Works (28)

Updated: November 1st, 2024 05:32

2024 conference paper

WIP: Piloting a Comprehensive Needs Assessment to Enhance Engineering Faculty Development

2024 ASEE Annual Conference & Exposition Proceedings. Presented at the 2024 ASEE Annual Conference & Exposition, Portland, Oregon.

By: M. Morin n, J. Ducoste n & E. Brown n

Event: 2024 ASEE Annual Conference & Exposition at Portland, Oregon on June 23, 2024

Sources: Crossref, NC State University Libraries, ORCID
Added: August 8, 2024

2023 conference paper

Developing Micro-credentials to Infuse Cybersecurity into Technician Education

Proceedings of the 2023 ASEE Annual Conference. Presented at the 2023 ASEE Annual Conference, Baltimore, MD.

By: E. Brown & Z. Hubbard

Event: 2023 ASEE Annual Conference at Baltimore, MD on June 25-28, 2023

Sources: NC State University Libraries, ORCID
Added: July 17, 2023

2021 journal article

Exploring Barriers to the Use of Evidenced-Based Instructional Practices

Journal of College Science Teaching, 51(2), 56–66. https://www.nsta.org/journal-college-science-teaching/journal-college-science-teaching-novemberdecember-2021/exploring

By: G. Gardner, E. Brown, Z. Grimes & G. Bishara

Sources: NC State University Libraries, ORCID
Added: June 20, 2023

2015 conference paper

Writing and Implementing Successful NSF S-STEM Proposals

2015 ASEE Annual Conference and Exposition Proceedings. Presented at the 2015 ASEE Annual Conference and Exposition.

By: E. Brown*, M. Farwell* & A. Kennedy*

Event: 2015 ASEE Annual Conference and Exposition

UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2014 chapter

A Comparison of Seasonal Regression Forecasting Models for the U.S. Beer Import Market

In Advances in Business and Management Forecasting (pp. 161–177).

By: J. Kros, W. Rowe & E. Brown*

author keywords: Seasonality; spreadsheet regression models; forecasting U. S. beer imports; demand estimation
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2013 chapter

Census Forecasting in an Inpatient Rehabilitation Facility

In Advances in Business and Management Forecasting (pp. 3–13).

By: J. Kros, E. Brown*, R. Joyner, P. Heath & L. Helms

author keywords: Inpatient census prediction; health care forecasting; rehabilitation; predictive modeling
TL;DR: This research addresses the issue of patient admissions in an inpatient rehabilitation facility attached to an 861 bed level-one trauma hospital and develops a predictive model for the IRF's Census to assist in resource planning. (via Semantic Scholar)
UN Sustainable Development Goal Categories
8. Decent Work and Economic Growth (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2013 chapter

Using process capability analysis and simulation to improve patient flow

In Applications of Management Science (pp. 219–229).

By: K. Keeling, E. Brown* & J. Kros

author keywords: Simulation; optimization; patient flow; process capability
TL;DR: Recommendations to the facility for alternative ways to schedule and allocate its resources in order to meet its current service level goal were given. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2012 book

Health Care Operations and Supply Chain Management

San Francisco, CA: John Wiley & Sons.

By: J. Kros & E. Brown

Sources: NC State University Libraries, ORCID
Added: September 27, 2020

2012 chapter

Using Process Mapping and Capability Analysis to Improve Room Turnaround Time at a Regional Hospital

In Decision Making In Service Industries: A Practical Approach (pp. 240–259).

By: J. Kros & E. Brown

Sources: Crossref, NC State University Libraries
Added: September 14, 2023

2010 journal article

Reducing Room Turnaround Time at a Regional Hospital

Quality Management in Health Care, 19(1), 90–102.

By: E. Brown* & J. Kros*

MeSH headings : Economics, Hospital; Efficiency, Organizational; Housekeeping, Hospital / organization & administration; Humans; North Carolina; Organizational Case Studies; Patients' Rooms / organization & administration; Time Factors
TL;DR: Process-mapping techniques as well as heuristic approaches integrated into an existing bed-tracking system are examined and an examination of the current room-cleaning procedures is included to verify that the improved room turnaround time did not come at the expense of infection control. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2009 journal article

Grouping Genetic Algorithm for the Blockmodel Problem

IEEE Transactions on Evolutionary Computation, 14(1), 103–111.

