“Effective Production: Measuring of the Sales Effect using Data Envelopment Analysis” accepted for publication at Annals of Operations Research

Effectiveness

Chia-Yen Lee (2012 graduate of the lab) published the fifth paper from his dissertation. In a previous paper, Lee and Johnson (2014), we define effectiveness as a way to distinguish between production performance and sales performance. In this paper we extend the concept to a panel data setting and analyze how efficiency and effectiveness evolve.

Abstract

Sales fluctuations lead to variations in the output levels affecting technical efficiency measures of operations when units sold are used at an output measure. The present study uses the concept of “effective production” and “effectiveness” to account for the effect of sales on operational performance measurements in a production system. The effectiveness measure complements the efficiency measure which does not account for the sales effect. The Malmquist productivity index is used to measure the sales effects characterized as the difference between the production function associated with efficiency and the sales-truncated production function associated with effectiveness. The proposed profit effectiveness is distinct from profit efficiency in that it accounts for sales. An empirical study of US airlines demonstrates the proposed method which describes the strategic position of a firm and a productivity-change analysis. These results demonstrate the concept of effectiveness and quantifies the effect of using sales as output.

Quantifying picker blocking in a bucket brigade order picking system accepted for publication in the International Journal of Production Economics

 

BucketBrigades

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.

GAMS code for CNLS

 

gams_s

 

This file contains the set of GAMS codes for CNLS that was developed for a GAMS tutorial at EWEPA XIII held in June 2013 in Helsinki Finland. Please see the introduction of codes inside the zip file.

 

Download

IIE Transactions accepts “Modeling Dependence in Health Behaviors”

SmokeDietExer
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.

DEA Cluster at Informs

goldengatebridge

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.

The DEA Journal publishes first issue

DEAJ

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.

Johnson named Department Editor at IIE Transactions

IIETrans

Affective September 1st 2014, Andrew Johnson is the department editor for facilities and production logistics at the IIE Transactions. As the flagship journal of the Institute of Industrial Engineers, IIE Transactions publishes original high-quality papers on a wide range of topics of interest to industrial engineers who want to remain current with the state-of-the-art technologies. The refereed journal aims to foster the engineering community by publishing papers with a strong methodological focus motivated by real problems that impact engineering practice and research. Published monthly, the journal is composed of four focus issues: Design and Manufacturing, Operations Engineering and Analytics, Quality and Reliability Engineering, and Scheduling and Logistics.

IIE Transactions encourages research motivated by critical and complex engineering problems that arise in a wide variety of domains including service, public policy, health care, security, biotechnology, transportation, and others. The journal publishes papers that integrate industrial engineering with other disciplines including statistics, other engineering disciplines, computer science, biological science, and operations research. Articles covering new methodologies and state-of-the-art surveys are included in the journal.

Visit to GRIPS

2014-06-10 06.31.56

I recently visited Professor Tone at National Graduate Institute for Policy Studies (GRIPS) in Roppongi Tokyo with my daughter Juila.

Emission at Coal Fired Power Plants

The production of electricity from coal also produces SO2 and NOx. The EPA cap and trade program has been used to regulate NOx admissions.  We use a production economics approach to estimate the actual cost to producers to reduce NOx emissions.

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