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College of Business
Copeland Hall
1 Ohio University
Athens OH 45701-2979

William Young

Young, William
O'Bleness Professor of Analytics & Information Systems
Muck 344
youngw1@ohio.edu
740.593.2041

Education

  • Ph.D., Mechanical and Systems Engineering, Ohio University, 2010
  • M.S., Electrical Engineering, Ohio University, 2005
  • B.S., Electrical Engineering, Ohio University, 2002

Research Interests

  • Operation Management
  • Operations Research
  • Predictive Analytics
  • Prescriptive Analytics

Publications

  • Tavasoli, A., Fazli, M. Ardjmand, E., Young, W., Shakeri, H. (2023) Competitive Pricing Under Local Network Effects, European Journal of Operational Research (EJOR), 311, Iss. 2, pp. 545-566, ISSN 0377-2217, DOI https://doi.org/10.1016/j.ejor.2023.04.039., CoB List: Top Quality
  • McCarthy, M., Young, W., Metcalf, A., & Rahmani, H., (2023) Predicting Student Success in an online Master of Business Administration Program, International Journal of Society Systems Science (IJSSS), 14, No. 3, pp. 201-221
  • Ardjmand, E., Young, W. & Rahman, Shakil, (2021) Order Cartonization and Fulfillment Center Assignment in the Retail Industry, Journal of International Business Disciplines, Vol. 16, Iss. 2, pp. 89-126
  • Fallahtafti, A., Ardjmand, E., Young, W. & Weckman G. (2021) A Multi-Objective Two-Echelon Location-Routing Problem for Cash Logistics: A Metaheuristic Approach, Applied Soft Computing (ASC), Vol. 111, Iss. 107685, ISSN: 1568-4946, DOI: https://doi.org/10.1016/j.asoc.2021.107685 CoB List: Top Quality
  • Ardjmand, E., Singh, M., Shakeri, H., Tavasoli, A., Young, W. (2021) Mitigating the Risk of Infection Spread in Manual Order Picking Operations: A Multi-Objective Approach, Applied Soft Computing (ASC), Vol. 100, Iss. 106953, ISSN 1568-4946, DOI: https://doi.org/10.1016/j.asoc.2020.106953, CoB List: Top Quality
  • Ardjmand, E., Shakeri, H., Tavasoli, A., & Young, W., (2021) Incentive Rate Determination in Viral Marketing, European Journal of Operational Research (EJOR), Vol. 289, Iss. 3, pp. 1169-1187, ISSN, 0377-2217, DOI: https://doi.org/10.1016/j.ejor.2020.07.046, CoB List: Top Quality
  • Ardjmand, E., Young, W., & Almasarwah, N. (2021) Detecting Community Structures within Complex Networks Using a Discrete Unconscious Search Algorithm, International Journal of Operations Research and Information Systems (IJORIS), 12, Iss. 2, Article 2, pp. 15-32, DOI: https://doi.org/10.1111/coin.12273
  • Gabler, C., Goodnite, A., Pueschel, A., & Young, W. (2020) Location, Location, Location? The Impact of Site Selection on Global Learning in Short-Term Study Abroad, Journal of Scholastic Inquiry: Business (JSIB), 1, Iss. 11, pp. 107-122, DOI: N/A
  • Ardjmand, E., Ghalehkhondabi, I., Young, W., Sadeghi, A., Weckman, G. & Shakeri, H., (2020) A Hybrid Artificial Neural Network, Genetic Algorithm and Column Generation Heuristic for Minimizing Makespan in Manual Order Picking Operations, Expert Systems with Applications (ESWA), Vol. 159, Iss. 113566, ISSN 0957-4174, DOI: https://doi.org/10.1016/j.eswa.2020.113566, 2020 IS 8.67, CoB List: Top Quality
  • Young, W. & Matta, V. (2020) How a College Resolved the Problem of Multi-Criteria Team Formation, International Journal of Society Systems Science (IJSSS), IJSSS-263147, 12, Iss. 4, pp. 329-351, DOI: https://doi.org/10.1504/IJSSS.2020.112406
  • Ardjmand, E., Young, W., Ghalehkhondabi, I, & Weckman, G., (2020), A Scheduling and Rescheduling Decision Support System for Apparel Manufacturing, International Journal of Operations Research and Information Systems (IJORIS): Special Issue on Industrial Innovation Systems and Applications, 12 Iss. 4, pp. 1-19, DOI: 10.4018/IJORIS.20211001.oa4
  • Young, W. & Weckman, G. (2020) A Team-Compatibility Decision Support System for the National Football League, International Journal of Computer Science in Sport (IJCSS), 19, Iss. 1, pp. 60-101, DOI: 10.2478/ijcss-2020-0005
  • Younes Sinaki, R. Sadeghi, A., Lynch, D., Young, W. & Weckman G. (2020) Financial Asset Management using Artificial Neural Networks, International Journal of Operations Research and Information Systems (IJORIS), 11, Iss. 3, pp., 66-88, DOI: 10.4018/IJORIS.2020070104
