关于二胡演奏中情感处理的几点思考

二胡是我国民族乐器,号称“东方的小提琴”,表现力强、感情细腻。20世纪初,经我国国乐大师刘天华先生毕生的努力,二胡从民间自流状态纳入到艺术的领域,在普通高等音乐院校占一席之地,并创立现代二胡学派。目前二胡演奏艺术在音乐教育中已经占有了相当重要的地位,以它为载体,作曲家利用它来表达自己的内心的真实情感。本文通过对二胡乐曲的时代特征、地域民族特征、人物形象特征等几个不同方面的阐述,揭示了在二胡演奏过程中情感处理方面的重要性。     

A Bicriterion Maximal Covering Location Formulation Which Considers the Satisfaction of Uncovered Demand

There have been many applications of the maximal covering location problem (MCLP). An underlying assumption of the MCLP is that demand not covered (i.e., not within a prespecified maximal distance of a facility) is not served. This may be an unrealistic assumption in many location planning scenarios, especially in the public sector. For example, in cases such as fire protection or ambulance service, calls not technically covered will still be serviced. The MCLP, however, does not consider the distances or travel times necessary to service such demand. This paper presents a bicriterion locational covering model which explicitly considers the travel distance or time necessary to service demand not within the maximal covering distance of a facility. The model may be used to generate noninferior (Pareto optimal) siting configurations which demonstrate the inherent trade-offs between a siting scheme designed to maximize total coverage and one designed to minimize total travel time for uncovered demand to reach its nearest facility. In addition, it is shown that for any particular weighting scheme on the two objectives, the problem can be solved as a p-median problem; a problem for which several efficient solution methods exist.     

Complexity Factors and Intuition-based Methods for Facility Network Design

Logistics managers frequently utilize decision support systems (DSS) to make facility network design decisions. Many DSS do not provide optimization capabilities, but instead rely on scenario evaluation as a means for developing solutions. We experimentally assessed the performances of decision makers, including experienced managers, who used four variants of a scenario evaluation-based DSS to solve realistically sized network design problems of varying complexities. Complexity factors included DSS attributes, problem size, network types, and demand dispersion patterns. Decision makers' performances were assessed relative to optimal solutions. Overall, the decision makers generated relatively high-quality solutions using the DSS variants. The type of design problem solved did not significantly impact problem-solving performance. However, performance degraded and variability in solution quality escalated as problem size was increased. The availability of incremental solution cost improvement cues in the DSS significantly improved solution quality and reduced performance variability. Iconic graphic enhancements to the DSS did not consistently affect performance. However, significant interactions existed among the effects of DSS graphics capabilities, DSS information cues, and problem attributes.     

Multiperiod Capacity Expansion in Globally Dispersed Regions

Multiperiod capacitated location (MCL) models specify where and when capacity expansions should be made, and how large they should be. The MCL model developed in this paper incorporates a shift from manufacturing for overseas markets to manufacturing in overseas markets. While MCL models generally have not provided lower bounds on the optimal solution, the methodology of this paper provides both upper and lower bounds. Computational results are given for problems involving up to 200 locations/destinations and 10‐year planning horizons. Near‐optimal solutions are provided in reasonable computing times with average convergence less than 2%. Representative variations in cost between regions are simulated in the test problems, and the managerial implications of alternative diversification strategies are also assessed.     

DYNAMIC LOCATION MODELING FOR PUBLIC-SECTOR FACILITIES: A MULTICRITERIA APPROACH*

A major complication in the planning of facility systems and in the analysis of their locational configurations is the fluctuating nature of the systems they serve. Locations identified now, based on current conditions, may be undesirable in the future, and those based on future conditions may be undesirable now. This paper proposes a general methodology using multiobjective analysis to plan public-sector facility systems operating in a dynamic environment. A model is developed for the specific case of locating emergency services and an illustrative example is presented.     

Locating Emergency Warning Sirens

In this paper, we report on the application of set covering and maximal covering location models to the problem of locating emergency warning sirens in a midwestern city. Two siren types are available, each having different costs and covering radii. Using a modified version of the set covering location model, we analyze the cost implications of several policy options being considered by the city's planners. Results of the study indicate that location covering models can be powerful and efficient tools in the design of such systems, and their use can lead to significant cost savings. In addition, such models provide decision makers the flexibility to examine the inherent costs associated with various policy options.     

The Influences of User Characteristics on Performance in a Logistics DSS Application

Decision Support Systems (DSS) are widely used in logistics decision applications, and a large number and variety of systems are commercially available. We investigate the contributions of user characteristics including experiences, data preferences, intuition, and effort to decision performance in a logistics DSS context. The study includes a laboratory experiment in which decision makers with varied experiences used a DSS to make facility network design decisions for problems of varying complexity. Two variants of the DSS are utilized in order to examine the interactions of a DSS decision aid with user characteristics. We find that intuition and effort are associated with decision-making performance. High analytic ability is not related to intuition, however. Education and previous experience are associated with performance. Yet these characteristics are also unrelated to intuition. Decision makers who highly value disaggregated data provided by the DSS tend to perform poorly. Also, the results suggest that the effects of users' experiences and preferences on performance are influenced by an analytical decision aid.