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

Ehsan Ardjmand

Ehsan Ardjmand
Assistant Professor of Analytics & Information Systems
Copeland 530
ardjmand@ohio.edu
740.566.0122

Education

  • Ph.D., Industrial and Systems Engineering, Ohio University

Research Interests

  • Business analytics
  • Large-scale optimization
  • Operations research
  • Machine learning

Publications

  • Ghalehkhondabi, I., & Ardjmand, E. (2019). Sustainable E-waste supply chain management with price/sustainability-sensitive demand and government intervention. Journal of Material Cycles and Waste Management, 1-22.
  • Ardjmand, E., Stowe, D. L., & Stowe, J. D. (2019). Using Portfolio Theory to Design Better Exams. Available at SSRN 3434422.
  • Shakeri, H., Tavassoli, A., Ardjmand, E., & Poggi-Corradini, P. (2019). Designing Optimal Multiplex Networks for Certain Laplacian Spectral Properties. arXiv preprint arXiv:1903.01073.
  • Ghalehkhondabi, I., Ardjmand, E., Young II, W. A., Weckman, G. R. (2019). A Review of Demand Forecasting Models and Methodological Developments within Tourism and Passenger Transportation Industry. Journal of Tourism Future (in press).
  • Ardjmand, E., Bajgiran, O. S., & Youssef, E. (2019). Using list-based simulated annealing and genetic algorithm for order batching and picker routing in put wall based picking systems. Applied Soft Computing, 75, 106-119.
  • Ardjmand, E., Youssef, E., Weckman, G. R., Young II, W. A., Shakeri, H., Moyer, A. (2019). A Multi-Objective Model for Minimizing Makespan and Total Travel Time in Put Wall Based Picking Systems. International Journal of Logistics Systems and Management (in press).
  • Ardjmand, E., Shakeri, H., Singh, M., & Bajgiran, O. S. (2018). Minimizing order picking makespan with multiple pickers in a wave picking warehouse. International Journal of Production Economics, 206, 169-183.
  • Ardjmand, E., Bajgiran, O. S., Rahman, S., Weckman, G. R., & Young, W. A. (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, 115, 16-34.
  • Rahman, S., Ardjmand, E., Shore, J. B., (2017). Facebook Use in the Western Maryland Appalachian Region: Restaurant/Café Businesses, 4(2), 143.
  • Ghalehkhondabi, I., Ardjmand, E., Young, W. A., & Weckman, G. R. (2017). Water demand forecasting: review of soft computing methods. Environmental Monitoring and Assessment, 189(7), 313.
  • Jahedi, M., Ardjmand, E., & Knezevic, M. (2017). Microstructure metrics for quantitative assessment of particle size and dispersion: Application to metal-matrix composites. Powder Technology, 311, 226-238.
  • Ardjmand, E., Ghalehkhondabi, I., Weckman, G. R., & Young, W. A. (2016). Application of decision support systems in scheduling/planning of manufacturing/service systems: a critical review. International Journal of Management and Decision Making, 15(3-4), 248-276.
  • Ghalehkhondabi, I., Ardjmand, E., & Weckman, G. Integrated decision making model for pricing and locating the customer order decoupling point of a newsvendor supply chain. OPSEARCH, 1-23.
  • Ardjmand, E., Millie, D. F., Ghalehkhondabi, I., Young II, W. A., & Weckman, G. R. (2016). A State-Based Sensitivity Analysis for Distinguishing the Global Importance of Predictor Variables in Artificial Neural Networks. Advances in Artificial Neural Systems, 2016.
  • Ardjmand, E., Weckman, G. R., Schwerha, D., & Snow, A. P. (2016). Analyzing the Retirement Satisfaction Predictors among Men and Women Using a Multi-Layer Feed Forward Neural Network and Decision Trees. ALLDATA 2016, 111.
  • Ardjmand, E., Weckman, G. R., Young, W. A., Sanei Bajgiran, O., & Aminipour, B. (2016). A robust optimisation model for production planning and pricing under demand uncertainty. International Journal of Production Research, 54(13), 3885-3905.
  • Ghalehkhondabi, I., Ardjmand, E., Weckman, G. R., & Young, W. A. (2016). An overview of energy demand forecasting methods published in 2005–2015. Energy Systems, 1-37.
  • Weckman, G. R., Dravenstott, R. W., Young II, W. A., Ardjmand, E., Millie, D. F., & Snow, A. P. (2016). A Prescriptive Stock Market Investment Strategy for the Restaurant Industry using an Artificial Neural Network Methodology. International Journal of Business Analytics (IJBAN), 3(1), 1-21.
  • Ardjmand, E., Young, W., Weckman, G, Bajgiran, O., Aminipour, B., Park, N. (2015) Applying Genetic Algorithm to a New Bi-Objective Stochastic Model for Location and Routing of Hazardous Material, Expert Systems with Applications, Accepted with revisions.
  • Ardjmand, E., Weckman, G., Park, N., Taherkhani, P., & Singh, M. (2015). Applying genetic algorithm to a new location and routing model of hazardous materials. International Journal of Production Research, 53(3), 916-928.
  • Millie, D. F., Weckman, G. R., Fahnenstiel, G. L., Carrick, H. J., Ardjmand, E., Young, W. A., ... & Shuchman, R. A. (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, (ja) – Chosen as editor’s choice.
  • Ardjmand, E., Park, N., Weckman, G., & Amin-Naseri, M. R. (2014). The discrete Unconscious search and its application to uncapacitated facility location problem. Computers & Industrial Engineering, 73, 32-40.
  • Millie, D. F., Weckman, G. R., Young II, W. A., Ivey, J. E., Fries, D. P., Ardjmand, E., & Fahnenstiel, G. L. (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, 125, 57-67.