  • Murtaza, N., Dag, A., Young, W., & Dursun, D. (2020) Determining Optimal Skillsets for Managers Based on Local and Global Job Markets: A Text Analytics Approach, Decision Sciences Journal of Innovative Education (DSJIE), 18, Iss. 3, pp. 374-408, DOI: https://doi.org/10.1111/dsji.12212, 2020 IS 1.30, 2021 IS 1.74
  • Ardjmand, E., Youssef, E., Weckman, G., Young, W. Shakeri, H., & Moyer, A. (2020) A Multi-Objective Model for Minimizing Makespan and Total Travel Time in Put Wall Based Picking Systems, International Journal of Logistics Systems and Management (IJLSM), 36, Iss. 1, pp. 138-176, DOI: https://doi.org/10.1504/IJLSM.2020.107230, 
  • Sadeghi, A., Younes Sinaki, R., Young, W., & Weckman, G., (2020) An Intelligent Model to Predict Energy Performances of Residential Buildings Based on Deep Neural Networks, Energies: Special Issue: Optimal Design and Operation of Sustainable Energy Systems, 13, Iss. 3, pp. 571-594, DOI: https://doi.org/10.3390/en13030571,
  • Ghalehkhondabi, I., Ardjmand, E., Young, W. & Weckman, G. (2019) A Review of Demand Forecasting Models and Methodological Developments within Tourism and Passenger Transportation Industry, Journal of Tourism Futures (JTF), Vol. 5, Iss. 1, pp. 75-93 DOI: 10.1108/JTF-10-2018-0061
  • Bihl, T. & Young, W. (2018) Special Issue: Operationally Relevant Methods for Big Data Problems, Journal of Algorithms & Computational Technology (ACT), Vol. 12, Iss. 4, pp. 291-292, DOI: https://doi.org/10.1177/1748301818806988
  • Ardjmand, E., Bajgiran, O. S., Rahman, S., Weckman, G. & Young, W. (2018) A Multi-Objective Model for Order Cartonization and Fulfillment Center Assignment in the E-tail/Retail Industry, Transportation Research Part E: Logistics and Transportation Review (TRLTR), Vol. 115, pp. 16–34 DOI: https://doi.org/10.1016/j.tre.2018.04.005, CoB List: Top Quality 
  • Kayaalp, N., Weckman, G., Young, W., Millie, D., & Celikbilek, C., (2017) Extracting Customer Opinions Associated with a Feature by Using a Sentence Segmentation Approach, International Journal of Business Information Systems (IJBIS), Vol. 26, No. 2, pp. 236-260 DOI: https://doi.org/10.1504/IJBIS.2017.086335
  • Ghalehkhondabi, I., Ardjmand, E., Weckman, G. & Young, W. (2017) An Overview of Energy Demand Forecasting Methods Published in 2005-2015, Energy Systems (ES), Vol. 8, Iss. 2, pp. 411-447, DOI: https://doi.org/10.1007/s12667-016-0203-y
  • Ghalehkhondabi, I., Weckman, G. & Young, W. (2017) Water Demand Forecasting: Review of Soft Computing Methods, Environmental Monitoring, and Assessment (EMA), Vol. 189, No. 313, pp. 3-15, DOI: https://doi.org/10.1007/s10661-017-6030-3
  • Ardjmand, E., Ghalehkhondabi, I., Weckman, G. & Young, W. (2016) Application of Decision Support Systems in Scheduling and Planning of Manufacturing and Service Systems: A Critical Review, International Journal of Management and Decision Making (IJMDM), Vol. 15, Iss. 3-4, pp. 248–276, DOI: 10.1504/IJMDM.2016.080703
  • Ardjmand, E., Ghalehkhondabi, I, Millie, D., Young, W., & Weckman, G. (2016) A State-Based Sensitivity Analysis for Distinguishing the Global Importance of Predictor Variables in Artificial Neural Networks, Advances in Artificial Neural Systems (AANS), Vol. 2016, ID. 2303181, pp. 1-11, http://dx.doi.org/10.1155/2016/230318
  • Ardjmand, E., Weckman, G., Young, W., Bajgiran, O., & Aminipour, A. (2016) A Robust Optimization Model for Production Planning and Pricing under Demand Uncertainty, International Journal of Production Research (IJPR), Vol. 54, Iss. 13, pp. 3885-3905 DOI http://dx.doi.org/10.1080/00207543.2016.1161251, CoB List: Top Quality
  • Ardjmand, E., Young, W., Weckman, G, Bajgiran, O., Aminipour, B., Park, N. (2016) Applying Genetic Algorithm to a New Bi-Objective Stochastic Model for Transportation, Location, and Allocation of Hazardous Materials, Expert Systems with Applications (ESWA), Vol. 51, Iss. C, pp. 49-58 DOI: https://doi.org/10.1016/j.eswa.2015.12.036, CoB List: Top Quality
  • Bihl, T., Young, W., Weckman, G. (2016) Defining, Understanding, and Addressing Big Data, International Journal of Business Analytics (IJBAN), 3, Iss. 2, pp. 1-32, DOI: 10.4018/IJBAN.2016040101
