This paper considers the design and analysis of algorithms for vehicle routing and scheduling problems with time window constraints. Given the intrinsic difficulty of this problem class, approximation methods seem to offer the most promise for practical size problems. After describing a variety of heuristics, we conduct an extensive computational study of their performance. The problem set includes routing and scheduling environments that differ in terms of the type of data used to generate the problems, the percentage of customers with time windows, their tightness and positioning, and the scheduling horizon. We found that several heuristics performed well in different problem environments; in particular an insertion-type heuristic consistently gave very good results.

https://www.jstor.org/stable/pdfplus/170697.pdf

Algorithms for the vehicle routing and scheduling problems with time window constraints

Estimation and inference in two-stage, semi-parametric models of production processes

Data envelopment analysis (DEA) - Thirty years on

Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in taiwan

https://www.grips.ac.jp/r-center/wp-content/uploads/07-08.pdf

Network DEA: A slacks-based measure approach

We evaluate the efficiency with which the 50 U.S. states convert public and private spending into jobs. We use a Data Envelopment Analysis model in which the states are the decision-making units; federal, state, private sector spending are the inputs; and jobs is the output. We find that 38 percent of states are efficient. However, there is considerable variation in efficiency, suggesting that the effect on job creation depends on where the money is spent. We find that high population states more likely to be efficient than low population states, while states located in the Southeast region are less likely to be efficient relative to states located elsewhere. We find that states with higher proportions of their workforce in the Professional and Business Services, Government, or Education and Health Services super-sectors are less likely to be efficient relative to states with lower proportions of their workforce in these super-sectors.

/pdf/measuring-the-efficiency-of-states-to-convert-government-and-3eky4q22pu.pdf

Measuring the Efficiency of States to Convert Government and Private Expenditures into Jobs

Organizations are complex and have many goals while almost all analytical tools measure performance using only one goal. Thus, analysts often rely on multiple analytical tools to produce a bewildering array of performance measures that often lack internal consistency and a clear focus. In this article, we show how Data Envelopment Analysis (DEA) builds a performance frontier (analogous to a production frontier) that measures organizational performance in the presence of multiple organizational measures. The DEA frontier produces target values for each organizational measure based on the observed performance of organizations in the comparison set. In addition, DEA provides factor performance levels for each performance measure for each organization and can detect circumstances in which an organization has a strong overall performance measure but still has weaknesses in one or more measures. We will illustrate this approach with applications to several examples using real data. This article is protected by copyright. All rights reserved. 

Using Data Envelopment Analysis to Measure and Improve Organizational Performance

OBJECTIVE We propose an alternative to the Risk Adjusted Mortality Rate (RAMR), about which we identify four serious concerns. We apply our method to cardiac surgery. DESIGN We present a methodology that uses the upper and lower tail probabilities (UTP/LTP) of the binomial distribution to screen for poor/high performing providers. STUDY SETTING The New York State Department of Health (NYS DOH) publicly releases data on all cardiac surgery patients in the state. We download cardiac surgery data from the NYS DOH website for the years 2011 through 2013. The state's objective is to identify poorly performing hospitals and surgeons and thereby reduce deaths. NYS employs the RAMR. RESULTS The UTP/LTP approach agrees with the RAMR in its classification of all 132 surgeons and all 40 hospitals. However, performance is a continuous construct and strict categorization can lead to failure to identify marginal providers. CONCLUSIONS Our methodology addresses all four concerns regarding the RAMR. The UTP/LTP approach avoids inappropriate hypothesis testing and is consistent with standard statistical theory and practice in its approach to case volume. It does not require confidence intervals and it applies to all providers regardless of case volume.

A Novel Approach to Evaluating Cardiac Surgery Providers: An Alternative to the RAMR.

Finding the optimal policy for multi-period perishable inventory systems requires solving computationally-expensive stochastic dynamic programs (DP). To avoid the difficulty of solving DP models, we propose a framework that uses an externality term to capture the long-term impact of ordering decisions on the average cost over an infinite horizon. By approximating the externality term, we yield a tractable approximate optimality condition, which is solved through standard marginal analysis. The resulted policy is near-optimal in long-run average cost and ordering decisions.

Thomas R. Sexton

Papers

Measuring the Efficiency of States to Convert Government and Private Expenditures into Jobs

Using Data Envelopment Analysis to Measure and Improve Organizational Performance

A Novel Approach to Evaluating Cardiac Surgery Providers: An Alternative to the RAMR.

A Marginal Analysis Framework to Incorporate the Externality Effect of Ordering Perishables