Simulation of alternative approaches to relieving congestion at locks in a river transportion system

We construct a discrete-event simulation model to investigate the impact of alternative decision rules and infrastructural improvements to relieve traffic congestion in a section of the Upper Mississippi River navigation system. The model covers a series of five locks that serve commercial tows with widely different barge configurations, as well as private recreational vessels. Mixes and intensities of vessel activity are highly dependent on the time of year, day of week and time of day. The model reveals that some improvement in performance (especially in peak periods) can be achieved by scheduling lock activity with priority given to vessels with shortest average processing and lock set-up times (tempered by the time that vessels have spent in queue). Greater improvement occurs with the use of helper boats and greatest improvement occurs with enlarged locks. The alternative remedies must be evaluated with consideration of their dramatically different capital costs.     

Equivalence in two-stage DEA approaches

Data envelopment analysis (DEA) is a linear programming problem approach for evaluating the relative efficiency of peer decision making units (DMUs) that have multiple inputs and outputs. DMUs can have a two-stage structure where all the outputs from the first stage are the only inputs to the second stage, in addition to the inputs to the first stage and the outputs from the second stage. The outputs from the first stage to the second stage are called intermediate measures. This paper examines relations and equivalence between two existing DEA approaches that address measuring the performance of two-stage processes.     

DEA congestion and returns to scale under an occurrence of multiple optimal projections

Economic implications of congestion have been recently discussed in many DEA (data envelopment analysis) studies. In addition, several previous research efforts have explored a theoretical linkage between returns to scale (RTS) and the concept of congestion, because the two economic concepts are closely connected to each other. Tone and Sahoo [Tone, K., Sahoo, B.K., 2004. Degree of scale economies and congestion: A unified DEA approach. European Journal of Operational Research 158, 755–772] have published the theoretical linkage in this journal. All of the previous studies, including their research (2004), assume a unique optimal solution in the investigation on DEA-based congestion. When multiple solutions occur in DEA-based congestion measurement, the economic implications of congestion obtained from the previous research are all problematic from both theoretical and practical perspectives. To deal with the issue, this study explores how to deal with the occurrence of multiple solutions in the DEA-based congestion measurement. This study proposes a new approach for the congestion measurement and theoretically compares the proposed approach with Tone and Sahoo (2004).     

On the DEA total weight flexibility and the aggregation in cross-efficiency evaluations

This paper discusses the DEA total weight flexibility in the context of the cross-efficiency evaluation. The DMUs in DEA are often assessed with unrealistic weighting schemes in their attempt to achieve the best ratings in their self-evaluation. We claim here that in a peer-appraisal like the cross-efficiency evaluation the cross-efficiencies provided by such weights cannot play the same role as those obtained with more reasonable weights. To address this issue, we propose to calculate the cross-efficiency scores by means of a weighted average of cross-efficiencies, instead of with the usual arithmetic mean, so the aggregation weights reflect the disequilibrium in the profiles of DEA weights that are used. Thus, the cross-efficiencies provided by profiles with large differences in their weights, especially those obtained with zero weights, would be attached lower aggregation weights (less importance) than those provided by more balanced profiles of weights.     

On alternative optimal solutions in the estimation of returns to scale in DEA

Zhu and Shen [European Journal of Operational Research 81 (1995) 590] show that alternative optimal solutions in the estimation of returns to scale (RTS) are caused by a particular linear dependency among a set of extreme efficient DMUs when one employs the concept of most productive scale size [European Journal of Operational Research 17 (1984) 35] in data envelopment analysis (DEA). This paper demonstrates that the presence of weakly efficient DMUs may also lead to alternative optima and extends the results of Zhu and Shen to the entire frontier. Necessary and sufficient conditions for the presence of multiple optimal solutions for constant returns to scale (CRS) DMUs are established.     

Employing super-efficiency analysis as an alternative to DEA: An application in outpatient substance abuse treatment

A common technique for conducting efficiency analyses consists of a two-stage procedure that combines data envelopment analysis (DEA) with Tobit regression. As the DEA scores are censored at one, this method has the drawback of masking important information at the upper tail of the distribution of scores. In this paper, we present a DEA-based methodology for a two-stage efficiency analysis where the upper bound constraint of one for the efficiency scores is relaxed. This method, super-efficiency DEA, is contrasted with the two-stage approach that employs traditional, bounded DEA scores. We use data from the National Drug Abuse Treatment Survey to examine how the relative efficiency of the treatment units is affected by the organizational structures, operating characteristics and treatment modalities of a nationally representative sample of outpatient substance abuse treatment units. Our results show that the super-efficiency DEA approach offers advantages over the traditional methodology. It is easy to implement, and, for the same sample size provides more information.     

