Soondo Hong (a 2010 graduate of the lab) continues to develop extension to his dissertation work which modeled and qualified picker blocking in narrow aisle order picking systems. He has now extend this work to consider bucket brigade operations. This paper addresses some of the unique challenges of the bucket brigade setting.

Abstract

This paper we model and quantify picker blocking in bucket brigade order picking systems (OPSs). Bucket brigades improves throughput and reduces variability in OPSs. However, each order picking trip fills different orders and creates workload variation per order. We show that bucket brigade order picking experiences picker blocking when there is a workload imbalance per pick face. We derive a closed-form solution to quantify the level of blocking for two extreme walk speed cases. Additional simulation comparisons validate the picker blocking model which includes backward walk and hand-off delays. We identify the relationship between picker blocking in bucket brigade OPSs and picker blocking in a circular-aisle abstraction of an OPSs in which backward walk and hand-off delays as well as forward walk speed are considered. Our analytical model and simulations verify that aggregating orders into batches smoothes the workload variation by pooling the randomness of picks in each order and that slowest-to-fastest picker sequencing modulates picker blocking between two pickers, i.e., the interaction between neighboring pickers.

Brandon Pope‘s (2011 graduate of the lab) dissertation is about modeling incentives in healthcare systems. This paper is a critical component where he explores the dependencies in health behaviors (diet, exercise and smoking) modeling as binary decisions and explores modeling the dependence through either joint attraction functions or probabilistic dependence. We find some evidence of superior performance of the joint attraction function approach for our data.

Abstract
The prediction and control of distributed healthcare behaviors within a population such as smoking, diet, and physical activity are of great concern to those who pay for healthcare, including employers, insurers, and public policy makers given the significant effect on costs. In considering the selection of multiple health behaviors, the nature of dependence between behaviors must be considered because simplifying assumptions such as independence are untenable. Using data from the National Heart, Lung, and Blood Institute, we find strong evidence to reject the hypothesis of independence between the aforementioned behaviors, while finding some evidence of conditional independence. In this paper, several alternatives to the assumption of independence are presented, each of which signicantly improves the ability to predict combined behavior. We present models of dependence through marginal probabilities and, taking inspiration from non-expected utility maximizing behavior, through attractions to behavioral alternatives. We find that consistently healthy (or unhealthy) combinations of behaviors are more likely to occur relative to the assumption of independence. We discuss how our results could be used in designing policies to curtail costs and improve health.

Informs held its Annual meeting in San Francisco this year from November 9-12. The DEA track had 8 invited session and 4 contributed sessions, with more than 40 papers presented. This is largest the track has been in the past 4 years.

The Informs meeting will be held in Philadelphia from November 1-4. I hope everyone will be able to join again. If you are interested in presenting in the DEA cluster at Informs, please contact me.

After many years in development, the DEA Journal published its first issue which was available at the NOW Publishing booth at Informs. This provides another field specific outlet for efficiency and productivity papers.

The mission of the new journal is to publish the best and most insightful papers on the theory and practice of Data Envelopment Analysis (DEA). The DEA Journal is the official journal of the International Data Envelopment Analysis Society (iDEAs). Click here, for more details and access to the articles in the first issue.