  • Weckman, G, Dravenstott, R., Young, W., Ardjmand, E., Millie, D., & Snow, A. (2016) A Prescriptive Stock Market Investment Strategy for the Restaurant Industry using an Artificial Neural Network Methodology, International Journal of Business Analytics (IJBAN), 3, Iss. 1, pp. 1-21, DOI: 10.4018/IJBAN.2016010101
  • Celikbilek, C., Bajgiran, O., Ardjmand, E., Weckman, G. & Young, W. (2015) A New Capacitated Multiple Allocation p-hub Median Model considering Multiple Stochastic Parameters, International Journal of Data Analysis and Information Systems (IJDAIS), Vol. 7, No. 2, pp. 75-84, DOI: https://doi.org/10.1007/s40092-017-0195-9
  • Moyer, A., Young, W., Weckman G., Martin, C., & Cutright, K., (2015) Rubrics on the Fly: Improving Efficiency and Consistency with a Rapid Grading and Feedback System, Journal of Teaching and Learning with Technology (JoTLT), 4, No. 2, pp. 6-29, DOI: 10.14434/jotlt.v4n2.1347
  • Young, W., Nykl, S., Weckman, G. & Chelberg, D. (2014) Using Voronoi Diagrams to Improve Classification Performances when Modeling Imbalanced Datasets, Neural Computing and Applications (NCA), Vol. 26, Iss. 5, pp. 1041-1054 , DOI: https://dl.acm.org/doi/abs/10.1007/s00521-014-1780-0, CoB List: High Quality
  • Young, W., Hicks, B., Villa-Lobos, D. & Franklin, T. (2014) Using Student Feedback and Professor-Developed Multimedia to Improve Instructor Presence and Student Learning, Journal of Teaching and Learning with Technology (JoTLT), Vol. 3, No. 2, pp. 12 – 30, DOI: 10.14434/jotlt.v3n2.12990
  • Millie, D., Weckman, G., Fahnenstiel, G., Carrick, H., Ardjmand, E., Young, W., Sayers, M., & Shuchman, R. (2014) Using Artificial Intelligence for CyanoHAB Niche Modeling: Discovery and Visualization of Microcystis-Environmental Associations within Western Lake Erie, Canadian Journal of Fisheries and Aquatic Sciences (CJFAS), 71, Iss. 11, pp. 1642-1654, DOI: https://doi.org/10.1139/cjfas-2013-0654
  • Young, W., Kinn, A., & Weckman G. (2014) The Implications of the NFL Scouting Combine, International Journal of Sports Science and Engineering (IJSSE), 8, Iss. 2, pp. 1-13
  • Anderson, J., Young, W., & Franklin, T. (2014) Brief Reflections on Flipping the College Classroom, Journal of the World Universities Forum (JWUF), 6, Iss. 3, pp. 21-29
  • Young, W., & Weckman G. (2014) The Pythagorean Winning Percentage Formula Derived for the National Football League, International Journal of Sports Science and Engineering (IJSSE), 8., Iss. 1, pp. 1-9
  • Millie, D., Weckman, G., Young, W., Ivey, J., Fries, D., Ardjmand, E., & Fahnenstiel, G. (2013) Coastal ‘Big Data’ and nature-inspired computation: prediction potentials, uncertainties, and knowledge derivation of neural networks for an algal metric, Estuarine, Coastal and Shelf Science (ECS), Vol. 125, pp. 57-67, DOI: 10.1016/j.ecss.2013.04.001
  • Young, W., Young, R., & Weckman, G., (2013) Improving an Internal Combustion Engine's Fuel Map through an Artificial Neural Network, International Journal of Decision Sciences (IJDS), 4, No. 2, pp. 85-103
  • Rinder, M. Weckman, G., Schwerha, D., Snow, A., Dreher, P., Park, N., Paschold, H., & Young, W. (2012) Healthcare Scheduling by Data Mining, Literature Review, and Future Directions, Journal of Healthcare Engineering (JHE), 3, No. 3. pp. 477-502, DOI: https://doi.org/10.1260/2040-2295.3.3.477
  • Millie, D., Weckman, Young, W., Ivey, J., Carrick, H., & Fahnenstiel, G. (2012) Modeling Microalga Abundance with Artificial Neural Networks: Demonstration of a Heuristic, ‘Grey-Box’ Technique to Deconvolve and Quantify Environmental Influences, Environmental Modelling & Software (EMS), Vol. 37, pp. 27-39, DOI: 10.1016/j.envsoft.2012.04.009
  • Young, W., Weckman, G., Hari, V., Whiting, H. & Snow A. (2012) Using Artificial Neural Networks to enhance CART, Neural Computing & Applications (NCA), Vol. 21, Num. 7, pp. 1477-1489, DOI: https://link.springer.com/article/10.1007/s00521-012-0887-4, CoB List: High Quality
  • Weckman, G., Bondal, A., Rinder, M. & Young, W. (2012) Applying a Hybrid Artificial Immune Systems to the Job Shop Scheduling Problem, Journal of Neural Computing and Applications (NCA), Vol. 21, No. 7, pp. 1465-1475, DOI 10.1007/s00521-012-0852-2, CoB List: High Quality