Alternative treatments of congestion in DEA: A rejoinder to Cooper,Gu, and Li

This paper is a response to Cooper, W.W., B. Gu, and S. Li: `Comparisons and Evaluations of Alternative Approaches to the Treatment of Congestion in DEA', European Journal of Operational Research (this issue), who claim that the standard FGL procedure by Färe, Grosskopf, and Lovell for dealing with congestion in DEA can (i) fail to identify congestion when it is present, and (ii) identify congestion when it is not present. We clarify the notion of congestion, and its relationship to structural efficiency and free disposability respectively, to point out that the FGL approach was originally intended for measuring structural efficiency, i.e. the influence of congestion on the efficiency of a particular production unit, not for identifying occurrence of congestion in any feasible production vector. Moreover, we point out that the result of Cooper et al. partially arises from ignorance of some key maintained assumptions underlying the FGL approach. Further, we present some counter-examples which demonstrate that the alternative approach advocated by Cooper et al. can equally fail in identification of congestion. Finally, some remarks on the influence of sampling error and errors-in-variables on the two-stage DEA approaches are presented.     

Multicriteria approaches for ranking of efficient units in DEA models

Data envelopment analysis models usually split decision making units into two basic groups, efficient and inefficient. Efficiency score of inefficient units allows their ranking but efficient units cannot be ranked directly because of their maximum efficiency. That is why there are formulated several models for ranking of efficient units. The paper presents two original models for ranking of efficient units in data envelopment analysis—they are based on multiple criteria decision making techniques—goal programming and analytic hierarchy process. The first model uses goal programming methodology and minimizes either the sum of undesirable deviations or maximal undesirable deviation from the efficient frontier. The second approach is analytic hierarchy process model for ranking of efficient units. The two presented models are compared with several super-efficiency models and other approaches for ranking decision making units in DEA models including definitions based on distances from optimistic and pessimistic envelopes and cross efficiency evaluation models. The results of the analysis by all presented models are illustrated on a real data set—evaluation of 194 bank branches of one of the Czech commercial banks.     

A one-model approach based on relaxed combinations of inputs for evaluating input congestion in DEA

This paper provides a one-model approach of input congestion based on input relaxation model developed in data envelopment analysis (e.g. [G.R. Jahanshahloo, M. Khodabakhshi, Suitable combination of inputs for improving outputs in DEA with determining input congestion — Considering textile industry of China, Applied Mathematics and Computation (1) (2004) 263–273; G.R. Jahanshahloo, M. Khodabakhshi, Determining assurance interval for non-Archimedean ele improving outputs model in DEA, Applied Mathematics and Computation 151 (2) (2004) 501–506; M. Khodabakhshi, A super-efficiency model based on improved outputs in data envelopment analysis, Applied Mathematics and Computation 184 (2) (2007) 695–703; M. Khodabakhshi, M. Asgharian, An input relaxation measure of efficiency in stochastic data analysis, Applied Mathematical Modelling 33 (2009) 2010–2023]. This approach reduces solving three problems with the two-model approach introduced in the first of the above-mentioned reference to two problems which is certainly important from computational point of view. The model is applied to a set of data extracted from ISI database to estimate input congestion of 12 Canadian business schools.     

Diagnosis and treatment of congestion in central urban areas

The development and dispersal of area-wide traffic jams is a matter of considerable social concern. Work at Middlesex University, supported by EPSRC, has enabled the construction of a simulation model with greater geographical scope than most conventional congestion simulation models. Our simulation concentrates on a holistic view of traffic jam formation in a setting of isotropic flow.In the model, traffic incidents can effectively be introduced anywhere in the network. The growth of traffic jams can be observed using a graphical display and options are included to disperse and control the formation of traffic queues.Simulation results have confirmed that the uncontrolled growth of the traffic jam is both rapid and potentially irreversible. Experiments with dispersing the traffic jam have given greater insight to the ‘gridlock’ phenomena. We suggest a number of possible, practical counter-measures, which would both inhibit the growth process and contribute to the controlled dispersion of queues in congested networks. The effectiveness of the proposed strategies is evaluated via the simulation model and as a result, we provide a coherent set of remedies which would assist in the diagnosis and treatment of central urban congestion problems.     

