# Andrew L. Johnson

• European Journal of Operational Research
• 2011
Model misspecification has significant impacts on Data Envelopment Analysis (DEA) efficiency estimates. This paper discusses the four most widely-used approaches to guide variable specification in DEA. We analyze Efficiency Contribution Measure (ECM), Principal Component Analysis (PCA-DEA), a regression-based test, and bootstrapping for variable selection(More)
• Operations Research
• 2010
Data Envelopment Analysis (DEA) is known as a nonparametric mathematical programming approach to productive efficiency analysis. In this paper we show that DEA can be alternatively interpreted as nonparametric least squares regression subject to shape constraints on frontier and sign constraints on residuals. This reinterpretation reveals the classic(More)
• European Journal of Operational Research
• 2013
Convex Nonparametric Least Squares (CNLSs) is a nonparametric regression method that does not require a priori specification of the functional form. The CNLS problem is solved by mathematical programming techniques; however, since the CNLS problem size grows quadratically as a function of the number of observations, standard quadratic programming (QP) and(More)
• 2008 Winter Simulation Conference
• 2008
This paper proposes an analytical model useful in the design of conveyor-based Automated Material Handling Systems (AMHS) to support semiconductor manufacturing. The objective is to correctly estimate the work-in-process on the conveyor and assess the system stability. The analysis approach is based on a queuing model, but takes into account details of the(More)
This paper discusses an order batching formulation and heuristic solution procedure suitable for a largescale order picking situation in parallel-aisle picking systems. Order batching can decrease the total travel distance of pickers not only through reducing the number of trips, but also by shortening the length of each trip. In practice, some order(More)
• J. Optimization Theory and Applications
• 2015
The standard assumption in the efficiency literature, that firms attempt to produce on the production frontier, may not hold in markets that are not perfectly competitive, where the production decisions of all firms will determine the market price, i.e., an increase in a firm’s output level leads to a lower market clearing price and potentially lower(More)
• European Journal of Operational Research
• 2011
Regression and linear programming provide the basis for popular techniques for estimating technical efficiency. Regression-based approaches are typically parametric and can be both deterministic or stochastic where the later allows for measurement error. In contrast, linear programming models are nonparametric and allow multiple inputs and outputs. The(More)