  • Young, W., Franklin, T., Cooper, T., Carroll, S. & Liu, C. (2011) Game-based Learning Aids in Second Life, Journal of Interactive Learning Research (JILR), 23., No. 1, pp. 55-78
  • Young, W., Weckman, G., Rangwala, M., Whiting, H., Paschold, H., Snow, A., Mourning, C. (2011) An Investigation of TREPAN utilizing a Continuous Oracle Model, International Journal of Data Analysis Techniques and Strategies (IJDATS), 3, No. 4, pp. 325-352, DOI: https://doi.org/10.1504/IJDATS.2011.042953
  • Young, W., Millie, D. Weckman, G., Anderson, J., Klarer, D. & Fahnenstiel, G. (2011) Modeling Net Ecosystem Metabolism with an Artificial Neural Network and Bayesian Belief Network, Environmental Modelling & Software (EMS), 26., pp. 1199-1210, DOI: https://doi.org/10.1016/j.envsoft.2011.04.004
  • Holland, W., Young, W., & Weckman, G. (2011) Facility RFID Localization System based on Artificial Neural Networks, International Journal of Industrial Engineering - Theory, Applications, and Practice (IJIETAP), Vol. 18., Iss. 1, pp. 16-24
  • Young, W., Weckman, G. & Holland, W. (2011) A Survey of the Methodologies for the Treatment of Missing Values within Datasets: Limitations and Benefits, Theoretical Issues in Ergonomics Science (TIES), Vol. 12, No. 1, pp. 15-43, DOI: https://doi.org/10.1080/14639220903470205
  • Weckman, G., Young, W., Hernández, S., Rangwala, M., & Ghai, V. (2010) Extracting Knowledge from Carbon Dioxide Corrosion Inhibition with Artificial Neural Networks, International Journal of Industrial Engineering - Theory, Applications, and Practice (IJIETAP), Vol. 17, Iss. 1, pp. 69-79
  • Weckman G., Paschold, H., Dowler, J., Whiting, H., & Young, W. (2010) Using Neural Networks with Limited Data to Estimate Manufacturing Cost, Journal of Industrial and Systems Engineering (JISE). Vol. 3, No. 4, pp. 257-274, DOI: 20.1001.1.17358272.2010.3.4.3.3,
  • Masel, D., Young, W. & Judd R. (2010) A Rule-Based Approach to Predict Forging Volume for Cost Estimation during Product Design, International Journal of Advanced Manufacturing Technology (IJAMT), Vol. 46, No 1-4, pp. 31-41, DOI 10.1007/s00170-009-2108-6
  • Weckman, G., Millie, D., Ganduri, C., Rangwala, M., Young, W., Rinder, M. & Fahnenstiel, G. (2009) Knowledge Extraction from the Black Box in Ecological Monitoring, Journal of Industrial and Systems Engineering (JISE), Vol. 3, No. 1, pp. 38-55
  • Young, W. & Weckman G. (2009) Using a Heuristic Approach to Derive a Grey-Box Model through an Artificial Neural Network Knowledge Extraction Technique, Neural Computing & Applications (NCA), Vol. 19, Iss. 3, pp. 353-366, DOI https://link.springer.com/article/10.1007/s00521-009-0270-2, CoB List: High Quality
  • Young, W., Kaya, S. & Weckman, G. (2009) Learning Before Erring: The Influence of Dielectric Materials to Pursue Moore’s Law, International Journal of Industrial Engineering - Theory, Applications, and Practice (IJIETAP), Vol. 16, Iss. 2, pp. 91-98
  • Young, W., Holland, W. & Weckman, G. (2008) Determining Hall of Fame Status for Major League Baseball through an Artificial Neural Network, Journal of Quantitative Analysis in Sports (JQAS), Vol. 4, Iss. 4, Article 4. pp. 1-44, DOI: https://doi.org/10.2202/1559-0410.1131
  • Young, W. & Weckman G. (2008) Evaluating the Effects of Aging for Professional Football Players in Combine Events using Performance-Aging Curves, International Journal of Sports Science and Engineering (S-SCI), Vol. 2, No. 3, pp. 131-143, ISSN 1750-9823
  • Young, W., Masel, D. & Judd, R. (2008) A Matrix-Based Methodology for Determining a Part Family's Learning Rate, Computers & Industrial Engineering (CIE), Vol. 54, No. 3, pp. 390-400, ISSN: 0360-8352, DOI: https://www.sciencedirect.com/science/article/abs/pii/S036083520700191X, CoB List: High Quality
  • Young, W., Weckman, G., Thompson, J. & Brown, M. (2008) Artificial Neural Networks for Knowledge Extraction of Concrete Shear Strength Prediction, International Journal of Industrial Engineering - Theory, Applications, and Practice (IJIETAP), Vol. 15, Iss. 1, pp. 26-35

