown that the algorithm finds a point that satisfies the shifted constraints with the smallest possible shift in the sense of the Euclidean norm and that it minimizes the objective on the corresponding shifted constrained set. The convergence to such a point is realized at a global linear rate, which depends explicitly on the augmentation parameter. This suggests us a rule for determining the augmentation parameter to control the speed of convergence of the shifted constraint norm to zero. This rule has the advantage of generating bounded augmentation parameters even when the problem is infeasible. As a by-product, the algorithm computes the smallest translation in the Euclidean norm that makes the constraints feasible. Furthermore, this work provides solution methods for stochastic optimization industrial problems decomposed on a scenario tree, based on the progressive hedging algorithm introduced by [Rockafellar et Wets, 1991]. We also focus on the convergence of that algorithm. On the one hand, we offer a counter-example showing that the algorithm could diverge if its augmentation parameter is iteratively updated. On the other hand, we show how to recover the multipliers associated with the non-dualized constraints defined on the scenario tree from those associated with the corresponding constraints of the scenario subproblems. Their convergence is also analyzed for convex problems. The practical interest of theses solutions techniques is corroborated by numerical experiments performed on the electric production management problem. We apply the progressive hedging algorithm to a realistic industrial problem. More precisely, we solve the French medium

Meta-analytic of the relationship between employee job satisfaction and customer satisfaction

OpenAIRE

Marlena León Mendoza; Carlos Ortega Maldonado

2014-01-01

A meta-analysis of the relationship between employee job satisfaction and customer satisfaction was conducted. This analysis produced statistically significant correlation for this relationship. Results suggest that the service context is a moderator of the employee job satisfaction – customer satisfaction relationship in a way that in personal services this correlation is stronger than in non-personal services. Some implications for future research are presented

Tailored parameter optimization methods for ordinary differential equation models with steady-state constraints.

Science.gov (United States)

Fiedler, Anna; Raeth, Sebastian; Theis, Fabian J; Hausser, Angelika; Hasenauer, Jan

2016-08-22

Ordinary differential equation (ODE) models are widely used to describe (bio-)chemical and biological processes. To enhance the predictive power of these models, their unknown parameters are estimated from experimental data. These experimental data are mostly collected in perturbation experiments, in which the processes are pushed out of steady state by applying a stimulus. The information that the initial condition is a steady state of the unperturbed process provides valuable information, as it restricts the dynamics of the process and thereby the parameters. However, implementing steady-state constraints in the optimization often results in convergence problems. In this manuscript, we propose two new methods for solving optimization problems with steady-state constraints. The first method exploits ideas from optimization algorithms on manifolds and introduces a retraction operator, essentially reducing the dimension of the optimization problem. The second method is based on the continuous analogue of the optimization problem. This continuous analogue is an ODE whose equilibrium points are the optima of the constrained optimization problem. This equivalence enables the use of adaptive numerical methods for solving optimization problems with steady-state constraints. Both methods are tailored to the problem structure and exploit the local geometry of the steady-state manifold and its stability properties. A parameterization of the steady-state manifold is not required. The efficiency and reliability of the proposed methods is evaluated using one toy example and two applications. The first application example uses published data while the second uses a novel dataset for Raf/MEK/ERK signaling. The proposed methods demonstrated better convergence properties than state-of-the-art methods employed in systems and computational biology. Furthermore, the average computation time per converged start is significantly lower. In addition to the theoretical results, the

The Relationship between Job Variables of Life Satisfaction and Marital Satisfaction of Lecturers

OpenAIRE

Metehan ÇELİK; Songül TÜMKAYA

2012-01-01

The purpose of this study was to examine the relationship between the job variables of life satisfaction and marital satisfaction of lecturers. It is descriptive study comparing the marital satisfaction and life satisfaction in terms of gender, academic status, working year and working hours. The sample of the study consisted of voluntary and married 119 lecturers (40 female, 79 male). Data collection instruments were Marital Adjustment Scale and Life Satisfaction Scale. In terms of gender va...

Citizen (Dis)satisfaction

DEFF Research Database (Denmark)

Olsen, Asmus Leth

2015-01-01

This article introduces the importance of equivalence framing for understanding how satisfaction measures affect citizens’ evaluation of public services. Does a 90 percent satisfaction rate have a different effect than a logically equivalent 10 percent dissatisfaction rate? Two experiments were...... conducted on citizens’ evaluations of hospital services in a large, nationally representative sample of Danish citizens. Both experiments found that exposing citizens to a patient dissatisfaction measure led to more negative views of public service than exposing them to a logically equivalent satisfaction...... metric. There is some support for part of the shift in evaluations being caused by a negativity bias: dissatisfaction has a larger negative impact than satisfaction has a positive impact. Both professional experience at a hospital and prior exposure to satisfaction rates reduced the negative response...

Preconditioned alternating direction method of multipliers for inverse problems with constraints

International Nuclear Information System (INIS)

Jiao, Yuling; Jin, Qinian; Lu, Xiliang; Wang, Weijie

2017-01-01

We propose a preconditioned alternating direction method of multipliers (ADMM) to solve linear inverse problems in Hilbert spaces with constraints, where the feature of the sought solution under a linear transformation is captured by a possibly non-smooth convex function. During each iteration step, our method avoids solving large linear systems by choosing a suitable preconditioning operator. In case the data is given exactly, we prove the convergence of our preconditioned ADMM without assuming the existence of a Lagrange multiplier. In case the data is corrupted by noise, we propose a stopping rule using information on noise level and show that our preconditioned ADMM is a regularization method; we also propose a heuristic rule when the information on noise level is unavailable or unreliable and give its detailed analysis. Numerical examples are presented to test the performance of the proposed method. (paper)

Preconditioning for partial differential equation constrained optimization with control constraints

KAUST Repository

Stoll, Martin

2011-10-18

Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.

Preconditioning for partial differential equation constrained optimization with control constraints

KAUST Repository

Stoll, Martin; Wathen, Andy

2011-01-01

Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.

Heuristic Search for Planning with Different Forced Goal-Ordering Constraints

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Jiangfeng Luo

2013-01-01

Full Text Available Planning with forced goal-ordering (FGO constraints has been proposed many times over the years, but there are still major difficulties in realizing these FGOs in plan generation. In certain planning domains, all the FGOs exist in the initial state. No matter which approach is adopted to achieve a subgoal, all the subgoals should be achieved in a given sequence from the initial state. Otherwise, the planning may arrive at a deadlock. For some other planning domains, there is no FGO in the initial state. However, FGO may occur during the planning process if certain subgoal is achieved by an inappropriate approach. This paper contributes to illustrate that it is the excludable constraints among the goal achievement operations (GAO of different subgoals that introduce the FGOs into the planning problem, and planning with FGO is still a challenge for the heuristic search based planners. Then, a novel multistep forward search algorithm is proposed which can solve the planning problem with different FGOs efficiently.

The Effect of Income on Job Satisfaction and Residential Satisfaction: a Literature Review

OpenAIRE

Bahare Fallahi, Aida Mehrad

2015-01-01

The aim of present literature review paper is to identify vital role of income on the amount of job satisfaction and residential satisfaction. The findings of this study express that these two inner feeling factors have fundamental role on individual€™s life. In addition, this study focused on value of income and its effect on job satisfaction and residential satisfaction. Moreover, low levels of income leads to various difficulties such as low level of job satisfaction and decrease of reside...

Declarative Programming with Temporal Constraints, in the Language CG

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Lorina Negreanu

2015-01-01

Full Text Available Specifying and interpreting temporal constraints are key elements of knowledge representation and reasoning, with applications in temporal databases, agent programming, and ambient intelligence. We present and formally characterize the language CG, which tackles this issue. In CG, users are able to develop time-dependent programs, in a flexible and straightforward manner. Such programs can, in turn, be coupled with evolving environments, thus empowering users to control the environment’s evolution. CG relies on a structure for storing temporal information, together with a dedicated query mechanism. Hence, we explore the computational complexity of our query satisfaction problem. We discuss previous implementation attempts of CG and introduce a novel prototype which relies on logic programming. Finally, we address the issue of consistency and correctness of CG program execution, using the Event-B modeling approach.

Declarative Programming with Temporal Constraints, in the Language CG.

Science.gov (United States)

Negreanu, Lorina

2015-01-01

Specifying and interpreting temporal constraints are key elements of knowledge representation and reasoning, with applications in temporal databases, agent programming, and ambient intelligence. We present and formally characterize the language CG, which tackles this issue. In CG, users are able to develop time-dependent programs, in a flexible and straightforward manner. Such programs can, in turn, be coupled with evolving environments, thus empowering users to control the environment's evolution. CG relies on a structure for storing temporal information, together with a dedicated query mechanism. Hence, we explore the computational complexity of our query satisfaction problem. We discuss previous implementation attempts of CG and introduce a novel prototype which relies on logic programming. Finally, we address the issue of consistency and correctness of CG program execution, using the Event-B modeling approach.

Visitors Satisfaction Measurement in Czech Tourism

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Tomáš Sadílek

2015-01-01

Full Text Available The paper deals with describing the method of satisfaction measurement as a one of marketing techniques used for detecting visitors’ satisfaction in tourist regions in the Czech Republic. In the treatise, we try to analyse visitors’ satisfaction with the twenty four partial factors affecting total satisfaction. In the theoretical part of the paper, there are described methodological approaches to satisfaction measurement and presented various methods for satisfaction measurement with focus on the Satisfaction Pyramid method which is also used in the field part. Other presented methods are Customer Satisfaction Index, European Customer Satisfaction Model, Importance-Satisfaction Matrix, SERVQUAL Concept and KANO Model. Data have been collected all over the Czech Republic in years 2010 and 2011 twice every year. In the field part there are presented calculations of data and described total satisfaction, Satisfaction Index and partial satisfactions as well as level of satisfaction by tourist regions and correlations between partial satisfactions and total satisfaction which refers to importance of partial factors. Most important factors affecting total satisfaction are public transport, sport equipment, shopping possibilities, children attractions, orientation signage and free time programs.

Measuring patient satisfaction with health care treatment using the Short Assessment of Patient Satisfaction measure delivered superior and robust satisfaction estimates.

Science.gov (United States)

Hawthorne, Graeme; Sansoni, Jan; Hayes, Laura; Marosszeky, Nick; Sansoni, Emily

2014-05-01

Reviews of patient satisfaction suggest seven dimensions, each of which should be assessed. This study reports development of a short generic patient satisfaction measure for use in routine clinical practice. Participants were randomly recruited from two Australian incontinence clinics. Participants completed a follow-up questionnaire including patient satisfaction items. Iterative Mokken and Rasch analyses derived the Short Assessment of Patient Satisfaction (SAPS) scale from the item bank. The SAPS psychometric properties illustrated the following features, namely its descriptive system covers all seven patient satisfaction dimensions, there were no misfitting items, and the scale exceeded the Loevinger H criteria for a strong unidimensional scale. The reliability of the SAPS was Cronbach α=0.86. When discriminatory function was examined, the SAPS scale was more sensitive than two other generic patient satisfaction instruments. The SAPS scale is based on a firm theoretical model of patient satisfaction and its descriptive system covers the known dimensions contributing to patient satisfaction. Its internal psychometric properties exceeded standard psychometric standards, and it discriminated at least as well as other longer patient satisfaction measures. Although it needs further validation, the study results suggest that it may be useful for assessing patient satisfaction with health care. Copyright © 2011 SAPS is held and will continue to be held in perpetuity by the authors with a license to the Commonwealth of Australia. Researchers are welcome to use the SAPS subject to acknowledgement/citation of the authors' rights in the usual way. Published by Elsevier Inc. All rights reserved.

An Automatic Course Scheduling Approach Using Instructors' Preferences

Directory of Open Access Journals (Sweden)

Hossam Faris

2012-03-01

Full Text Available University Courses Timetabling problem has been extensively researched in the last decade. Therefore, numerous approaches were proposed to solve UCT problem. This paper proposes a new approach to process a sequence of meetings between instructors, rooms, and students in predefined periods of time with satisfying a set of constraints divided in variety of types. In addition, this paper proposes new representation for courses timetabling and conflict-free for each time slot by mining instructor preferences from previous schedules to avoid undesirable times for instructors. Experiments on different real data showed the approach achieved increased satisfaction degree for each instructor and gives feasible schedule with satisfying all hard constraints in construction operation. The generated schedules have high satisfaction degrees comparing with schedules created manually. The research conducts experiments on collected data gathered from the computer science department and other related departments in Jordan University of Science and Technology- Jordan.

[Relevance between expectations before treatment, new symptoms and satisfaction after treatment in patients with pelvic organ prolapse].