By: T. James*, E. Brown* & C. Ragsdale*

author keywords: Blockmodel; grouping genetic algorithm (GGA); social network analysis
TL;DR: Testing on numerous examples from the literature indicates a grouping genetic algorithm (GGA) is an appropriate tool for solving this type of problem, and provides good solutions, even to large-size problems, in reasonable computational time. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2009 conference paper

The Engineering Math Committee: A Successful Collaboration at East Carolina University

Proceedings of the 2009 ASEE National Conference. Presented at the 2009 ASEE National Conference, Austin, Texas.

By: E. Brown & H. Ries

Event: 2009 ASEE National Conference at Austin, Texas

Sources: NC State University Libraries, ORCID
Added: September 27, 2020

2008 conference paper

An Example of Vertical Integration in an Engineering Curriculum

Proceedings of the 2008 ASEE Southeast Section Meeting. Presented at the 2008 ASEE Southeast Section Meeting, Memphis, TN.

By: E. Brown, R. Williams & P. Bedenbaugh

Event: 2008 ASEE Southeast Section Meeting at Memphis, TN

Sources: NC State University Libraries, ORCID
Added: September 27, 2020

2007 journal article

A GROUPING GENETIC ALGORITHM FOR THE MULTIPLE TRAVELING SALESPERSON PROBLEM

International Journal of Information Technology & Decision Making, 06(02), 333–347.

By: E. Brown*, C. Ragsdale* & A. Carter*

author keywords: multiple traveling salesperson problem; grouping genetic algorithm; genetic algorithm
TL;DR: This research demonstrates that the GGA with its new chromosome representation is capable of solving a variety of MTSP problems from the literature and can outperform the traditional encodings of previously published GA methods. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2006 journal article

Grouping efficiency measures and their impact on factory measures for the machine-part cell formation problem: A simulation study

Engineering Applications of Artificial Intelligence, 20(1), 63–78.

By: K. Keeling*, E. Brown* & T. James*

author keywords: grouping genetic algorithm; grouping efficacy; grouping capability index
TL;DR: Results indicate that it is not always the case that a ''more efficient'' machine/part cell formation leads to significant changes or improvements in factory measures over a ''less efficient'' cell formation. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2005 conference paper

A Formulation for Solving the Assembly Line Balancing Problem Using a Genetic Algorithm

Proceedings of the 2005 Spring Simulation Multiconference (San Diego, CA). Presented at the 2005 Spring Simulation Multiconference, San Diego, CA.

By: E. Brown & R. Sumichrast

Event: 2005 Spring Simulation Multiconference at San Diego, CA

Sources: NC State University Libraries, ORCID
Added: September 27, 2020

2005 journal article

A hybrid grouping genetic algorithm for the cell formation problem

Computers & Operations Research, 34(7), 2059–2079.

By: T. James*, E. Brown* & K. Keeling*

author keywords: machine-part cell formation; grouping genetic algorithm; heuristics
TL;DR: The hybrid grouping genetic algorithm developed performs well on all test problems, exceeding or matching the solution quality of the results presented in previous literature for most problems. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2004 journal article

A grouping genetic algorithm for registration area planning

Omega, 34(3), 220–230.

By: M. Vroblefski* & E. Brown*

author keywords: artificial intelligence; heuristics; stochastic programming; telecommunications
TL;DR: The proposed grouping genetic algorithm, GGARAP, is robust and finds good solutions for the registration area planning problem for a wide range of network situations and the computational effort involved in runningGGARAP is minimal. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2004 journal article

A grouping genetic algorithm for the microcell sectorization problem

Engineering Applications of Artificial Intelligence, 17(6), 589–598.

By: E. Brown* & M. Vroblefski*

author keywords: code-division multiple-access; dynamic channel allocation; genetic algorithm; grouping genetic algorithm; microcell sectorization; wireless communication networks
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2004 journal article

Evaluating performance advantages of grouping genetic algorithms

Engineering Applications of Artificial Intelligence, 18(1), 1–12.