Presentations & Awards

  • Faculty Excellence Award for Teaching and Learning, CoB, Ohio University 2023
  • Research Recognition, College of Business, Ohio University 2021
  • Teaching Recognition, College of Business, Ohio University 2021
  • University Professor Award, Ohio University 2020
  • College of Business Research Award, College of Business, Ohio University 2018
  • Graduate Teaching Award, College of Business, Ohio University 2017
  • College of Business Research Award, College of Business, Ohio University 2017
  • Senior Class Faculty Recognition Award, College of Business, Ohio University 2016
  • Cincinnati-Dayton Outstanding Young OR/MS Award, INFORMS 2015
  • Outstanding Doctoral Student Leader Award, Ohio University 2010

Bio

Dr. William A. Young II is an enthusiastic educator, an active researcher, and a team-oriented collaborator in service. At Ohio University’s College of Business, Young is a Charles G. O’Bleness Full Professor of Business Analytics in the Department of Analytics and Information Systems. As an Associate Professor, Young received Ohio University’s University Professor Award in 2020. Young earned his doctorate in Mechanical and Systems Engineering from Ohio University’s Russ College of Engineering and Technology in 2010. He also received bachelor’s and master’s degrees in electrical engineering at Ohio University in 2002 and 2005, respectively.

He has collaborated with multidisciplinary teams of faculty, students, and professionals on projects and programs that have been funded by General Electric Aviation, the National Science Foundation, Sogeti, Capgemini, and Ohio’s Department of Labor. Young's primary research and teaching interests relate to business analytics and operations management. In terms of his research, Young has various peer-reviewed articles related to operation management, healthcare services, and environmental systems, as well as specific interests in quantitative sports analysis, and educational technologies and techniques for innovative curriculum development and teaching instruction. Young has published his articles in journals such as Expert Systems with Applications, Applied Soft Computing, International Journal of Production Research, European Journal of Operational Research, Transportation Research Part E: Logistics and Transportation Review, Neural Computing & Applications, and Computers and Industrial Engineering. Young has co-authored a college course textbook titled ‘Excel’ in Business Analytics.