Science.gov (United States)

Wang, Yu; Han, Jinsong; Zhang, Kun; Zhu, Fuli; Yang, Junfang; Wang, Yiting

2015-09-01

To investigate the relevance between expectations before treatment, new symptoms and satisfaction after treatment of the pelvic organ prolapse (POP) patients. Made a collection of 75 cases of POP patients at Peking University Third Hospital, who were affected by the POP symptoms and came to our clinic for treatment from January to December in 2013. Prospectively investigate the patients' expectations before treatment, which were the most troubling symptoms to be solved. According to treatment we divided the patients into surgery and pessary groups. Two groups were followed up with the degree to achieve the desired goals using patient global impression of improvement (PGI-I), new symptoms and satisfaction after treatment, try to find the relevance between expectations before treatment, new symptoms and satisfaction after treatment. There were 47 (63%, 47/75) patients in the surgical group and 28 (37%, 28/75) patients in the pessary group. The top three problems for patients were friction when walking (25%, 19/75), dysuria (23%, 17/75) and the feeling of vaginal prolapse (19%, 14/75). The follow-up rate was of 93% (70/75), follow-up time was (5 ± 4) months. Satisfaction score after treatment of surgical group was higher than that of pessary group [(4.9 ± 0.4) versus (4.0 ± 1.3) scores, P satisfaction scores was relevant (P = 0.021). The availability of new symptoms and satisfaction scores was relevant (P = 0.001). When achieving higher expectations to the treatment and no more new symptoms, the satisfaction score after treatment is higher.

MODLP program description: A program for solving linear optimal hydraulic control of groundwater contamination based on MODFLOW simulation. Version 1.0

International Nuclear Information System (INIS)

Ahlfeld, D.P.; Dougherty, D.E.

1994-11-01

MODLP is a computational tool that may help design capture zones for controlling the movement of contaminated groundwater. It creates and solves linear optimization programs that contain constraints on hydraulic head or head differences in a groundwater system. The groundwater domain is represented by USGS MODFLOW groundwater flow simulation model. This document describes the general structure of the computer program, MODLP, the types of constraints that may be imposed, detailed input instructions, interpretation of the output, and the interaction with the MODFLOW simulation kernel

Reconstruction of Undersampled Big Dynamic MRI Data Using Non-Convex Low-Rank and Sparsity Constraints

Directory of Open Access Journals (Sweden)

Ryan Wen Liu

2017-03-01

Full Text Available Dynamic magnetic resonance imaging (MRI has been extensively utilized for enhancing medical living environment visualization, however, in clinical practice it often suffers from long data acquisition times. Dynamic imaging essentially reconstructs the visual image from raw (k,t-space measurements, commonly referred to as big data. The purpose of this work is to accelerate big medical data acquisition in dynamic MRI by developing a non-convex minimization framework. In particular, to overcome the inherent speed limitation, both non-convex low-rank and sparsity constraints were combined to accelerate the dynamic imaging. However, the non-convex constraints make the dynamic reconstruction problem difficult to directly solve through the commonly-used numerical methods. To guarantee solution efficiency and stability, a numerical algorithm based on Alternating Direction Method of Multipliers (ADMM is proposed to solve the resulting non-convex optimization problem. ADMM decomposes the original complex optimization problem into several simple sub-problems. Each sub-problem has a closed-form solution or could be efficiently solved using existing numerical methods. It has been proven that the quality of images reconstructed from fewer measurements can be significantly improved using non-convex minimization. Numerous experiments have been conducted on two in vivo cardiac datasets to compare the proposed method with several state-of-the-art imaging methods. Experimental results illustrated that the proposed method could guarantee the superior imaging performance in terms of quantitative and visual image quality assessments.

Customer satisfaction.

Science.gov (United States)

Vukmir, Rade B

2006-01-01

This paper seeks to present an analysis of the literature examining objective information concerning the subject of customer service, as it applies to the current medical practice. Hopefully, this information will be synthesized to generate a cogent approach to correlate customer service with quality. Articles were obtained by an English language search of MEDLINE from January 1976 to July 2005. This computerized search was supplemented with literature from the author's personal collection of peer-reviewed articles on customer service in a medical setting. This information was presented in a qualitative fashion. There is a significant lack of objective data correlating customer service objectives, patient satisfaction and quality of care. Patients present predominantly for the convenience of emergency department care. Specifics of satisfaction are directed to the timing, and amount of "caring". Demographic correlates including symptom presentation, practice style, location and physician issues directly impact on satisfaction. It is most helpful to develop a productive plan for the "difficult patient", emphasizing communication and empathy. Profiling of the customer satisfaction experience is best accomplished by examining the specifics of satisfaction, nature of the ED patient, demographic profile, symptom presentation and physician interventions emphasizing communication--especially with the difficult patient. The current emergency medicine customer service dilemmas are a complex interaction of both patient and physician factors specifically targeting both efficiency and patient satisfaction. Awareness of these issues particular to the emergency patient can help to maximize efficiency, minimize subsequent medicolegal risk and improve patient care if a tailored management plan is formulated.

Trajectory optimization for lunar soft landing with complex constraints

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Chu, Huiping; Ma, Lin; Wang, Kexin; Shao, Zhijiang; Song, Zhengyu

2017-11-01

A unified trajectory optimization framework with initialization strategies is proposed in this paper for lunar soft landing for various missions with specific requirements. Two main missions of interest are Apollo-like Landing from low lunar orbit and Vertical Takeoff Vertical Landing (a promising mobility method) on the lunar surface. The trajectory optimization is characterized by difficulties arising from discontinuous thrust, multi-phase connections, jump of attitude angle, and obstacles avoidance. Here R-function is applied to deal with the discontinuities of thrust, checkpoint constraints are introduced to connect multiple landing phases, attitude angular rate is designed to get rid of radical changes, and safeguards are imposed to avoid collision with obstacles. The resulting dynamic problems are generally with complex constraints. The unified framework based on Gauss Pseudospectral Method (GPM) and Nonlinear Programming (NLP) solver are designed to solve the problems efficiently. Advanced initialization strategies are developed to enhance both the convergence and computation efficiency. Numerical results demonstrate the adaptability of the framework for various landing missions, and the performance of successful solution of difficult dynamic problems.

Job satisfaction, work ability and life satisfaction among Finnish anaesthesiologists.

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Lindfors, P M; Meretoja, O A; Töyry, S M; Luukkonen, R A; Elovainio, M J; Leino, T J

2007-08-01

Organizational changes and relative growth of the ageing population together with related health problems seem to have increased stressfulness in the work of anaesthesiologists. However, little is known about their work-related well-being and the factors through which their situation could be improved. A cross-sectional questionnaire study of the level and the determinants of job satisfaction, work ability and life satisfaction among female and male anaesthesiologists involved 258 Finnish anaesthesiologists working full time (53% men). The respondents had fairly high job satisfaction, work ability and life satisfaction. No gender differences appeared in these well-being indicators, but their determinants differed by gender. Job satisfaction was only associated with work-related factors in both genders: with job control in women and with job control and organizational justice in men. Work ability correlated with job control and health in both genders and with family life in women. Life satisfaction correlated with individual- and family related factors such as social support and family problems in both genders. Life satisfaction correlated with physical workload in men and health in women. Women had less job control, fewer permanent job contracts and more domestic workload than men. Job control and organizational justice were the most important determinants in work-related well-being. Work-related factors were slightly more important correlates of well-being in males, and family life seems to play a larger role in the well-being of female anaesthesiologists. Organizational and gender issues need to be addressed in order to maintain a high level of well-being among anaesthesiologists.

The Effects of Experience Grouping on Achievement, Problem-Solving Discourse, and Satisfaction in Professional Technical Training

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Mulcahy, Robert Sean

2010-01-01

Learners inevitably enter adult technical training classrooms--indeed, in all classrooms--with different levels of expertise on the subject matter. When the diversity of expertise is wide and the course makes use of small group problem solving, instructors have a choice about how to group learners: they may distribute learners with greater…

The role of coping strategies and self-efficacy as predictors of life satisfaction in a sample of parents of children with autism spectrum disorder.

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Luque Salas, Bárbara; Yáñez Rodríguez, Virginia; Tabernero Urbieta, Carmen; Cuadrado, Esther

2017-02-01

This research aims to understand the role of coping strategies and self-efficacy expectations as predictors of life satisfaction in a sample of parents of boys and girls diagnosed with autistic spectrum disorder. A total of 129 parents (64 men and 65 women) answered a questionnaire on life-satisfaction, coping strategies and self-efficacy scales. Using a regression model, results show that the age of the child is associated with a lower level of satisfaction in parents. The results show that self-efficacy is the variable that best explains the level of satisfaction in mothers, while the use of problem solving explains a higher level of satisfaction in fathers. Men and women show similar levels of life satisfaction; however significant differences were found in coping strategies where women demonstrated higher expressing emotions and social support strategies than men. The development of functional coping strategies and of a high level of self-efficacy represents a key tool for adapting to caring for children with autism. Our results indicated the necessity of early intervention with parents to promote coping strategies, self-efficacy and high level of life satisfaction.

A STUDY ON STATUS OF CLIENT SATISFACTION IN PATIENTS ATTENDING GOVERNMENT HEALTH FACILITIES IN AGRA DISTRICT

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D Anand

2012-09-01

Full Text Available Background: It is easier to evaluate the patient’s satisfaction towards the service than evaluate the quality of medical services that they receive. Patient satisfaction indicators remain stable over time as oppose to clinical indicators which will be changed with technology and pace of medical progress. Objectives: 1 To assess the level of satisfaction of patients attending government health facilities.2 To identify the area of low satisfaction at Government health facility. Methodology: Multistage sampling technique was used for selecting primary and secondary level health facilities. Patients were interviewed, when they were leaving health facility by using pretested, predesigned, semi-structured schedule. Results: A total of 600 clients were interviewed in this study and it was found that there was high level of satisfaction with signboard/display, courtesy and respect given by doctor, overall time duration given by doctor, skills of doctor, effectiveness of health services in solving problem, cost incurred on health services, and behavior of paramedical staff. Whereas comparatively low level of satisfaction was found regarding timings of OPD, registration procedure, waiting time, Cleanliness and comfort of waiting area and examination room, privacy measures and behavior of other non medical staff member.Major causes of dissatisfaction at primary level were Comfort and cleanliness of waiting area and service area, privacy measures, overall time duration given by doctor and behavior of supporting staff. However at higher i.e. secondary and tertiary level major causes found were inadequate OPD timing, mismanaged registration procedure and long waiting time to seek doctor. Conclusion: To raise level of patients satisfaction there should be capacity building,training and orientation programmes for health professonals.

Analysis of Satisfaction Degree of the Public Insurance System Beneficiaries

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Manuela PANAITESCU

2013-08-01

Full Text Available The public insurance system provides financial benefits to individuals that are obtained by collecting the due contributions. The analysis of satisfaction degree of the beneficiaries of the system was carried out to determine the challenges the system is facing and for determining the needs of the beneficiaries. In order to reduce the financial constraints the public insurance system is facing, it is necessary to create an appropriate insurance system that meets the needs of the beneficiaries. The research took into account that the public insurance system determines the quality of life of the population and has a strong influence on the economy, particularly on the labour market and the capital market.

Modified Cuckoo Search Algorithm for Solving Nonconvex Economic Load Dispatch Problems

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Thang Trung Nguyen

2016-01-01

Full Text Available This paper presents the application of modified cuckoo search algorithm (MCSA for solving economic load dispatch (ELD problems. The MCSA method is developed to improve the search ability and solution quality of the conventional CSA method. In the MCSA, the evaluation of eggs has divided the initial eggs into two groups, the top egg group with good quality and the abandoned group with worse quality. Moreover, the value of the updated step size in MCSA is adapted as generating a new solution for the abandoned group and the top group via the Levy flights so that a large zone is searched at the beginning and a local zone is foraged as the maximum number of iterations is nearly reached. The MCSA method has been tested on different systems with different characteristics of thermal units and constraints. The result comparison with other methods in the literature has indicated that the MCSA method can be a powerful method for solving the ELD.

Satisfaction of users of the Family Health Strategy in a capital city of Northeast Brazil

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Luana Kelle Batista Moura

2017-03-01

Full Text Available Objective: To analyze the satisfaction of users of the Family Health Strategy in relation to the Reliability and Safety aspects. Method: This is a quantitative research carried out with 353 participants enrolled in an Integrated Health Center of the eastern region of a capital in the Northeast Brazil, through the SERVQUAL instrument. The data collection took place from January to May 2015, the research was approved by the Ethics and Research Committee of the UNINOVAFAPI University Center. Results: The results indicated that in the Reliability dimension, participants agreed that the healthcare professionals record the attendance, perform on the promised date and have an interest in solving the problems. In the Security dimension, the majority of the participants were indifferent as to the behavior of the professionals generating confidence. They demonstrated security in requesting the services because they were politely attended by the professionals. Moreover, in the two dimensions analyzed, it was noticed that there is a tendency to increase satisfaction as the participants' income decreases with significant statistical relations, with satisfaction on Reliability and Security inversely proportional to income. Conclusion: It is considered that users of the Family Health Strategy have demonstrated satisfaction with the services received, however, there is a need for more studies with different methodological approaches to better elucidate the intersubjective issues that shape the process of interaction between users, healthcare professionals and services. Keywords: Family health; patient satisfaction; security.