By: E. Brown* & R. Sumichrast*

author keywords: genetic algorithm; grouping genetic algorithm; grouping problems; constrained optimization; bin packing; machine-part cell formation; assembly line balancing
TL;DR: Empirical tests of the performance of GA and GGA in three domains which have substantial, practical importance, and which have been the subject of considerable academic research are described. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2004 conference paper

Formulating the Multiple Traveling Salesperson Problem for a Grouping Genetic Algorithm

Proceedings of the 2004 Institute of Industrial Engineers Annual Conference. Presented at the 2004 Institute of Industrial Engineers Annual Conference, Houston, TX.

By: E. Brown, C. Ragsdale & A. Carter

Event: 2004 Institute of Industrial Engineers Annual Conference at Houston, TX

Sources: NC State University Libraries, ORCID
Added: September 27, 2020

2004 journal article

On Modeling Line Balancing Problems in Spreadsheets

INFORMS Transactions on Education, 4(2), 45–48.

By: C. Ragsdale* & E. Brown*

TL;DR: This paper demonstrates how a similar technique can be used to create efficient spreadsheet models for line balancing problems with greatly simplifying the handling of precedence relations among activities. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2003 conference paper

A Grouping Genetic Algorithm for the Assembly Line Balancing Problem

Proceedings of the 2003 Institute of Industrial Engineers Annual Conference. Presented at the 2003 Institute of Industrial Engineers Annual Conference, Portland, Oregon.

By: E. Brown & R. Sumichrast

Event: 2003 Institute of Industrial Engineers Annual Conference at Portland, Oregon

Sources: NC State University Libraries, ORCID
Added: September 27, 2020

2003 journal article

CPGEA: a grouping genetic algorithm for material cutting plan generation

Computers & Industrial Engineering, 44(4), 651–672.

By: C. Hung*, R. Sumichrast* & E. Brown*

author keywords: heuristic; genetic algorithm; cutting plan generation problem
TL;DR: CPGEA solutions are found to be consistently lower cost than the competing methods and the difference in solution quality is most pronounced for difficult problems requiring multiple identical plates in the optimal solution. (via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure (OpenAlex)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2003 journal article

Impact of the replacement heuristic in a grouping genetic algorithm

Computers & Operations Research, 30(11), 1575–1593.

By: E. Brown* & R. Sumichrast*

author keywords: grouping genetic algorithm; heuristic
TL;DR: Evidence is presented that the success of a GGA is heavily dependent on the replacement heuristic used as a part of the crossover operator, and that GGA performs up to 40% worse when problem-specific knowledge is not incorporated into the replace heuristic. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2002 conference paper

Replacement Heuristics for a Grouping Genetic Algorithm

Proceedings of the 2002 Southeast Decision Sciences Institute Annual Meeting. Presented at the 2002 Southeast Decision Sciences Institute Annual Meeting, Hilton Head, NC.

By: E. Brown & R. Sumichrast

Event: 2002 Southeast Decision Sciences Institute Annual Meeting at Hilton Head, NC

Sources: NC State University Libraries, ORCID
Added: September 27, 2020

2001 journal article

CF-GGA: A grouping genetic algorithm for the cell formation problem

International Journal of Production Research, 39(16), 3651–3669.

By: E. Brown* & R. Sumichrast

TL;DR: The GGA in this study, CF-GGA, a grouping genetic algorithm for the cell formation problem, performs very well when applied to a variety of problems from the literature and is able to match solutions with several highly complex algorithms and heuristics that were previously employed to solve these problems. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

2000 journal article

Shift Detection Properties of Moving Centerline Control Chart Schemes

Journal of Quality Technology, 32(1), 67–74.

By: C. Mastrangelo* & E. Brown*

TL;DR: The shift detection capability of the moving centerline exponentially weighted moving average (MCEWMA) chart is explored and enhancements for quicker detection of small process upsets are recommended. (via Semantic Scholar)
Sources: Crossref, NC State University Libraries
Added: January 27, 2020

Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.

Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.