On the necessity of alternative approaches towards finite elastoplasticity

In order to simulate elastoplasticity within metal forming processes different approaches towards numerical implementation have been realized. Nevertheless, most of them or consider only the quasistatic case or use distinct time discretization schemes for the balance and the evolution equations. In the following, the effects of latter will be outlined on the basis of a numerical example exploiting a conventional ansatz towards finite elastoplasticity. This access should serve as a motivation for identifying why it is still important to investigate the implementation of elastoplastic phenomena beyond the well established methods. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Choosing weights from alternative optimal solutions of dual multiplier models in DEA

In this paper we propose a two-step procedure to be used for the selection of the weights that we obtain from the multiplier model in a DEA efficiency analysis. It is well known that optimal solutions of the envelopment formulation for extreme efficient units are often highly degenerate and, consequently, have alternate optima for the weights. Different optimal weights may then be obtained depending, for instance, on the software used. The idea behind the procedure we present is to explore the set of alternate optima in order to help make a choice of optimal weights. The selection of weights for a given extreme efficient point is connected with the dimension of the efficient facets of the frontier. Our approach makes it possible to select the weights associated with the facets of higher dimension that this unit generates and, in particular, it selects those weights associated with a full dimensional efficient facet (FDEF) if any. In this sense the weights provided by our procedure will have the maximum support from the production possibility set. We also look for weights that maximize the relative value of the inputs and outputs included in the efficiency analysis in a sense to be described in this article.     

Moduli spaces of model real submanifolds: Two alternative approaches

Instead of the invariant theory approach employed by Beloshapka and Mamai for constructing the moduli spaces of Beloshapka's universal Cauchy-Riemann(CR) models,we consider two alternative approaches borrowed from the theories of equivalence problem and Lie symmetries,each of which having its own advantages.Also the moduli space M(1,4) associated to the class of universal CR models of CR dimension 1 and codimension 4 is computed by means of the presented methods.     

Provider experience and technical efficiency in the treatment of stroke patients: DEA approach

This study uses Data Envelopment Analysis to examine relationships between provider experience and technical efficiency in stroke treatment patients. Using 214 hospitals grouped according to stroke treatment experience, the study examines how the inputs—average length of stay (ALOS), occupational and physical therapy charges, and all other charges—are combined to treat mild and severe stroke cases. This study finds that, on average, technical efficiency improves with experience. However, although more experienced providers are on average deemed more technically efficient, they tend to have higher charges. The study further illustrates that the gap in case severity between efficient and inefficient providers widens as experience level increases. These findings suggest there is great potential for inefficient providers to alter practice patterns to those similar to efficient providers, in order to significantly reduce aggregate expenditures.     

Returns to scale in dynamic DEA

Two different types of inputs (variable inputs and quasi-fixed inputs) are incorporated into an analytical framework of dynamic data envelopment analysis (DEA). A unique feature of the quasi-inputs is that those are considered as outputs at the current period, while being treated as inputs at the next period. The dynamic DEA can measure interdependency among consecutive periods. This study incorporates the concept of returns to scale into the dynamic DEA.     

Estimating returns to scale in DEA

This paper addresses issues of returns to scale in Data Envelopment Analysis. Starting with the model developed by Banker, but avoiding Banker's conclusions on returns-to-scale, the paper shows how two close variants (inputs and outputs oriented) of the Banker-Charnes-Cooper model can be used to provide precise estimates of returns to scale. The estimation of returns to scale for each unit is done by testing the existence of solutions in four regions defined in the neighborhood of the analyzed unit. Numerical examples and graphs are used to illustrate the proposed procedures.     

加性DEA模型与规模收益

[1]给出了用C^2R模型或C^2GS^2模型来判断决策单元的规模收益情况的定理,指出它有时失效。对DEA有效（C^2GS^2）的决策单元,本用加性DEA模型来有效地判断其规模收益情况。     

DEA模型在资金分配和管理中的应用

资金的合理使用,是经济活动中的一个非常重要的问题.利用DEA的理论、方法模型,探讨资金的使用效率、分配的合理性,以及最佳资金预算的确定方法.涉及的DEA模型结构属于非参数的最优化DEA模型,以及DEA平行网络结构.模型中所使用的生产可能集是可以评价是否呈现"拥挤"迹象的.     

Using SSM to structure the identification of inputs and outputs in DEA

This paper reports on an innovative combination of hard and soft methods—soft systems methodology (SSM) with data envelopment analysis (DEA). Problems in defining and agreeing appropriate inputs and outputs for DEA led to the use of SSM as a way or producing a comprehensive and systemic database of performance indicators. The contributions of the paper are: the use of SSM to improve DEA specifications; conceptual clarifications within both SSM and DEA; and an innovative example of multimethodology. These developments are illustrated through a study evaluating the performance of the basic research institutes of the Chinese Academy of Sciences.