Cognitive Load in eCommerce Applications—Measurement and Effects on User Satisfaction

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Peter Schmutz

2009-01-01

Full Text Available Guidelines for designing usable interfaces recommend reducing short term memory load. Cognitive load, that is, working memory demands during problem solving, reasoning, or thinking, may affect users' general satisfaction and performance when completing complex tasks. Whereas in design guidelines numerous ways of reducing cognitive load in interactive systems are described, not many attempts have been made to measure cognitive load in Web applications, and few techniques exist. In this study participants' cognitive load was measured while they were engaged in searching for several products in four different online book stores. NASA-TLX and dual-task methodology were used to measure subjective and objective mental workload. The dual-task methodology involved searching for books as the primary task and a visual monitoring task as the secondary task. NASA-TLX scores differed significantly among the shops. Secondary task reaction times showed no significant differences between the four shops. Strong correlations between NASA-TLX, primary task completion time, and general satisfaction suggest that NASA-TLX can be used as a valuable additional measure of efficiency. Furthermore, strong correlations were found between browse/search preference and NASA-TLX as well as between search/browse preference and user satisfaction. Thus we suggest browse/search preference as a promising heuristic assessment method of cognitive load.

Toward Solving the Problem of Problem Solving: An Analysis Framework

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Roesler, Rebecca A.

2016-01-01

Teaching is replete with problem solving. Problem solving as a skill, however, is seldom addressed directly within music teacher education curricula, and research in music education has not examined problem solving systematically. A framework detailing problem-solving component skills would provide a needed foundation. I observed problem solving…

Minimizing total weighted tardiness for the single machine scheduling problem with dependent setup time and precedence constraints

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Hamidreza Haddad

2012-04-01

Full Text Available This paper tackles the single machine scheduling problem with dependent setup time and precedence constraints. The primary objective of this paper is minimization of total weighted tardiness. Since the complexity of the resulted problem is NP-hard we use metaheuristics method to solve the resulted model. The proposed model of this paper uses genetic algorithm to solve the problem in reasonable amount of time. Because of high sensitivity of GA to its initial values of parameters, a Taguchi approach is presented to calibrate its parameters. Computational experiments validate the effectiveness and capability of proposed method.

Tracking the employee satisfaction-life satisfaction binary: the case of South African academics

OpenAIRE

Mafini, Chengedzai

2014-01-01

Orientation: The study tests a conceptual framework that suggests a positive interplay between life satisfaction and five employee satisfaction dimensions, namely workplace flexibility, skills utilisation, teamwork, remuneration and autonomy. Research purpose: The aim of the study was to investigate the relationship between employee satisfaction and life satisfaction amongst university academics in South Africa. Motivation for the study: The study occupies the gap in literature focusin...

Constraints to solve parallelogram grid problems in 2D non separable linear canonical transform

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Zhao, Liang; Healy, John J.; Muniraj, Inbarasan; Cui, Xiao-Guang; Malallah, Ra'ed; Ryle, James P.; Sheridan, John T.

2017-05-01

The 2D non-separable linear canonical transform (2D-NS-LCT) can model a range of various paraxial optical systems. Digital algorithms to evaluate the 2D-NS-LCTs are important in modeling the light field propagations and also of interest in many digital signal processing applications. In [Zhao 14] we have reported that a given 2D input image with rectangular shape/boundary, in general, results in a parallelogram output sampling grid (generally in an affine coordinates rather than in a Cartesian coordinates) thus limiting the further calculations, e.g. inverse transform. One possible solution is to use the interpolation techniques; however, it reduces the speed and accuracy of the numerical approximations. To alleviate this problem, in this paper, some constraints are derived under which the output samples are located in the Cartesian coordinates. Therefore, no interpolation operation is required and thus the calculation error can be significantly eliminated.

From physical dose constraints to equivalent uniform dose constraints in inverse radiotherapy planning

International Nuclear Information System (INIS)

Thieke, Christian; Bortfeld, Thomas; Niemierko, Andrzej; Nill, Simeon

2003-01-01

Optimization algorithms in inverse radiotherapy planning need information about the desired dose distribution. Usually the planner defines physical dose constraints for each structure of the treatment plan, either in form of minimum and maximum doses or as dose-volume constraints. The concept of equivalent uniform dose (EUD) was designed to describe dose distributions with a higher clinical relevance. In this paper, we present a method to consider the EUD as an optimization constraint by using the method of projections onto convex sets (POCS). In each iteration of the optimization loop, for the actual dose distribution of an organ that violates an EUD constraint a new dose distribution is calculated that satisfies the EUD constraint, leading to voxel-based physical dose constraints. The new dose distribution is found by projecting the current one onto the convex set of all dose distributions fulfilling the EUD constraint. The algorithm is easy to integrate into existing inverse planning systems, and it allows the planner to choose between physical and EUD constraints separately for each structure. A clinical case of a head and neck tumor is optimized using three different sets of constraints: physical constraints for all structures, physical constraints for the target and EUD constraints for the organs at risk, and EUD constraints for all structures. The results show that the POCS method converges stable and given EUD constraints are reached closely

Intrinsic job satisfaction, overall satisfaction, and intention to leave the job among nursing assistants in nursing homes.

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Decker, Frederic H; Harris-Kojetin, Lauren D; Bercovitz, Anita

2009-10-01

We examined predictors of intrinsic job satisfaction, overall satisfaction, and intention to leave the job among nursing assistants (NAs). The study focused on NAs who worked 30 or more hours per week in a nursing home. Data on 2,146 NAs meeting this criterion came from the 2004 National Nursing Assistant Survey, the first telephone interview survey of NAs nationwide. Regression equations were calculated in which intrinsic satisfaction, overall satisfaction, and intention to leave were dependent variables. NA attributes (e.g., job tenure and education) and extrinsic job factors (e.g., assessment of supervisor behavior, pay satisfaction, and benefits) were exogenous variables. A positive assessment of the supervisor's behavior had the strongest association with intrinsic satisfaction. Pay satisfaction had the second strongest association with intrinsic satisfaction. Predictors with the strongest associations with intention to leave were overall and intrinsic satisfaction. Assessment of the supervisor was not associated directly with intention to leave. Assessments of the supervisor and pay may affect overall satisfaction and intention to leave in part through their direct effects on intrinsic satisfaction. Some facility and NA attributes were related to intrinsic satisfaction but not to overall satisfaction, suggesting that intrinsic satisfaction may be an intervening variable in the impact of these attributes on overall satisfaction. Intrinsic satisfaction and extrinsic job factors amenable to change appear central to NAs' overall satisfaction and intention to leave. A facility may be able to improve extrinsic job factors that improve NAs' job-related affects, including intrinsic satisfaction.

Relations between life satisfaction, family and friendship satisfaction and religiosity in adolescence

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Doralúcia Gil da Silva

2017-02-01

Full Text Available This work aimed to discuss relations between life satisfaction, family and friendship satisfaction and religiosity in a sample of adolescents. A record of sociodemographic data, a Multidimensional Scale of Life Satisfaction and a Positive and Negative Affect Scale were applied in 420 students (M= 14.91 years old; SD=1.65 from public schools of Porto Alegre. The results indicated that adolescents who reported having religion had higher life satisfaction, subjective well-being, and family and friendship satisfaction, all with significant differences. Religiosity and interpersonal relationships are factors that can act in a positive way and increase well-being perception by the adolescent. Implications about the form of to assess subjective well-being, as well as religiosity, are discussed.

An Efficient Approach for Solving Mesh Optimization Problems Using Newton’s Method

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Jibum Kim

2014-01-01

Full Text Available We present an efficient approach for solving various mesh optimization problems. Our approach is based on Newton’s method, which uses both first-order (gradient and second-order (Hessian derivatives of the nonlinear objective function. The volume and surface mesh optimization algorithms are developed such that mesh validity and surface constraints are satisfied. We also propose several Hessian modification methods when the Hessian matrix is not positive definite. We demonstrate our approach by comparing our method with nonlinear conjugate gradient and steepest descent methods in terms of both efficiency and mesh quality.

Canadian nurse practitioner job satisfaction.

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LaMarche, Kimberley; Tullai-McGuinness, Susan

2009-01-01

To examine the level of job satisfaction and its association with extrinsic and intrinsic job satisfaction characteristics among Canadian primary healthcare nurse practitioners (NPs). A descriptive correlational design was used to collect data on NPs' job satisfaction and on the factors that influence their job satisfaction. A convenience sample of licensed Canadian NPs was recruited from established provincial associations and special-interest groups. Data about job satisfaction were collected using two valid and reliable instruments, the Misener Nurse Practitioner Job Satisfaction Survey and the Minnesota Satisfaction Questionnaire. Descriptive statistics, Pearson correlation and regression analysis were used to describe the results. The overall job satisfaction for this sample ranged from satisfied to highly satisfied. The elements that had the most influence on overall job satisfaction were the extrinsic category of partnership/collegiality and the intrinsic category of challenge/autonomy. These findings were consistent with Herzberg's Dual Factor Theory of Job Satisfaction. The outcomes of this study will serve as a foundation for designing effective human health resource retention and recruitment strategies that will assist in enhancing the implementation and the successful preservation of the NP's role.

[Nurses' professional satisfaction].

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Del Cura, M L; Rodrigues, A R

1999-10-01

We carried out a study with 91 nurses, trying to find out about the feelings of these professionals regarding their satisfaction at work. We used the Work Satisfaction Assessment Questionnaire (WSAQ), drawn up and validated by Siqueira (1978) and adapted with the analysis of seven factors: General Satisfaction; Physical and Psychological Stress; "Status" of the Job; Location of the Company; Compensating Benefits; Recognition and Personal Development. Data showed nurses satisfied with their work, in its intrinsic aspects (Accomplishment, Recognition and Autonomy). The psychiatric nurses were the most mature, most experienced, showing a higher satisfaction level, whereas the pediatric nurses were the youngest, most inexperienced and presenting the highest level of dissatisfaction at work.

THE LINK BETWEEN STUDENTS' SATISFACTION WITH FACULTY, OVERALL STUDENTS' SATISFACTION WITH STUDENT LIFE AND STUDENT PERFORMANCES

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Zoran Mihanović

2016-03-01

Full Text Available Customer satisfaction has long been recognized as a central concept of all business activities. Satisfaction can serve as an indicator of success of the company, both in the past and present, as well as an indicator of future performance. High quality service to students is a prerequisite of maintaining competitiveness in the market of higher education. A relationship that is created between the expectations of students and their satisfaction with the quality of service that provides educational institution plays an important role in shaping the reputation of academic institutions. Academic institutions are becoming aware of the importance of student satisfaction, because satisfaction positively influences their decision to continue their education at this institution, and the positive word of mouth that will attract prospective students. Satisfaction will affect student motivation, and therefore their performance. This paper provides insight into the marketing aspects of customer satisfaction, primarily insight into the satisfaction of students in the educational sector. The aim is to establish the influence of satisfaction various factors related to the university and higher education to the satisfaction of student life, and does student life satisfaction affect the overall happiness and student performance. The research was conducted on the student population of the University of Split, on a sample of 191 respondents. The research was conducted with the help of online survey questionnaire. The claim that student’s satisfactions with housing affect the satisfaction with the quality of student life is rejected. The results confirmed that the student’s satisfaction with university contents, university bodies and services, teaching, teaching methods and academic reputation affects the satisfaction of student life and student life satisfaction affect the student performance.

Assessment of Mammography Experiences and Satisfaction among American Indian/Alaska Native Women

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Ndikum-Moffor, Florence M.; Braiuca, Stacy; Daley, Christine Makosky; Gajewski, Byron J.; Engelman, Kimberly K.

2013-01-01

BACKGROUND American Indian/Alaska Native (AI/AN) women have lower breast cancer (BCA) screening and 5-year survival rates than non-Hispanic Whites. Understanding reasons for low screening rates is important to combat later stage diagnoses. The purpose of this study was to assess mammography experiences and satisfaction among AI/AN women. METHODS Nine focus groups were held with rural (N=15) and urban (N=38) AI/AN women 40 years and older in Kansas and Kansas City, Missouri, living both near and far from Indian Health Service (IHS) and tribal facilities, to examine experiences and satisfaction with mammography. Transcripts were coded and themes identified using a community-based participatory research approach. FINDINGS Themes were classified under knowledge, communication, and awareness of breast cancer, barriers to mammography, mammogram facility size, impressions of mammogram technologist, motivations to getting a mammogram, and how to improve the mammogram experience. Participants had knowledge of prevention, but described cultural reasons for not discussing it and described better experiences in smaller facilities. Participants indicated having a mammogram technologist who was friendly, knowledgeable, respectful, competent, and explained the test was a determining factor in satisfaction. Other factors included family history, physician recommendation, and financial incentives. Barriers included transportation, cost, perceptions of prejudice, and time constraints. Participants on reservations or near IHS facilities preferred IHS over mainstream providers. Suggestions for improvement included caring technologists, better machines with less discomfort, and education. CONCLUSIONS Interventions to enhance the professionalism, empathy, and cultural awareness of mammogram technologists, reduce barriers, and provide positive expectations and incentives could improve satisfaction and compliance with screening mammography. PMID:24183414

SATISFACTION OF PATIENTS WITH ARTHROSIS FROM MULTIDISCIPLINARY COOPERATION

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Gergana Nenova

2016-10-01

only within the model of the multidisciplinary team providing integrated care, in contrast with the very low levels of satisfaction with the quality of rehabilitation provided by the NHIF (control group - 2:43 to issue "8" and 2.40 for question "10". CONCLUSIONS: the leading role of the physiotherapist is definitely essential for the patient in the model of the integrated care provided by the multidisciplinary task team at home. The health problem is solved by a patient-centered approach in an environment that is familiar and close to him with almost identical costs in terms of money, time, emotions, etc. in comparison with the costs provided by NHIF.