Presentations

  • Ye, L., Ardjmand, E. (2019) The Role of Gender Identity on Building Consumer Brand Relationship: SEM and fsQCA Findings. 2019 summer AMA conference.
  • Rahman, S., Ardjmand, E. (2019) Utilizing Business Analytics: To Boost Tourism. International Academy of Business Disciplines.
  • Singh, M., Ardjmand, E. (2019) Carton Set Optimization in E-commerce Warehouses. International Conference on Production Research.
  • Ardjmand, E., Shore, J., Rahman, S. (2018) Analyzing Perceptions and Attitudes of Tourists that Lead to Customer Satisfaction: An Approach to Expand Tourism. The International Academy of Business Discipline, 30th Annual Conference.
  • Ardjmand, E., Huh, D. W. (2017) Coordinated Warehouse Order Picking and Production Scheduling: A NSGA-II Approach. 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017).
  • Huh, D. W., Ardjmand, E. (2017) Overcoming use of Standard industry codes; Inter-industry Interactions and evolution of industries. Industry Studies Conference.
  • Rahman, S., Shore, J., Ardjmand, E. (2017). Small Businesses in Appalachia: Impact of Social Media on their operation and Opportunities. 29th IABD Annual Conference.
  • Ardjmand, E., Weckman, G. R., Schwerha, D., & Snow, A. P. (2016). Analyzing the Retirement Satisfaction Predictors among Men and Women Using a Multi-Layer Feed Forward Neural Network and Decision Trees. ALLDATA 2016, 111.
  • Millie, D. F., Weckman, G.R., Fahnenstiel, G. L., Carrick, H. J., Ardjmand, E., Young II, W. A., Shuchman, R. A., Sayers, M. J., Fries, D. P. (2014). Joint Aquatic Sciences Meeting 2014.
  • Millie, D. F., Weckman, G.R., Fahnenstiel, G. L., Young II, W. A., Ardjmand, E., Fahnenstiel, J. A., Shuchman, R. A., Sayers, M. J. (2014). 7th Symposium on Harmful Algae in the US.
  • Amin-naseri, M.R., Ardjmand, E. & Weckman, G.R. (2013). Training the Feedforward Neural Network Using Unconscious Search. In: Proceedings of International Joint Conference on Neural Networks (pp. 700-706). Dallas, Texas, USA: IEEE.
  • Ardjmand, E., Amin-Naseri, M.R. (2012). Unconscious Search - A New Structured Search Algorithm for Solving Continuous Engineering Optimization Problems Based on the Theory of Psychoanalysis, Advances in Swarm Intelligence. In: Y. Tan, Y. Shi & Z. Ji, (Vol. 7331, pp. 233-242): Springer Berlin / Heidelberg.

Biography

Dr. Ehsan Ardjmand is an Assistant Professor of Analytics and Information Systems at Ohio University. His teaching and research interests include predictive and prescriptive modeling in business, large-scale optimization, machine learning, and operations research. Dr. Ardjmand has more than eight years of experience in manufacturing and service industries in various operations management and data analytics related positions. He has led several research projects related to business intelligence, large-scale optimization, and data science and their applications in manufacturing, supply chain, and social media, to name a few.