Schwartz, Nancy Lou (1939–1981)

The purpose of this study is to develop economic incentives for consumers of care services that will lead to efficient delivery of care of any specified quality. The importance of this investigation derives from the rising cost of services and the resulting quest for new organizational structures for their delivery. These new structures are supposed to utilize resources more efficiently than current institutions and thereby make services available to a broader class of consumers. The authors posit a care delivery that provides two kinds of services-preventive care and treatment. Provision of each kind of care is costly. The individual selects a level of preventive care that maximizes expected utility, where utility is a function of disposable income. It is shown that the level of preventive care chosen by the individual will not in general be appropriate for the minimization of the total costs of care. The possibility of selecting a payment scheme for services is investigated, ranging from full prepayment to fee-for-service compatible with minimization of expected total cost. The main result is the development of such a payment plan. Few issues capture the public's attention more than care. This is not surprising in view of rapidly rising care costs and the realization that sooner or later all will need such services. In addition, ghetto dwellers, rural inhabitants, Morton I. Kamien, Ph.D., is Professor and Chairman of the Department of Managerial Economics and Decision Sciences in Northwestern University. He was formerly on the faculty of the Graduate School of Industrial Administration of Carnegie-Mellon University. Nancy L. Schwartz, Ph.D., is Professor of Managerial Economics in Northwestern University. She was formerly on the faculty of the Graduate School of Industrial Administration of Carnegie-Mellon University. Professors Kamien and Schwartz have coauthored articles which have appeared in Econometrica, American Economic Review, Management Science, Journal of Economic Theory, and Journal of Applied Probability. Financial assistance of the Health Services Research Center of the Hospital Research and Educational Trust, and Northwestern University is gratefully acknowledged. The authors retain all responsibility for views expressed. This paper was submitted in August, 1972. and the aged, among others have special concerns regarding accessibility of medical services, apart from and in addition to cost. All this has prompted the government to seek ways of supplementing and improving the present essentially private system of care delivery. Among the measures already undertaken, the best known provide insurance coverage for a variety of medical expenses for the poor and the aged. More direct measures are contemplated, including Federally subsidized health services planning and delivery systems. This paper deals with an economic aspect of such a system. There will be multiple criteria in selecting an organizational structure for a care delivery system. For example, one may ask whether the organizational structure is conducive to providing a mix of services consistent with the needs of its constituency. Will it be able to meet changing needs of its clients? Does it pro-

Focus on Authors

The power systems of the future - smart grid - will see an increase in both renewable energy sources and load demand increasing the need for fast dynamic reconfiguration of system parameters. Advanced simulation capabilities are needed to support future planning and to implement real-time dynamic optimization. To achieve this, intelligent algorithms are needed for prediction and system monitoring along with advanced hardware to provide speed. FASTSIM capabilities allows for fast prediction of how a proposed reconfiguration will affect the system permitting implementation of radical reconfigurations without fear of disturbing vital system settings since the proposed solution will be checked before being implemented. Power systems will need to be continuously monitored for power losses and system contingencies. A combination of system states prediction, dynamic load flow, system optimization, and solution stability checking will allow for a more reliable, affordable and clean power grid. This paper presents a dynamic optimization method based on adaptive critic designs for the smart grid environment.

Contributors

Dynamic optimization of ship energy efficiency considering time-varying environmental factors

Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design parameters. Aiming at the spindle unit of refitted machine tool for solid rocket,the vibration acceleration of tool is taken as objective function,and the electromechanical system design parameters are appointed as design variables. Dynamic optimization model is set up by adopting Lagrange-Maxwell equations,Park transform and electromechanical system energy equations. In the procedure of seeking high efficient optimization method,exponential function is adopted to be the weight function of particle swarm optimization algorithm. Exponential inertia weight particle swarm algorithm(EPSA),is formed and applied to solve the dynamic optimization problem of electromechanical system. The probability density function of EPSA is presented and used to perform convergence analysis. After calculation,the optimized design parameters of the spindle unit are obtained in limited time period. The vibration acceleration of the tool has been decreased greatly by the optimized design parameters. The research job in the paper reveals that the problem of dynamic optimization of electromechanical system can be solved by the method of combining system dynamic analysis with reformed swarm particle optimization. Such kind of method can be applied in the design of robots,NC machine,and other electromechanical equipments.

An enhanced scatter search method for the global dynamic optimization of nonlinear processes using the control vector parametrization (CVP) approach is presented. Sharing some features of the scatter search metaheuristic, this new method presents a simpler but more effective design which helps to overcome typical difficulties of nonlinear dynamic systems optimization such as noise, flat areas, nonsmoothness, and/or discontinuities. This new algorithm provides a good balance between robustness and efficiency in the global phase, and couples a local search procedure to accelerate the convergence to optimal solutions. Its application to four multimodal dynamic optimization problems, compared with other state-of-the-art global optimization algorithms, including an advanced scatter search design, proves its efficiency and robustness, showing a very good scalability.

Regional rail transit, formed by the economic integration needs of urban agglomerations, is a comprehensive rail transit system with different kinds of transportation systems. Nowadays, although different kinds of rail transit systems are developing rapidly and the facilities are comprehensive, there is a lack of effective dynamic coordination among the various standards and subsystems. Consequently, the regional rail transit network cannot meet higher overall transport capacity and safety requirements. To solve this problem, this paper proposes a dynamic collaborative optimization method for regional rail transit based on passenger route guidance and train scheduling. This method takes the minimization of the maximum peak value of the road network dynamic risk as the optimization objective to establish a mathematical optimization model. The rail transit road network in the Chengdu–Chongqing area is taken as an example to establish a road network simulation model. Through the combination of the simulation model and intelligent optimization algorithms, the entire multi-standard rail transit network is dynamically optimized for train dispatching and passenger flow guidance. Finally, the effectiveness of the method is verified by the simulation of the actual rail transit network.