Solving Partial Differential Equations Using a New Differential Evolution Algorithm

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Natee Panagant

2014-01-01

Full Text Available This paper proposes an alternative meshless approach to solve partial differential equations (PDEs. With a global approximate function being defined, a partial differential equation problem is converted into an optimisation problem with equality constraints from PDE boundary conditions. An evolutionary algorithm (EA is employed to search for the optimum solution. For this approach, the most difficult task is the low convergence rate of EA which consequently results in poor PDE solution approximation. However, its attractiveness remains due to the nature of a soft computing technique in EA. The algorithm can be used to tackle almost any kind of optimisation problem with simple evolutionary operation, which means it is mathematically simpler to use. A new efficient differential evolution (DE is presented and used to solve a number of the partial differential equations. The results obtained are illustrated and compared with exact solutions. It is shown that the proposed method has a potential to be a future meshless tool provided that the search performance of EA is greatly enhanced.

Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals

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Lorber, Mateja; Skela Savič, Brigita

2012-01-01

Aim To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. Methods The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction – satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. Results We found a medium level of job satisfaction in both leaders (3.49 ± 0.5) and employees (3.19 ± 0.6), however, there was a significant difference between their estimates (t = 3.237; P = Job satisfaction was explained by age (P job satisfaction variance. Conclusion Satisfied employees play a crucial role in an organization’s success, so health care organizations must be aware of the importance of employees’ job satisfaction. It is recommended to monitor employees’ job satisfaction levels on an annual basis. PMID:22661140

The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint

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Elnaz Bani

2016-06-01

Full Text Available This paper presents a mathematical model to solve a multi-objective decision making supplier selection problem. The proposed problem considers three objective functions: the first objective function minimizes the cost of purchasing the products while the second objective function minimizes the due dates and finally the third objective function maximizes the customer satisfaction. The resulted problem is formulated as mixed integer programming and, therefore, we use invasive weed optimization technique to solve the resulted problem. The performance of the proposed model is compared with NSGA II based on different criteria such as mean ideal distance and quality matrix. The preliminary results indicate that the proposed model performs relatively well compared with alternative method.

A Single-Arm Feasibility Trial of Problem-Solving Skills Training for Parents of Children with Idiopathic Chronic Pain Conditions Receiving Intensive Pain Rehabilitation.

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Law, Emily F; Fales, Jessica L; Beals-Erickson, Sarah E; Failo, Alessandro; Logan, Deirdre; Randall, Edin; Weiss, Karen; Durkin, Lindsay; Palermo, Tonya M

2017-05-01

To adapt problem-solving skills training (PSST) for parents of children receiving intensive pain rehabilitation and evaluate treatment feasibility, acceptability, and satisfaction. Using a prospective single-arm case series design, we evaluated the feasibility of delivering PSST to 26 parents (84.6% female) from one of three pediatric pain rehabilitation programs. Parents completed four to six sessions of PSST delivered during a 2-4-week period. A mixed-methods approach was used to assess treatment acceptability and satisfaction. We also assessed changes in parent mental health and behavior outcomes from pretreatment to immediate posttreatment and 3-month follow-up. Parents demonstrated excellent treatment adherence and rated the intervention as highly acceptable and satisfactory. Preliminary analyses indicated improvements in domains of mental health, parenting behaviors, health status, and problem-solving skills. Findings demonstrate the potential role of psychological interventions directed at reducing parent distress in the context of intensive pediatric pain rehabilitation. © The Author 2016. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Search and Coherence-Building in Intuition and Insight Problem Solving

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Michael Öllinger

2017-05-01

Full Text Available Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. There are several accounts that address certain aspects of coherence-building. However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state. We adopted a fluency account assuming that the ease of information processing indicates the realization of a coherent state. The third stage is designated to evaluate the result of the coherence-building process and assess whether the given problem is solved or not. If the coherent state does not fit the requirements of the task, the process re-enters at stage 1. These three stages characterize intuition. For insight problem solving a fourth stage is necessary, which restructures the given representation after repeated failure, so that a new search space results. The new search space enables new coherent states. We provide a review of the most important findings, outline our model, present a large number of examples, deduce potential new paradigms and measures that might help to decipher the underlying cognitive processes.

Basic Psychological Need Satisfaction in Leisure Activities and Adolescents’ Life Satisfaction

OpenAIRE

Leversen, Ingrid; Danielsen, Anne G.; Birkeland, Marianne Skogbrott; Samdal, Oddrun

2012-01-01

Participation in leisure activities is an important arena for the positive psychological development of adolescents. The present study set out to examine the relationship between adolescents’ satisfaction of the psychological needs for competence, relatedness, and autonomy in their participation in leisure activities and their perceived life satisfaction. The aim was to identify the extent to which satisfaction of the three needs explained the relationship between participation in leisure act...

Parallel local search for solving Constraint Problems on the Cell Broadband Engine (Preliminary Results

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Salvator Abreu

2009-10-01

Full Text Available We explore the use of the Cell Broadband Engine (Cell/BE for short for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor BladeCenter machine with twin Cell/BE processors (total of 16 SPUs per blade. This algorithm was chosen because it fits very well the Cell/BE architecture and requires neither shared memory nor communication between processors, while retaining a compact memory footprint. We study the performance on several large optimization benchmarks and show that this achieves mostly linear time speedups, even sometimes super-linear. This is possible because the parallel implementation might explore simultaneously different parts of the search space and therefore converge faster towards the best sub-space and thus towards a solution. Besides getting speedups, the resulting times exhibit a much smaller variance, which benefits applications where a timely reply is critical.

The Relationship of Sexual Satisfaction and Marital Satisfaction with Domestic Violence against Pregnant Women

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Somayeh Ramezani

2015-10-01

Full Text Available Introduction: Domestic violence is one of the most important public health priorities that directly or indirectly impact on pregnancy outcomes. Given the importance of sexuality in pregnancy and its effect on marital relations, this study aimed to investigate the relationship between sexual satisfaction and violence against pregnant women.Methods: In this cross-sectional study, 430 pregnant women admitted to Fatemiyeh hospital in Shahroud during the first quarter of 2015, after obtaining informed consent, were selected to complete Larson Sexual Satisfaction Scale and ENRICH Marital Satisfaction Scale as well as Domestic Violence questionnaire. Relationships between variables were analyzed using structural equation modeling.Results: The mean age of mothers was 28±5.2 years. Prevalence of domestic violence was reported 84.4% in this study. The 81.2% of participants reported physical violence, 55.8% reported emotional violence and 25.3% reported sexual violence. The mean score of marital satisfaction in women with domestic violence (162.5 ± 28.9 was significantly lower than that in pregnant women without domestic violence (188.7 ± 31.4. A significant negative relationship was observed between sexual satisfaction and marital satisfaction with the domestic violence, --0.42 and ‌–0.61, respectively.Conclusion: Considering the high prevalence of domestic violence and its significant relationship with marital satisfaction and sexual satisfaction in this study, interventions and counseling are recommended to increase marital satisfaction and sexual satisfaction and to reduce domestic violence during pregnancy.

Job Satisfaction of Nursing Managers

OpenAIRE

Petrosova, Liana; Pokhilenko, Irina

2015-01-01

The aim of the study was to research levels of job satisfaction, factors affecting job satisfaction/dissatisfaction, and ways to improve job satisfaction among nursing managers. The purposes of the study were to extend knowledge in the field of healthcare management, to raise awareness about factors that affect job satisfaction in nursing management career, and to provide suggestions regarding how to increase job satisfaction among nursing managers. The method of this study is literature r...

Life satisfaction and work-related satisfaction among anesthesiologists in Poland.

Science.gov (United States)

Gaszynska, Ewelina; Stankiewicz-Rudnicki, Michal; Szatko, Franciszek; Wieczorek, Andrzej; Gaszynski, Tomasz

2014-01-01

The aim of the study was to assess the level of life and job satisfaction of Polish anesthesiologists and to explore the impact of extrinsic-hygiene and intrinsic-motivating determinants. A cross-sectional questionnaire study was conducted among consultant anesthesiologists in Lodz region. The questionnaire concerned patient care, burden, income, personal rewards, professional relations, job satisfaction in general, and life satisfaction. Respondents were asked to rate their level of satisfaction for each item on a seven-point Likert scale (1: extremely dissatisfied; 7: extremely satisfied). 86.03% of anesthesiologists were satisfied with their economic status, 77.94% found their health status satisfactory, and 52.21% viewed their personal future optimistically. In general, 71.32% of anesthesiologists were satisfied with their current job situation. Among the less satisfying job aspects were work-related stress (2.49; SD = 1.23), administrative burden (2.85; SD = 1.47), workload (3.63; SD = 1.56), and leisure time (3.09; SD = 1.44). Considerable work-related stress leads to job dissatisfaction among anesthesiologists. There is an association between job satisfaction and health status, social life, and economic status. Working for long hours by anesthesiologists results in a high risk of burnout.

The study of life-satisfaction

NARCIS (Netherlands)

R. Veenhoven (Ruut)

1996-01-01

textabstractABSTRACT This chapter reviews the literature on life satisfaction. Six questions are considered: 1) What is the point of studying life-satisfaction? 2) What is life-satisfaction? 3) Can life-satisfaction be measured? 4) How satisfied are we? 5) What causes us to be satisfied or

A New Method for Solving Multiobjective Bilevel Programs

Directory of Open Access Journals (Sweden)

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.

Improving customer satisfaction

OpenAIRE

Wei, Yu

2011-01-01

Today, the competition among enterprises is growing in intensity and organizations of all types and sizes have increasingly come to understand the importance of customer satisfaction and good services. The purpose of this study is to investigate the present level of customer satisfaction with language training institutes and find out any possible areas of improvement. This thesis will discuss and analyze the factors that influence the customer’s level of satisfaction and assist the case compa...

A Decomposition-Based Pricing Method for Solving a Large-Scale MILP Model for an Integrated Fishery

Directory of Open Access Journals (Sweden)

M. Babul Hasan

2007-01-01

The IFP can be decomposed into a trawler-scheduling subproblem and a fish-processing subproblem in two different ways by relaxing different sets of constraints. We tried conventional decomposition techniques including subgradient optimization and Dantzig-Wolfe decomposition, both of which were unacceptably slow. We then developed a decomposition-based pricing method for solving the large fishery model, which gives excellent computation times. Numerical results for several planning horizon models are presented.

Fiber-reinforced materials: finite elements for the treatment of the inextensibility constraint

Science.gov (United States)

Auricchio, Ferdinando; Scalet, Giulia; Wriggers, Peter

2017-12-01

The present paper proposes a numerical framework for the analysis of problems involving fiber-reinforced anisotropic materials. Specifically, isotropic linear elastic solids, reinforced by a single family of inextensible fibers, are considered. The kinematic constraint equation of inextensibility in the fiber direction leads to the presence of an undetermined fiber stress in the constitutive equations. To avoid locking-phenomena in the numerical solution due to the presence of the constraint, mixed finite elements based on the Lagrange multiplier, perturbed Lagrangian, and penalty method are proposed. Several boundary-value problems under plane strain conditions are solved and numerical results are compared to analytical solutions, whenever the derivation is possible. The performed simulations allow to assess the performance of the proposed finite elements and to discuss several features of the developed formulations concerning the effective approximation for the displacement and fiber stress fields, mesh convergence, and sensitivity to penalty parameters.

A Constraint Programming Model for Fast Optimal Stowage of Container Vessel Bays

DEFF Research Database (Denmark)

Delgado-Ortegon, Alberto; Jensen, Rune Møller; Janstrup, Kira

2012-01-01

Container vessel stowage planning is a hard combinatorial optimization problem with both high economic and environmental impact. We have developed an approach that often is able to generate near-optimal plans for large container vessels within a few minutes. It decomposes the problem into a master...... planning phase that distributes the containers to bay sections and a slot planning phase that assigns containers of each bay section to slots. In this paper, we focus on the slot planning phase of this approach and present a constraint programming and integer programming model for stowing a set...... of containers in a single bay section. This so-called slot planning problem is NP-hard and often involves stowing several hundred containers. Using state-of-the-art constraint solvers and modeling techniques, however, we were able to solve 90% of 236 real instances from our industrial collaborator to optimality...

