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

Ehsan Ardjmand

Ehsan Ardjmand
Associate Professor of Analytics & Information Systems; Director, Online Master of Business Analytics (MBAn) Program
Copeland 530
ardjmand@俄亥俄州.edu
740.566.0122
OpenScholar

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). 价格/可持续性敏感需求和政府干预的可持续电子废物供应链管理. 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). 具有一定拉普拉斯谱性质的最优复用网络设计. arXiv preprint arXiv:1903.01073.
  • Ghalehkhondabi, I., Ardjmand, E., Young II, W. A., Weckman, G. R. (2019). 旅游和客运行业需求预测模型和方法发展综述. Journal of Tourism Future (in press).
  • Ardjmand, E., Bajgiran, O. S., & Youssef, E. (2019). 利用基于列表的模拟退火和遗传算法求解基于放墙式拣选系统中的订单批处理和拣选机路径. Applied Soft Computing, 75, 106-119.
  • Ardjmand, E., Youssef, E., Weckman, G. R., Young II, W. A., Shakeri, H., Moyer, A. (2019). 基于放墙的拣货系统最大完工时间和总行程时间最小的多目标模型. 国际物流系统与管理杂志(出版中).
  • Ardjmand, E., Shakeri, H., Singh, M., & Bajgiran, O. S. (2018). 在波浪拣货仓库中使用多台拣货机最大限度地减少拣货时间. International Journal of Production Economics, 206, 169-183.
  • Ardjmand, E., Bajgiran, O. S., Rahman, S., Weckman, G. R., & Young, W. A. (2018). 电子零售/零售行业订单卡通化和履行中心分配的多目标模型. 交通运输研究与发展，2001,11 (2):1 - 4.
  • Rahman, S., Ardjmand, E., Shore, J. B., (2017). Facebook在马里兰西部阿巴拉契亚地区的使用:餐馆/咖啡馆商业，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). 粒度和分散定量评估的微观结构度量:在金属基复合材料中的newbb电子. Powder Technology, 311, 226-238.
  • Ardjmand, E., Ghalehkhondabi, I., Weckman, G. R., & Young, W. A. (2016). 决策支持系统在制造/服务系统调度/计划中的newbb电子:综述. 管理与决策，15(3)，248-276.
  • Ghalehkhondabi, I., Ardjmand, E., & Weckman, G. 报贩供应链客户订单解耦点定价与定位的集成决策模型. OPSEARCH, 1-23.
  • Ardjmand, E., Millie, D. F., Ghalehkhondabi, I., Young II, W. A., & Weckman, G. R. (2016). 人工神经网络中预测变量全局重要性的状态敏感性分析. Advances in Artificial Neural Systems, 2016.
  • Ardjmand, E., Weckman, G. R., Schwerha, D., & 雪,. P. (2016). 基于多层前馈神经网络与决策树的男女退休满意度预测因子分析. ALLDATA 2016, 111.
  • Ardjmand, E., Weckman, G. R., Young, W. A., Sanei Bajgiran, O., & Aminipour, B. (2016). 需求不确定性下生产计划和定价的鲁棒优化模型. 农业工程学报，26 (3)，391 - 391.
  • Ghalehkhondabi, I., Ardjmand, E., Weckman, G. R., & Young, W. A. (2016). 2005-2015年能源需求预测方法综述. Energy Systems, 1-37.
  • Weckman, G. R., Dravenstott, R. W., Young II, W. A., Ardjmand, E., Millie, D. F., & 雪,. P. (2016). 基于人工神经网络的餐饮业规定性股票市场投资策略. International Journal of Business Analytics (IJBAN), 3(1), 1-21.
  • Ardjmand, E., Young, W., Weckman, G, Bajgiran, O., Aminipour, B., Park, N. (2015)基于遗传算法的危险物品定位路径新双目标随机模型, Expert Systems with Applications, Accepted with revisions.
  • Ardjmand, E., Weckman, G., Park, N., Taherkhani, P., & Singh, M. (2015). 将遗传算法newbb电子于一种新的危险物品定位路径模型. 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). 基于人工智能的蓝藻藻生态位建模:伊利湖西部微囊藻与环境关联的发现与可视化. 加拿大渔业与水产科学杂志，(ja) -被选为编辑之选.
  • Ardjmand, E., Park, N., Weckman, G., & Amin-Naseri, M. R. (2014). 离散无意识搜索及其在无能力设施选址问题中的newbb电子. 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). 沿海“大数据”和受自然启发的计算:预测潜力, uncertainties, 并对一种藻类度量的神经网络进行了知识推导. Estuarine, Coastal and Shelf Science, 125, 57-67.

Presentations

  • 你们,我., Ardjmand, E. (2019)性别认同对建立消费者品牌关系的作用:SEM和fsQCA研究结果. 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)分析游客的感知和态度导致顾客满意:一种拓展旅游业的方法. 国际商业学科学会第30届年会.
  • Ardjmand, E., 嗯,维. W. (2017)仓库订单拣选与生产调度:一种NSGA-II方法. 2017 IEEE计算智能系列研讨会(IEEE SSCI 2017).
  • 嗯,维. 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). 阿巴拉契亚地区的小企业:社交媒体对其运营和机遇的影响. 29th IABD Annual Conference.
  • Ardjmand, E., Weckman, G. R., Schwerha, D., & 雪,. P. (2016). 基于多层前馈神经网络与决策树的男女退休满意度预测因子分析. 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). 利用无意识搜索训练前馈神经网络. 见:国际神经网络联合会议论文集(pp. 700-706). Dallas, Texas, USA: IEEE.
  • Ardjmand, E., Amin-Naseri, M.R. (2012). 无意识搜索——一种基于精神分析理论的解决连续工程优化问题的结构化搜索算法, Advances in Swarm Intelligence. Y:. 棕褐色,Y. 史 & Z. 霁(卷. 7331, pp. 233-242): Springer Berlin / Heidelberg.

Biography

Ehsan Ardjmand，newbb电子平台分析与信息系统副教授，商业分析硕士项目主任. He received his Ph.D. 拥有超过15年的newbb电子先进机器学习和优化技术来改善业务运营和决策的经验.

Dr. Ardjmand的研究兴趣在于当代预测和规范的商业分析问题，其中融合了人工智能领域, networks, information systems, and operations management intersect. 他与行业合作伙伴广泛合作，实施数据驱动的解决方案.

Dr. Ardjmand还担任observvea Inc .的顾问委员会成员.，为实施因果机器学习和人工智能方法提供指导.