With the development of science and technology, there has been growing the grid size, the growing demand for electricity and the extent of increasing the electricity market.In this paper, a mathematical morphology and genetic algorithm based dynamic reactive power optimization method for distribution network is proposed.By means of constructing mathematical morphology filter, the binary image composed by allelic genes of chromosome is filtered and the problem that deals with the action times of voltage regulating devices for compensation is turned into filtering problem of discrete binary image.With further automate scheduling, distribution automation and unmanned substation reactive power optimization of distribution line running made an urgent request.Reactive power optimization can improve the voltage passing rate, increasing the reliability of the system, the power quality, and the system runs the security and economy of the perfect combination, very broad application prospects.

Optimal grade transition and selection of closed-loop controllers in a gas-phase olefin polymerization fluidized bed reactor

Catherine Elizabeth Snow, born December 14, 1945, in Toledo, Ohio, received her BA in psychology in 1966 from Oberlin College in Oberlin, Ohio, and was awarded highest honors, Phi Beta Kappa, for her thesis titled “Effects of Luminance and Contrast on Contour Dependent Color After‐Effects.” In 1967, her thesis “Conjunctive and Disjunctive Thinking in Children” led to an MA in psychology from McGill University in Montreal, Quebec. In 1971 McGill University awarded Snow a PhD in psychology for her thesis “Language Acquisition and Mothers' Speech to Children.”

A numerical method of structural dynamic shape optimization is presented by using reproducing kernel particle method (RKPM), by which the mesh distortion that exists in shape optimal method based on finite element can be eliminated completely and the optimal model for structural dynamic optimization design is built. The discreteness-based design sensitivity analysis in both natural frequency and dynamic response is proposed by using direct differentiation method and discrete derivatives on the basis of structural dynamic analysis, in which the penalty method is employed into imposing the essential boundary conditions, and the derivatives of shape functions with respect to design variables are derived. The algorithm of dynamic sensitivity analysis is testified by numerical example, and the numerical results obtained are in good agreement with those obtained using semi-analytical method and global finite differences method. Finally, by integrating the algorithm mentioned based on RKPM with parameterized descriptive method of boundary shape, two examples for structural dynamic shape optimization are performed.

The steering system has an important impact on the energy consumption, maneuverability, and driving stability of vehicles. In order to improve the system’s comprehensive performance, this research takes electro-hydraulic active steering (EHAS) system as the design object and utilizes the dynamic constraints collaborative optimization (DCCO) method for the parametric optimization of the EHAS system. Steering modality is combined with dynamic performance evaluation indices such as steering energy consumption, steering road feel, steering sensibility, and steering stability, to evaluate the comprehensive performance of the EHAS system. Then, a hierarchical multidisciplinary optimization model of EHAS system is established based on DCCO method, which takes the comprehensive performance of steering system as the overall system and steering energy consumption, steering road feel, steering sensibility, and steering modality as subsystems respectively. The multidisciplinary performance evaluation indices of EHAS system are derived for the first time, among which the evaluation index of steering modality is obtained by combining of design of experiments (DOE) design method and response surface method. The optimization results show that the EHAS system optimized by DCCO method can effectively improve steering energy consumption, steering road feel, and steering sensibility.

High-performance computing (HPC) systems consume huge amount of power, while bringing about higher operational costs, lower reliability. Power optimization has become an important target for HPC system design. Network energy optimization is significant for the energy optimization of the whole system. In this paper, the dynamic energy optimization method of network with MPI communication operation is presented, which can find MPI operation implementation with the least network energy by accurate dynamic energy estimation, and reduce the energy consumption of network. Taking barrier as an example, we validate the correctness and usefulness of the dynamic energy optimization method of network.

A dynamic performance analysis and optimization method of the horizontal machining center based on contact theory was presented in this paper. The contact stiffness models of ball screw joints and guide joints were proposed based on contact theory, and the predicted values are in good agreement with the experimental results. In particular, the prediction errors of the ball screw joints are within 2.8% compared with the 13 sets of experimental results of THK Company for 26 types. The analysis principle of dynamic performance was given by modal theory. With the goal of reducing the sum of modal flexibility and strengthening the weak modes, static flexibility analysis, modal flexibility analysis, and potential energy distribution analysis were carried out. By studying the effects of geometric parameters, material parameters, surface parameters, and assembly parameters on weak parts, the most effective parameters for optimization were determined. The sensitive parameters were improved from type selection, surface technology, assembly process, and structural improvement. The optimization results showed that the modal flexibility of the weak modes has been reduced by 51.80%, 38.44%, 46.58%, and 27.21%, respectively, the modal flexibility ratios have been reduced by 17.27%, 5.19%, 27.11%, and 2.45%, respectively, and the 1st, 3rd, 4th, and 7th natural frequencies of the horizontal machining center have increased by 26.64%, 11.38%, 4.14%, and 4.55%, respectively. The effects of various parameters on the horizontal machining center were also discussed, which can provide reference for further optimization and research.