Implementing network constraints in the EMPS model

Energy Technology Data Exchange (ETDEWEB)

Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.

2010-02-15

This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)

Satisfaction and 'comparison sharing'

DEFF Research Database (Denmark)

Amilon, Anna

2009-01-01

the probability of satisfaction. Results show that comparison sharing impacts satisfaction for women, and that those women who share more equally than their peers are more likely to be satisfied, whereas comparison sharing has no influence on satisfaction for men. Also, parents are less likely to be satisfied...

Analyzing Food-Related Life Satisfaction and other Predictors of Life Satisfaction in Central Chile.

Science.gov (United States)

Schnettler, Berta; Lobos, Germán; Orellana, Ligia; Grunert, Klaus; Sepúlveda, José; Mora, Marcos; Denegri, Marianela; Miranda, Horacio

2015-06-17

This study aimed to assess the effect of satisfaction with food-related life on life satisfaction among inhabitants of the main municipalities of central Chile. A survey was applied to a sample of 1,277 people, distributed proportionally by municipality. The questionnaire included the following scales: SWLS (Satisfaction with Life Scale), SWFL (Satisfaction with Food-related Life) and the Health-Related Quality of Life Index (HRQOL). Questions were asked regarding eating habits inside and outside the home, time available for meals at home, the assessment of five sources of happiness and the demographic characteristics of those surveyed. An ordered logit model was proposed, in which the dependent variable was satisfaction with life. Satisfaction with life was significantly related to the respondent's socioeconomic status, self-perception of health, degree of satisfaction with food-related life, monthly food expenditure, time available for supper with the family (p health problems, frequency of supper with the family, the degree of agreement with respect to family being an important source of happiness (p food consumption in fast food outlets (p health, family and eating, and the family interaction associated with eating may play an important role in overall satisfaction with life.

Tracking the employee satisfaction-life satisfaction binary: The case of South African academics

Directory of Open Access Journals (Sweden)

Chengedzai Mafini

2014-11-01

Research purpose: The aim of the study was to investigate the relationship between employee satisfaction and life satisfaction amongst university academics in South Africa. Motivation for the study: The study occupies the gap in literature focusing on the interaction between employee satisfaction and life satisfaction amongst South African university academics. Research design, approach and method: A three-section survey questionnaire was administered to 273 academics recruited from three universities in Gauteng, South Africa. After a confirmatory factor analysis, hypotheses were tested using a combination of Kendall’s tau correlation coefficient and regression analysis. Main findings: Correlation tests revealed strong positive relationships between life satisfaction and three factors: workplace flexibility, skills utilisation and autonomy. Regression analysis showed that workplace flexibility, skills utilisation and autonomy were statistically significant. Practical/managerial implications: Research findings could expedite the generation of strategies for meeting the employment needs and expectations of university academics, thereby reducing the shortage of university academics in South Africa. Contributions/value-add: The conceptual framework proposed in this study is a useful tool for conceptualising the relationship between employee satisfaction and life satisfaction in the higher education environment.

Gender Differences in Job Satisfaction, Satisfaction with Society and Satisfaction from their Salary in Greek Civil Servants who are working under conditions of Labour—Intensive

Science.gov (United States)

Antonakas, Nikolaos; Mironaki, Amalia

2009-08-01

The objective of this study is to determine empirically the existence of differences in three dimensions of satisfaction in Greek civil servants' gender, when they work under conditions of stress and tension. The three dimensions of satisfaction selected to be considered were job satisfaction, satisfaction with society and satisfaction from their salary. For this a two parts questionnaire was used. The first part included, besides sex and socially demographic characteristics of employees and the second part consisted of the above aspects of satisfaction. Used a sample of 290 employees and a factor analysis was conducted on the results of the questionnaire. The central question of this paper was whether the strength of the force of better wage, compared with the average civil servant, affects a different way to meet women and men's satisfaction who work under working conditions—intensity. The main finding of this study was the existence differences between women and men in the dimension of satisfaction from the salary.

Customer satisfaction and business excellence

DEFF Research Database (Denmark)

Kristensen, Kai; Martensen, Anne; Grønholdt, Lars

The topic for this paper is the link between customer satisfaction and business performance, which makes it possible to use customer satisfaction measures as basis for creating business excellence. First, the paper presents microeconomic models for the relationship between customer satisfaction......, customer loyalty and performance, and optimal customer satisfaction is characterized which will help management choose the right quality parameters for improvement. Second, the paper describes empirical evidence that customer satisfaction measures, based on a modelling approach, have impact on economic...

The study of life-satisfaction

OpenAIRE

Veenhoven, Ruut

1996-01-01

textabstractABSTRACT This chapter reviews the literature on life satisfaction. Six questions are considered: 1) What is the point of studying life-satisfaction? 2) What is life-satisfaction? 3) Can life-satisfaction be measured? 4) How satisfied are we? 5) What causes us to be satisfied or dissatisfied with life? 6) Can the level of life-satisfaction be increased? These questions are considered at the individual level as well as the societal level. In the concluding section a general overview...

Customer satisfaction research

Energy Technology Data Exchange (ETDEWEB)

Tormasi, T

1987-03-01

A review of four aspects of the Gas and Fuel Corporation of Victoria's study of customer satisfaction covers: (1) corporate goals to meet its responsibility as a public utility and operate as a successful marketing organization, (2) the history of customer satisfaction research by GFC, (3) measurements of customer satisfaction through expectations research, and (4) case studies involving domestic appliance maintenance and gas mains renewal. Continuous validation of GFC's policies and procedures is the basis for future growth and success. 3 tables.

A constriction factor based particle swarm optimisation algorithm to solve the economic dispatch problem including losses

Energy Technology Data Exchange (ETDEWEB)

Young, Steven; Montakhab, Mohammad; Nouri, Hassan

2011-07-15

Economic dispatch (ED) is one of the most important problems to be solved in power generation as fractional percentage fuel reductions represent significant cost savings. ED wishes to optimise the power generated by each generating unit in a system in order to find the minimum operating cost at a required load demand, whilst ensuring both equality and inequality constraints are met. For the process of optimisation, a model must be created for each generating unit. The particle swarm optimisation technique is an evolutionary computation technique with one of the most powerful methods for solving global optimisation problems. The aim of this paper is to add in a constriction factor to the particle swarm optimisation algorithm (CFBPSO). Results show that the algorithm is very good at solving the ED problem and that CFBPSO must be able to work in a practical environment and so a valve point effect with transmission losses should be included in future work.

Sewing constraints for conformal field theories on surfaces with boundaries

International Nuclear Information System (INIS)

Lewellen, D.C.

1992-01-01

In a conformal field theory, correlation functions on any Riemann surface are in principle unambiguously defined by sewing together three-point functions on the sphere, provided that the four-point functions on the sphere are crossing symmetric, and the one-point functions on the torus are modular covariant. In this work we extend Sonoda's proof of this result to conformal field theories defined on surfaces with boundaries. Four additional sewing constraints arise; three on the half-plane and one on the cylinder. These relate the various OPE coefficients in the theory (bulk, boundary, and bulk-boundary) to one another. In rational theories these relations can be expressed in terms of data arising solely within the bulk theory: The matrix S which implements modular transformations on the characters, and the matrices implementing duality transformations on the four-point conformal-block functions. As an example we solve these relations for the boundary and bulk-boundary structure constants in the Ising model with all possible conformally invariant boundary conditions. The role of the basic sewing constraints in the construction of open string theories is discussed. (orig.)

Individual Differences in the Relationship between Satisfaction with Job Rewards and Job Satisfaction

Science.gov (United States)

Hofmans, Joeri; De Gieter, Sara; Pepermans, Roland

2013-01-01

Although previous research often showed a positive relationship between pay satisfaction and job satisfaction, we dispute the universality of this finding. Cluster-wise regression analyses on three samples consistently show that two types of individuals can be distinguished, each with a different job reward-job satisfaction relationship. For the…

Organizational Communication: Perceptions of Staff Members' Level of Communication Satisfaction and Job Satisfaction

Science.gov (United States)

Sharma, Priti; Lampley, James; Good, Donald

2015-01-01

The purpose of this research study was to explore the topic of organizational communication in higher education and examine staff members' perceptions about their level of communication and job satisfaction in their workplaces. This study was also designed to test the relationship between communication satisfaction and job satisfaction by…

Reduction of Constraints: Applicability of the Homogeneity Constraint for Macrobatch 3

International Nuclear Information System (INIS)

Peeler, D.K.

2001-01-01

The Product Composition Control System (PCCS) is used to determine the acceptability of each batch of Defense Waste Processing Facility (DWPF) melter feed in the Slurry Mix Evaporator (SME). This control system imposes several constraints on the composition of the contents of the SME to define acceptability. These constraints relate process or product properties to composition via prediction models. A SME batch is deemed acceptable if its sample composition measurements lead to acceptable property predictions after accounting for modeling, measurement and analytic uncertainties. The baseline document guiding the use of these data and models is ''SME Acceptability Determination for DWPF Process Control (U)'' by Brown and Postles [1996]. A minimum of three PCCS constraints support the prediction of the glass durability from a given SME batch. The Savannah River Technology Center (SRTC) is reviewing all of the PCCS constraints associated with durability. The purpose of this review is to revisit these constraints in light of the additional knowledge gained since the beginning of radioactive operations at DWPF and to identify any supplemental studies needed to amplify this knowledge so that redundant or overly conservative constraints can be eliminated or replaced by more appropriate constraints

Exact Solution of a Constraint Optimization Problem for the Thermoelectric Figure of Merit

Directory of Open Access Journals (Sweden)

Wolfgang Seifert

2012-03-01

Full Text Available In the classical theory of thermoelectricity, the performance integrals for a fully self-compatible material depend on the dimensionless figure of merit zT. Usually these integrals are evaluated for constraints z = const. and zT = const., respectively. In this paper we discuss the question from a mathematical point of view whether there is an optimal temperature characteristics of the figure of merit. We solve this isoperimetric variational problem for the best envelope of a family of curves z(TT.

Exact Solution of a Constraint Optimization Problem for the Thermoelectric Figure of Merit.

Science.gov (United States)

Seifert, Wolfgang; Pluschke, Volker

2012-03-21

In the classical theory of thermoelectricity, the performance integrals for a fully self-compatible material depend on the dimensionless figure of merit zT. Usually these integrals are evaluated for constraints z = const. and zT = const., respectively. In this paper we discuss the question from a mathematical point of view whether there is an optimal temperature characteristics of the figure of merit. We solve this isoperimetric variational problem for the best envelope of a family of curves z(T)T.

Visitors Satisfaction Measurement in Czech Tourism

OpenAIRE

Tomáš Sadílek

2015-01-01

The paper deals with describing the method of satisfaction measurement as a one of marketing techniques used for detecting visitors’ satisfaction in tourist regions in the Czech Republic. In the treatise, we try to analyse visitors’ satisfaction with the twenty four partial factors affecting total satisfaction. In the theoretical part of the paper, there are described methodological approaches to satisfaction measurement and presented various methods for satisfaction measurement with focus on...

Life Satisfaction and Work-Related Satisfaction among Anesthesiologists in Poland

Directory of Open Access Journals (Sweden)

Ewelina Gaszynska

2014-01-01

Full Text Available The aim of the study was to assess the level of life and job satisfaction of Polish anesthesiologists and to explore the impact of extrinsic-hygiene and intrinsic-motivating determinants. Materials and Methods. A cross-sectional questionnaire study was conducted among consultant anesthesiologists in Lodz region. The questionnaire concerned patient care, burden, income, personal rewards, professional relations, job satisfaction in general, and life satisfaction. Respondents were asked to rate their level of satisfaction for each item on a seven-point Likert scale (1: extremely dissatisfied; 7: extremely satisfied. Results. 86.03% of anesthesiologists were satisfied with their economic status, 77.94% found their health status satisfactory, and 52.21% viewed their personal future optimistically. In general, 71.32% of anesthesiologists were satisfied with their current job situation. Among the less satisfying job aspects were work-related stress (2.49; SD = 1.23, administrative burden (2.85; SD = 1.47, workload (3.63; SD = 1.56, and leisure time (3.09; SD = 1.44. Conclusions. Considerable work-related stress leads to job dissatisfaction among anesthesiologists. There is an association between job satisfaction and health status, social life, and economic status. Working for long hours by anesthesiologists results in a high risk of burnout.

Implementation of the - Constraint Method in Special Class of Multi-objective Fuzzy Bi-Level Nonlinear Problems

Directory of Open Access Journals (Sweden)

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

Heat exchanger networks design with constraints

International Nuclear Information System (INIS)

Amidpur, M.; Zoghi, A.; Nasiri, N.

2000-01-01

So far there have been two approaches to the problem of heat recovery system design where stream matching constraints exist. The first approach involves mathematical techniques for solving the combinational problem taking due recognition of the constraints. These methodologies are now efficient, still suffer from the problem of taking a significant amount of control and direction away from the designer. The second approach based upon so called pinch technology and involves the use of adaptation of standard problem table algorithm. Unfortunately, the proposed methodologies are not very easy to understand, therefore they fail to provide the insight and generally associated with these approaches. Here, a new pinch based methodology is presented. In this method, we modified the traditional numerical targeting procedure-problem table algorithm which is stream cascade table. Unconstrained groups are established by using of artificial intelligence method such that they have minimum utility consumption among different alternatives. Each group is an individual network, therefore, traditional optimization, used in pinch technology, should be employed. By transferring energy between groups heat recovery can be maximized, then each group designs individually and finally networks combine together. One of the advantages of using this method is simple targeting and easy networks-design. Besides the approach has the potential using of new network design methods such as dual temperature approach, flexible pinch design, pseudo pinch design. It is hoped that this methodology provides insight easy network design

Caring for inpatient boarders in the emergency department: improving safety and patient and staff satisfaction.

Science.gov (United States)

Bornemann-Shepherd, Melanie; Le-Lazar, Jamie; Makic, Mary Beth Flynn; DeVine, Deborah; McDevitt, Kelly; Paul, Marcee

2015-01-01

Hospital capacity constraints lead to large numbers of inpatients being held for extended periods in the emergency department. This creates concerns with safety, quality of care, and dissatisfaction of patients and staff. The aim of this quality-improvement project was to improve satisfaction and processes in which nurses provided care to inpatient boarders held in the emergency department. A quality-improvement project framework that included the use of a questionnaire was used to ascertain employee and patient dissatisfaction and identify opportunities for improvement. A task force was created to develop action plans related to holding and caring for inpatients in the emergency department. A questionnaire was sent to nursing staff in spring 2012, and responses from the questionnaire identified improvements that could be implemented to improve care for inpatient boarders. Situation-background-assessment-recommendation (SBAR) communications and direct observations were also used to identify specific improvements. Post-questionnaire results indicated improved satisfaction for both staff and patients. It was recognized early that the ED inpatient area would benefit from the supervision of an inpatient director, managers, and staff. Outcomes showed that creating an inpatient unit within the emergency department had a positive effect on staff and patient satisfaction. Copyright © 2015 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.

Quantitative relationships between occupant satisfaction and satisfaction aspects of indoor environmental quality and building design.

Science.gov (United States)

Frontczak, M; Schiavon, S; Goins, J; Arens, E; Zhang, H; Wargocki, P

2012-04-01

The article examines which subjectively evaluated indoor environmental parameters and building features mostly affect occupants' satisfaction in mainly US office buildings. The study analyzed data from a web-based survey administered to 52,980 occupants in 351 office buildings over 10 years by the Center for the Built Environment. The survey uses 7-point ordered scale questions pertaining to satisfaction with indoor environmental parameters, workspace, and building features. The average building occupant was satisfied with his/her workspace and building. Proportional odds ordinal logistic regression shows that satisfaction with all 15 parameters listed in the survey contributed significantly to overall workspace satisfaction. The most important parameters were satisfaction with amount of space (odds ratio OR 1.57, 95% CI: 1.55-1.59), noise level (OR 1.27, 95% CI: 1.25-1.29), and visual privacy (OR 1.26, 95% CI: 1.24-1.28). Satisfaction with amount of space was ranked to be most important for workspace satisfaction, regardless of age group (below 30, 31-50 or over 50 years old), gender, type of office (single or shared offices, or cubicles), distance of workspace from a window (within 4.6 m or further), or satisfaction level with workspace (satisfied or dissatisfied). Satisfaction with amount of space was not related to the gross amount of space available per person. To maximize workspace satisfaction, designer should invest in aspects that increase satisfaction with amount of space and storage, noise level, and visual privacy. Office workers will be most satisfied with their workspace and building when located close to a window in a private office. This may affect job satisfaction, work performance, and personal and company productivity. © 2011 John Wiley & Sons A/S.

Job satisfaction and gender differences in job satisfaction of teachers in Serbian primary schools

Directory of Open Access Journals (Sweden)

Gligorović Bojana

2014-01-01

Full Text Available This paper aims to examine Serbian primary teachers' job satisfaction as well as the differences in job satisfaction between male and female teachers. The participants were 362 teachers from 57 primary schools in Serbia. Nine dimensions of job satisfaction (Pay, Promotion, Supervision, Fringe Benefits, Contingent Rewards, Operating Procedures, Co-Workers, Nature of Work, Communication were measured. The results indicate that from the dimensions of job satisfaction, Serbian primary teachers are most satisfied with the Nature of work, Communication and Supervision, while the major sources of Serbian primary teachers' job dissatisfaction are Fringe benefits, Pay and Operating procedures. When it comes to the gender difference in job satisfaction, T-test analysis shows slightly higher satisfaction among female teachers, while statistically significant difference exists only in two dimensions: Supervision and Nature of work. Serbian policy makers in the field of education as well as school administrators should pay close attention to teachers' job satisfaction and its improvement considering that it is an essential to the continuing growth of school effectiveness.

Asymmetric effects in customer satisfaction

DEFF Research Database (Denmark)

Füller, Johann; Matzler, Kurt; Faullant, Rita

2006-01-01

The results of this study on customer satisfaction in snowboard areas show that the relationship between an attribute and overall satisfaction can indeed be asymmetric. A 30-item self-administered survey was completed by snowboarders (n=2526) in 51 areas in Austria, Germany, Switzerland and Italy....... Results show that waiting time is a dissatisfier; it has a significant impact on overall customer satisfaction in the low satisfaction condition and becomes insignificant in the high satisfaction situation. Restaurants and bars are hybrids, i.e. importance does not depend on performance. Slopes, fun...

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks.

Science.gov (United States)

Zhang, Guomei; Sun, Hao

2016-12-16

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor's reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

Measuring student satisfaction from their satisfaction in life: a relationship of different components.

Directory of Open Access Journals (Sweden)

Alfonso Ríos Sánchez

2015-02-01

Full Text Available The study sought to find significant satisfaction variables regarding the quality of education concomitantly linked to life satisfaction. It was conducted during 2012-2013, with a population of 235 students of 3rd and 4th graders from Secondary School Education. A measuring instrument based on the sub-dimensional model of comprehensive evaluation and program Scheerens Stufflebeam was created. The ratio of the sub dimensions through regression analysis was studied. Empathy, personal achievements and recognition of success, were the most significant variables as predictors of satisfaction with the quality of education in connection with satisfaction with life. These variables can help us overcome a reduced view on satisfaction, emphasizing areas of school management that can be strengthened and which students consider relevant to their educational development.

Nonlinear Equilibrium and Stability Analysis of Axially Loaded Piles Under Bilateral Contact Constraints

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Ricardo A. da Mota Silveira

Full Text Available AbstractThis paper presents a nonlinear stability analysis of piles under bilateral contact constraints imposed by a geological medium (soil or rock. To solve this contact problem, the paper proposes a general numerical methodology, based on the finite element method (FEM. In this context, a geometrically nonlinear beam-column element is used to model the pile while the geological medium can be idealized as discrete (spring or continuum (Winkler and Pasternak foundation elements. Foundation elements are supposed to react under tension and compression, so during the deformation process the structural elements are subjected to bilateral contact constraints. The errors along the equilibrium paths are minimized and the convoluted nonlinear equilibrium paths are made traceable through the use of an updated Lagrangian formulation and a Newton-Raphson scheme working with the generalized displacement technique. The study offers stability analyses of three problems involving piles under bilateral contact constraints. The analyses show that in the evaluation of critical loads a great influence is wielded by the instability modes. Also, the structural system stiffness can be highly influenced by the representative model of the soil.

Job satisfaction of nurses and identifying factors of job satisfaction in Slovenian Hospitals.

Science.gov (United States)

Lorber, Mateja; Skela Savič, Brigita

2012-06-01

To determine the level of job satisfaction of nursing professionals in Slovenian hospitals and factors influencing job satisfaction in nursing. The study included 4 hospitals selected from the hospital list comprising 26 hospitals in Slovenia. The employees of these hospitals represent 29.8% and 509 employees included in the study represent 6% of all employees in nursing in Slovenian hospitals. One structured survey questionnaire was administered to the leaders and the other to employees, both consisting 154 items evaluated on a 5 point Likert-type scale. We examined the correlation between independent variables (age, number of years of employment, behavior of leaders, personal characteristics of leaders, and managerial competencies of leaders) and the dependent variable (job satisfaction - satisfaction with the work, coworkers, management, pay, etc) by applying correlation analysis and multivariate regression analysis. In addition, factor analysis was used to establish characteristic components of the variables measured. We found a medium level of job satisfaction in both leaders (3.49±0.5) and employees (3.19±0.6), however, there was a significant difference between their estimates (t=3.237; P=lt;0.001). Job satisfaction was explained by age (Plt;0.05; β=0.091), years of employment (Plt;0.05; β=0.193), personal characteristics of leaders (Plt;0.001; β=0.158), and managerial competencies of leaders (Plt;0.000; β=0.634) in 46% of cases. The factor analysis yielded four factors explaining 64% of the total job satisfaction variance. Satisfied employees play a crucial role in an organization's success, so health care organizations must be aware of the importance of employees' job satisfaction. It is recommended to monitor employees' job satisfaction levels on an annual basis.

Job satisfaction of nursing assistants.

Science.gov (United States)

Lerner, Nancy; Resnick, Barbara; Galik, Elizabeth; Flynn, Linda

2011-11-01

This secondary data analysis explored factors influencing job satisfaction in a sample of nursing assistants employed in Maryland skilled nursing facilities. Multiple factors have been shown to affect job satisfaction and turnover in nursing assistants (NAs), but the problem of turnover persists in skilled nursing facility environments affecting quality of care. An existing data set of 556 nursing assistants from 12 Maryland skilled nursing facilities was used. To explore factors found to influence job satisfaction from other studies, a multiple regression analysis was performed. Nine dependent variables previously shown to affect job satisfaction were used. Of these variables, only years of experience (β = .230) and performance of restorative care (β = .095) were found to be positively associated with job satisfaction. Self-esteem (β = -.094) was found to be negatively associated with job satisfaction. Only length of experience and exemplary care as evidenced by the performance of restorative care were associated with job satisfaction. These results mirror results found in other studies. Self-esteem was negatively associated with job satisfaction in this population, a finding needing further study. Copyright © 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins

Reliability-based trajectory optimization using nonintrusive polynomial chaos for Mars entry mission

Science.gov (United States)

Huang, Yuechen; Li, Haiyang

2018-06-01

This paper presents the reliability-based sequential optimization (RBSO) method to settle the trajectory optimization problem with parametric uncertainties in entry dynamics for Mars entry mission. First, the deterministic entry trajectory optimization model is reviewed, and then the reliability-based optimization model is formulated. In addition, the modified sequential optimization method, in which the nonintrusive polynomial chaos expansion (PCE) method and the most probable point (MPP) searching method are employed, is proposed to solve the reliability-based optimization problem efficiently. The nonintrusive PCE method contributes to the transformation between the stochastic optimization (SO) and the deterministic optimization (DO) and to the approximation of trajectory solution efficiently. The MPP method, which is used for assessing the reliability of constraints satisfaction only up to the necessary level, is employed to further improve the computational efficiency. The cycle including SO, reliability assessment and constraints update is repeated in the RBSO until the reliability requirements of constraints satisfaction are satisfied. Finally, the RBSO is compared with the traditional DO and the traditional sequential optimization based on Monte Carlo (MC) simulation in a specific Mars entry mission to demonstrate the effectiveness and the efficiency of the proposed method.

Performance of clustering techniques for solving multi depot vehicle routing problem

Directory of Open Access Journals (Sweden)

Eliana M. Toro-Ocampo

2016-01-01

Full Text Available The vehicle routing problem considering multiple depots is classified as NP-hard. MDVRP determines simultaneously the routes of a set of vehicles and aims to meet a set of clients with a known demand. The objective function of the problem is to minimize the total distance traveled by the routes given that all customers must be served considering capacity constraints in depots and vehicles. This paper presents a hybrid methodology that combines agglomerative clustering techniques to generate initial solutions with an iterated local search algorithm (ILS to solve the problem. Although previous studies clustering methods have been proposed like strategies to generate initial solutions, in this work the search is intensified on the information generated after applying the clustering technique. Besides an extensive analysis on the performance of techniques, and their effect in the final solution is performed. The operation of the proposed methodology is feasible and effective to solve the problem regarding the quality of the answers and computational times obtained on request evaluated literature

Employees´ Job Satisfaction in Company

OpenAIRE

Václavková, Barbora

2015-01-01

This Master´s thesis Employees´ Job Satisfaction in Company is focused on job satisfaction of employees in a particular company. The aim of this thesis is to analyse the current level of employees´ satisfaction, factors that affect the degree of satisfaction and weak segments propose recommendations to increase the level of satisfaction among employees. The first part is theoretical and deals with the approach of the topic employees´ job satisfaction describe theoretical methods that are in p...

Influence of employees' attachment styles on their life satisfaction as mediated by job satisfaction and burnout.

Science.gov (United States)

Reizer, Abira

2015-01-01

The aim of this study was to obtain better insight into the associations between attachment styles and employees' life satisfaction. This was achieved by examining the mediating roles of burnout and job satisfaction. Three hundred and thirty-nine employees, from a convenience community sample, participated in the current study. Results of the mediation model indicated that the associations between avoidance and life satisfaction were mediated by burnout and job satisfaction. However, the associations between attachment anxiety and life satisfaction were mediated by burnout but not by job satisfaction. Theoretical and practical implications for organizations and for attachment theory at work are discussed.

Satisfaction with electronic health records is associated with job satisfaction among primary care physicians

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Christine D Jones

2013-12-01

Full Text Available Objective To evaluate the association between electronic health record (EHR satisfaction and job satisfaction in primary care physicians (PCPs.Method Cross-sectional survey of PCPs at 825 primary care practices in North Carolina.Results Surveys were returned from 283 individuals across 214 practices (26% response rate for practices, of whom 122 were physicians with EHRs and no missing information. We found that for each point increase in EHR satisfaction, job satisfaction increased by ~0.36 points both in an unadjusted and an adjusted model (β 0.359 unadjusted, 0.361 adjusted; p < 0.001 for both models.Conclusion We found that EHR satisfaction was associated with job satisfaction in a cross-sectional survey of PCPs. Our conclusions are limited by suboptimum survey response rate, but if confirmed may have substantial implications for how EHR vendors develop their product to support the needs of PCPs.

Data Reduction Algorithm Using Nonnegative Matrix Factorization with Nonlinear Constraints

Science.gov (United States)

Sembiring, Pasukat

2017-12-01

Processing ofdata with very large dimensions has been a hot topic in recent decades. Various techniques have been proposed in order to execute the desired information or structure. Non- Negative Matrix Factorization (NMF) based on non-negatives data has become one of the popular methods for shrinking dimensions. The main strength of this method is non-negative object, the object model by a combination of some basic non-negative parts, so as to provide a physical interpretation of the object construction. The NMF is a dimension reduction method thathasbeen used widely for numerous applications including computer vision,text mining, pattern recognitions,and bioinformatics. Mathematical formulation for NMF did not appear as a convex optimization problem and various types of algorithms have been proposed to solve the problem. The Framework of Alternative Nonnegative Least Square(ANLS) are the coordinates of the block formulation approaches that have been proven reliable theoretically and empirically efficient. This paper proposes a new algorithm to solve NMF problem based on the framework of ANLS.This algorithm inherits the convergenceproperty of the ANLS framework to nonlinear constraints NMF formulations.

The relationship between self-control, job satisfaction and life satisfaction in Chinese employees: A preliminary study.

Science.gov (United States)

Dou, Kai; Nie, Yan-Gang; Wang, Yu-Jie; Liu, Yao-Zhong

2016-01-01

Previous studies have demonstrated that self-control is positively related to life satisfaction, but this association in Chinese employees and its underlying mechanism are less commonly investigated. In this preliminary study the relationships between self-control and life satisfaction and the mediating effect of job satisfaction were tested. Participants were 482 full-time employees (188 male, 294 female) from different cities in China. They answered self-report questionnaires online that assessed self-control, job satisfaction, and life satisfaction. Path analyses were conducted and bootstrap technique was used to judge the significance of the mediation. Self-control was positively related to both job and life satisfaction. More importantly, job satisfaction significantly mediated the association between self-control and life satisfaction. Furthermore, there was no significant difference in the size of the mediating effect between intrinsic and extrinsic job satisfaction. Results of this preliminary study provide further evidence of the positive association between self-control and life satisfaction. Job satisfaction is found to mediate this relationship.

All ternary permutation constraint satisfaction problems parameterized above average have kernels with quadratic numbers of variables

DEFF Research Database (Denmark)

Gutin, Gregory; Van Iersel, Leo; Mnich, Matthias

2010-01-01

A ternary Permutation-CSP is specified by a subset Π of the symmetric group S3. An instance of such a problem consists of a set of variables V and a multiset of constraints, which are ordered triples of distinct variables of V. The objective is to find a linear ordering α of V that maximizes...... the number of triples whose rearrangement (under α) follows a permutation in Π. We prove that all ternary Permutation-CSPs parameterized above average have kernels with quadratic numbers of variables....

A Regularization SAA Scheme for a Stochastic Mathematical Program with Complementarity Constraints

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Yu-xin Li

2014-01-01

Full Text Available To reflect uncertain data in practical problems, stochastic versions of the mathematical program with complementarity constraints (MPCC have drawn much attention in the recent literature. Our concern is the detailed analysis of convergence properties of a regularization sample average approximation (SAA method for solving a stochastic mathematical program with complementarity constraints (SMPCC. The analysis of this regularization method is carried out in three steps: First, the almost sure convergence of optimal solutions of the regularized SAA problem to that of the true problem is established by the notion of epiconvergence in variational analysis. Second, under MPCC-MFCQ, which is weaker than MPCC-LICQ, we show that any accumulation point of Karash-Kuhn-Tucker points of the regularized SAA problem is almost surely a kind of stationary point of SMPCC as the sample size tends to infinity. Finally, some numerical results are reported to show the efficiency of the method proposed.

SU-F-T-342: Dosimetric Constraint Prediction Guided Automatic Mulit-Objective Optimization for Intensity Modulated Radiotherapy

International Nuclear Information System (INIS)

Song, T; Zhou, L; Li, Y

2016-01-01

Purpose: For intensity modulated radiotherapy, the plan optimization is time consuming with difficulties of selecting objectives and constraints, and their relative weights. A fast and automatic multi-objective optimization algorithm with abilities to predict optimal constraints and manager their trade-offs can help to solve this problem. Our purpose is to develop such a framework and algorithm for a general inverse planning. Methods: There are three main components contained in this proposed multi-objective optimization framework: prediction of initial dosimetric constraints, further adjustment of constraints and plan optimization. We firstly use our previously developed in-house geometry-dosimetry correlation model to predict the optimal patient-specific dosimetric endpoints, and treat them as initial dosimetric constraints. Secondly, we build an endpoint(organ) priority list and a constraint adjustment rule to repeatedly tune these constraints from their initial values, until every single endpoint has no room for further improvement. Lastly, we implement a voxel-independent based FMO algorithm for optimization. During the optimization, a model for tuning these voxel weighting factors respecting to constraints is created. For framework and algorithm evaluation, we randomly selected 20 IMRT prostate cases from the clinic and compared them with our automatic generated plans, in both the efficiency and plan quality. Results: For each evaluated plan, the proposed multi-objective framework could run fluently and automatically. The voxel weighting factor iteration time varied from 10 to 30 under an updated constraint, and the constraint tuning time varied from 20 to 30 for every case until no more stricter constraint is allowed. The average total costing time for the whole optimization procedure is ∼30mins. By comparing the DVHs, better OAR dose sparing could be observed in automatic generated plan, for 13 out of the 20 cases, while others are with competitive

SU-F-T-342: Dosimetric Constraint Prediction Guided Automatic Mulit-Objective Optimization for Intensity Modulated Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Song, T; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China); Li, Y [Beihang University, Beijing, Beijing (China)

2016-06-15

Purpose: For intensity modulated radiotherapy, the plan optimization is time consuming with difficulties of selecting objectives and constraints, and their relative weights. A fast and automatic multi-objective optimization algorithm with abilities to predict optimal constraints and manager their trade-offs can help to solve this problem. Our purpose is to develop such a framework and algorithm for a general inverse planning. Methods: There are three main components contained in this proposed multi-objective optimization framework: prediction of initial dosimetric constraints, further adjustment of constraints and plan optimization. We firstly use our previously developed in-house geometry-dosimetry correlation model to predict the optimal patient-specific dosimetric endpoints, and treat them as initial dosimetric constraints. Secondly, we build an endpoint(organ) priority list and a constraint adjustment rule to repeatedly tune these constraints from their initial values, until every single endpoint has no room for further improvement. Lastly, we implement a voxel-independent based FMO algorithm for optimization. During the optimization, a model for tuning these voxel weighting factors respecting to constraints is created. For framework and algorithm evaluation, we randomly selected 20 IMRT prostate cases from the clinic and compared them with our automatic generated plans, in both the efficiency and plan quality. Results: For each evaluated plan, the proposed multi-objective framework could run fluently and automatically. The voxel weighting factor iteration time varied from 10 to 30 under an updated constraint, and the constraint tuning time varied from 20 to 30 for every case until no more stricter constraint is allowed. The average total costing time for the whole optimization procedure is ∼30mins. By comparing the DVHs, better OAR dose sparing could be observed in automatic generated plan, for 13 out of the 20 cases, while others are with competitive

A new methodological development for solving linear bilevel integer programming problems in hybrid fuzzy environment

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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.

Input and output constraints-based stabilisation of switched nonlinear systems with unstable subsystems and its application

Science.gov (United States)

Chen, Chao; Liu, Qian; Zhao, Jun

2018-01-01

This paper studies the problem of stabilisation of switched nonlinear systems with output and input constraints. We propose a recursive approach to solve this issue. None of the subsystems are assumed to be stablisable while the switched system is stabilised by dual design of controllers for subsystems and a switching law. When only dealing with bounded input, we provide nested switching controllers using an extended backstepping procedure. If both input and output constraints are taken into consideration, a Barrier Lyapunov Function is employed during operation to construct multiple Lyapunov functions for switched nonlinear system in the backstepping procedure. As a practical example, the control design of an equilibrium manifold expansion model of aero-engine is given to demonstrate the effectiveness of the proposed design method.

Impact of Scribes on Physician Satisfaction, Patient Satisfaction, and Charting Efficiency: A Randomized Controlled Trial.

Science.gov (United States)

Gidwani, Risha; Nguyen, Cathina; Kofoed, Alexis; Carragee, Catherine; Rydel, Tracy; Nelligan, Ian; Sattler, Amelia; Mahoney, Megan; Lin, Steven

2017-09-01

Scribes are increasingly being used in clinical practice despite a lack of high-quality evidence regarding their effects. Our objective was to evaluate the effect of medical scribes on physician satisfaction, patient satisfaction, and charting efficiency. We conducted a randomized controlled trial in which physicians in an academic family medicine clinic were randomized to 1 week with a scribe then 1 week without a scribe for the course of 1 year. Scribes drafted all relevant documentation, which was reviewed by the physician before attestation and signing. In encounters without a scribe, the physician performed all charting duties. Our outcomes were physician satisfaction, measured by a 5-item instrument that included physicians' perceptions of chart quality and chart accuracy; patient satisfaction, measured by a 6-item instrument; and charting efficiency, measured by time to chart close. Scribes improved all aspects of physician satisfaction, including overall satisfaction with clinic (OR = 10.75), having enough face time with patients (OR = 3.71), time spent charting (OR = 86.09), chart quality (OR = 7.25), and chart accuracy (OR = 4.61) (all P values patient satisfaction. Scribes increased the proportion of charts that were closed within 48 hours (OR =1.18, P =.028). To our knowledge, we have conducted the first randomized controlled trial of scribes. We found that scribes produced significant improvements in overall physician satisfaction, satisfaction with chart quality and accuracy, and charting efficiency without detracting from patient satisfaction. Scribes appear to be a promising strategy to improve health care efficiency and reduce physician burnout. © 2017 Annals of Family Medicine, Inc.

Scheduling a maintenance activity under skills constraints to minimize total weighted tardiness and late tasks

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Djalal Hedjazi

2015-04-01

Full Text Available Skill management is a key factor in improving effectiveness of industrial companies, notably their maintenance services. The problem considered in this paper concerns scheduling of maintenance tasks under resource (maintenance teams constraints. This problem is generally known as unrelated parallel machine scheduling. We consider the problem with a both objectives of minimizing total weighted tardiness (TWT and number of tardiness tasks. Our interest is focused particularly on solving this problem under skill constraints, which each resource has a skill level. So, we propose a new efficient heuristic to obtain an approximate solution for this NP-hard problem and demonstrate his effectiveness through computational experiments. This heuristic is designed for implementation in a static maintenance scheduling problem (with unequal release dates, processing times and resource skills, while minimizing objective functions aforementioned.

Design of quadrature mirror filter bank using Lagrange multiplier method based on fractional derivative constraints

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B. Kuldeep

2015-06-01

Full Text Available Fractional calculus has recently been identified as a very important mathematical tool in the field of signal processing. Digital filters designed by fractional derivatives give more accurate frequency response in the prescribed frequency region. Digital filters are most important part of multi-rate filter bank systems. In this paper, an improved method based on fractional derivative constraints is presented for the design of two-channel quadrature mirror filter (QMF bank. The design problem is formulated as minimization of L2 error of filter bank transfer function in passband, stopband interval and at quadrature frequency, and then Lagrange multiplier method with fractional derivative constraints is applied to solve it. The proposed method is then successfully applied for the design of two-channel QMF bank with higher order filter taps. Performance of the QMF bank design is then examined through study of various parameters such as passband error, stopband error, transition band error, peak reconstruction error (PRE, stopband attenuation (As. It is found that, the good design can be obtained with the change of number and value of fractional derivative constraint coefficients.

Controlled neural network application in track-match problem

International Nuclear Information System (INIS)

Baginyan, S.A.; Ososkov, G.A.

1993-01-01

Track-match problem of high energy physics (HEP) data handling is formulated in terms of incidence matrices. The corresponding Hopfield neural network is developed to solve this type of constraint satisfaction problems (CSP). A special concept of the controlled neural network is proposed as a basis of an algorithm for the effective CSP solution. Results of comparable calculations show the very high performance of this algorithm against conventional search procedures. 8 refs.; 1 fig.; 1 tab

Assessment of satisfaction with pharmaceutical services in patients receiving antiretroviral therapy in outpatient HIV treatment setting.

Science.gov (United States)

Agu, Kenneth Anene; Oqua, Dorothy; Agada, Peter; Ohiaeri, Samuel I; Adesina, Afusat; Abdulkareem, Mohammed Habeeb; King, Rosalyn C; Wutoh, Anthony K

2014-06-01

The patient's perception and satisfaction are increasingly considered as a useful factor in the assessment of competency of health care providers and quality of care. However, these patient focused assessments are largely ignored when assessing health care outcomes. The study assessed the perception and satisfaction of patients receiving antiretroviral therapy (ART) with pharmaceutical services received in outpatient HIV treatment settings. Seventeen HIV treatment centres in Nigeria. This cross-sectional survey included 2,700 patients randomly selected from 26,319 HIV patients on ART, who received pharmaceutical services in the study setting. A study-specific Likert-type instrument was administered to the participants at point of exit from the pharmacy. Midpoint of the 5-point scale was computed and scores above it were regarded as positive while below as negative. Chi-square was used for inferential statistics. All reported p values were 2-sided at 95 % confidence interval (CI). Patient satisfaction with pharmaceutical services. Of 2,700 patients sampled, data from 1,617 (59.9 %) were valid for analysis; 62.3 % were aged 26-40 years and 65.4 % were females. The participants had received pharmaceutical services for a mean duration of 25.2 (95 % CI 24.3-26.1) months. Perception of participants regarding the appearance of pharmacy was positive while that regarding the pharmacists' efforts to solve patients' medication related problems was negative. The participants' rating of satisfaction with the waiting time to access pharmaceutical services was negative; the satisfaction decreases with increasing waiting time. However, the satisfaction with the overall quality of pharmaceutical services received was rated as positive; 90.0 % reported that they got the kind of pharmaceutical services they wanted; 98.2 % would come back to the pharmacy if they were to seek help again and would recommend services to others. The level of satisfaction was found to be associated with

Character profiles and life satisfaction.

Science.gov (United States)

Park, Hwanjin; Suh, Byung Seong; Kim, Won Sool; Lee, Hye-Kyung; Park, Seon-Cheol; Lee, Kounseok

2015-04-01

There is a surge of interest in subjective well-being (SWB), which concerns how individuals feel about their happiness. Life satisfaction tends to be influenced by individual psychological traits and external social factors. The aim of this study was to examine the relationship between individual character and SWB. Data from 3522 university students were analyzed in this study. Character profiles were evaluated using the Temperament and Character Inventory-Revised Short version (TCI-RS). Life satisfaction was assessed using the Satisfaction with Life Scale (SWLS). All statistical tests regarding the correlations between each character profile and life satisfaction were conducted using ANOVAs, t-tests, multiple linear regression models and correlation analyses. The creative (SCT) profile was associated with the highest levels of life satisfaction, whereas the depressive (sct) profile was associated with the lowest levels of life satisfaction. Additionally, high self-directedness, self-transcendence and cooperation were associated with high life satisfaction. The results of gender-adjusted multiple regression analysis showed that the effects of self-directedness were the strongest in the assessment of one's quality of life, followed by self-transcendence and cooperativeness, in that order. All of the three-character profiles were significantly correlated with one's quality of life, and the character profiles of TCI-RS explained 27.6% of life satisfaction in total. Among the three-character profiles, the self-directedness profile was most associated with life satisfaction. Our study was cross-sectional, and self-reported data from students at a single university were analyzed. The results of this study showed that, among the character profiles, the effects of self-directedness were the strongest for predicting life satisfaction. Copyright © 2014 Elsevier Inc. All rights reserved.

Patient satisfaction with cataract surgery

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Wasfi Ehab I

2008-10-01

Full Text Available Abstract Introduction Measuring the patient satisfaction is a very important issue that will help very much in improving the service provided to patients and improve the level of satisfaction. Aim To evaluate patient satisfaction with the cataract surgery service and identify any areas for improvement, determination of patient satisfaction with referral, out-patient consultation, pre-assessment clinic, surgery and post-operative care, also to report patients' comments relating to improvement in service provision. Methodology A retrospective study was undertaken for 150 patients underwent cataract surgery at Barrow General Hospital, UK, the survey sample was by postal questionnaires. We collected our data from the theatre lists for a period of 4 month. Results This study included 150 patients; the response rate was (72% 108 patients, Most patients were referred from their general practitioner 86.1%, 93 (86.1% patients were happy with the time interval from seeing their GP to eye clinic. In the eye out patient department many factors significantly affected the level of patient satisfaction, in general the more information provided for the patient the more the satisfaction. Conclusion Patient satisfaction is on important health outcome old understanding both the domains of satisfaction as well as their relative importance to patients is necessary to improve the overall quality of patient care. Meeting the doctor, presenting all relevant information and giving printed information are very important factors in improving the patient's satisfaction with cataract surgery.

A cross-lagged test of the association between customer satisfaction and employee job satisfaction in a relational context.

Science.gov (United States)

Zablah, Alex R; Carlson, Brad D; Donavan, D Todd; Maxham, James G; Brown, Tom J

2016-05-01

Due to its practical importance, the relationship between customer satisfaction and frontline employee (FLE) job satisfaction has received significant attention in the literature. Numerous studies to date confirm that the constructs are related and rely on this empirical finding to infer support for the "inside-out" effect of FLE job satisfaction on customer satisfaction. In doing so, prior studies ignore the possibility that-as suggested by the Service Profit Chain's satisfaction mirror-a portion of the observed empirical effect may be due to the "outside-in" impact of customer satisfaction on FLE job satisfaction. Consequently, both the magnitude and direction of the causal relationship between the constructs remain unclear. To address this oversight, this study builds on multisource data, including longitudinal satisfaction data provided by 49,242 customers and 1,470 FLEs from across 209 retail stores, to examine the association between FLE job satisfaction and customer satisfaction in a context where service relationships are the norm. Consistent with predictions rooted in social exchange theory, the results reveal that (a) customer satisfaction and FLE job satisfaction are reciprocally related; (b) the outside-in effect of customer satisfaction on FLE job satisfaction is predominant (i.e., larger in magnitude than the inside-out effect); and (c) customer engagement determines the extent of this outside-in predominance. Contrary to common wisdom, the study's findings suggest that, in relational contexts, incentivizing FLEs to satisfy customers may prove to be more effective for enhancing FLE and customer outcomes than direct investments in FLE job satisfaction. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Price satisfaction and producer loyalty

DEFF Research Database (Denmark)

Mutonyi, Sarah; Beukel, Karin; Gyau, Amos

2016-01-01

Purpose The purpose of this paper is to investigate which dimensions of price satisfaction influence producers’ trust in buyers and assess the mediating role of such trust in the relationship between price satisfaction and producer loyalty in fresh fruit supply chains. Design/methodology/approach......Purpose The purpose of this paper is to investigate which dimensions of price satisfaction influence producers’ trust in buyers and assess the mediating role of such trust in the relationship between price satisfaction and producer loyalty in fresh fruit supply chains. Design...... reliability, and relative price are dimensions of price satisfaction that affect producers’ trust in the buyer. Moreover, trust between the producer and the buyer is found to be a strong mediator between price satisfaction and producer loyalty. The findings support recent studies about trust and its mediating...... between the multi-dimensional nature of price satisfaction and producer loyalty with trust as a mediating variable in the business-to-business (B2B) context. Although B2B relationships have been shown to be of great importance for smallholders in enhancing business performance with their buyers, little...

三维装配几何约束闭环系统的递归分解方法%A Recursive Decomposition Algorithm for 3D Assembly Geometric Constraint System with Closed-loops

Institute of Scientific and Technical Information of China (English)

黄学良; 李娜; 陈立平

2013-01-01

Numerical methods are always employed to solve 3D assembly geometric constraint system with closed-loops which can not be decomposed by the existing decomposition methods,but their inherent inefficiency and instability can not be overcome.In this paper,with the analysis of the structural constraint of serial kinematic chain and the topological structure of geometric constraint closed-loop graph,a recursive decomposition algorithm for 3D geometric constraint system with closed-loops is proposed.The basic idea of the proposed algorithm is to introduce the equivalent geometric constraint combination to substitute the structural constraint of serial kinematic chain,and separate the geometric constraint subsystems which can be solved independently from the geometric constraint system with closed-loops.The proposed method can decompose most 3D geometric constraint closed-loop systems which are always solved by numerical method into a series of geometric constraint subsystems between two rigid bodies which can be solved by analytical or reasoning method,so that the computational efficiency and stability can be improved dramatically.Finally,a typical example has been given to validate the correctness and effectiveness of the proposed method.%由于现有几何约束分解方法无法分解三维装配几何约束闭环系统,故常采用数值迭代方法对其进行求解,但存在效率低、稳定性差等问题.为此,通过分析几何约束闭环图的拓扑结构和串联运动链的结构约束,提出基于串联运动链结构约束等价替换的三维几何约束闭环系统的递归分解方法.该方法通过不断地引入几何约束组合等价替换串联运动链的结构约束,从几何约束闭环系统中分离出可独立求解的子系统,实现几何约束闭环系统的递归分解.该方法可将此前许多必须整体迭代求解的三维几何约束闭环系统分解为一系列可解析求解的2�

Social Interactions in Job Satisfaction

OpenAIRE

Tumen, Semih; Zeydanli, Tugba

2015-01-01

The literature documents that job satisfaction is positively correlated with worker performance and pro- ductivity. We examine whether aggregate job satisfaction in a certain labor market environment can have an impact on individual-level job satisfaction. If the answer is yes, then policies targeted to increase job satisfaction can increase productivity not only directly, but through spillover externalities too. We seek an answer to this question using two different data sets from the United...

The Relationship Between Emotional Intelligence and Couples Marital Satisfaction in Three Regions of the Isfahan

Directory of Open Access Journals (Sweden)

زهره نصیری زارچ

2016-02-01

Full Text Available This study aims to thoroughly investigate the relationship between emotional intelligence and couples satisfaction performed in three regions of the Isfahan city. The research design was a descriptive correlative and the statistical population of the study consisted of all married couples who had at least one child in third grade of primary schools and from socioeconomic conditions point of view lived in rich, semi-rich and under rich areas of the city. In the research 318 samples (159 couples were chosen using random Multi-stage cluster sampling. the research aim was fundamentally based on two standard questionnaires of Bar-On emotional intelligence and ENRICH marital satisfaction. The data was analyzed using Pearson correlation method, t-test, stepwise regression. The result analysis showed that in the rich area of the components self-esteem, empathy and impulse control, in the semi-rich area Happiness, Stress Tolerance, Assertiveness, reality testing, flexibility, independence, interpersonal relationship, optimism, impulse control and problem solving and in the under rich area while Stress Tolerance and Assertiveness are the most  predictive power, in under rich area. the most significant point of the survey shows that assertiveness, reality testing, impulse control and interpersonal relationships have reversed effects, in the semi-rich area. Considering the result of the study shows that some other major factors influence couples satisfaction as well as emotional intelligence and nowadays, in the modern society satisfying providing couples satisfaction, highly depends on other social economic factor.

Patient Satisfaction in Military Dental Treatment Facilities

Science.gov (United States)

2006-03-07

the variance in regards to overall satisfaction. 15. SUBJECT TERMS Dentistry, Patient Satisfaction, Military, Consumer Satisfaction, Dental... patient satisfaction in military dental treatment facilities. Dental health is extremely important for the military as dental assets are not always... customer satisfaction is an important component of military dental care. Quarterly patient satisfaction reports are generated for each dental treatment