CONTACT
+66-2-986-9009 ext 1105
Phone Extension: 1102
EDUCATION
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B.S. in Computer Science, University of Maryland, USA
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B.S. in Mathematics, University of Maryland, USA
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M.S. in Management Science, University of Maryland, USA
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Ph.D. in Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, USA
WORK EXPERIENCES
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2004-Present: SIIT
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2005-2006: Consultant, Thailand Airport Ground Services, Thailand
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2003-2004: Teaching Assistant for higher education program, Virginia Polytechnic Institute and State University, VA
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2001-2004: Research Assistant, Virginia Polytechnic Institute and State University, VA
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1999-2000: Consultant, Lampshade Company, NJ
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1998-1999: Consultant, Otis Elevator, NY.
ACADEMIC AWARDS
Development and Promotion of Science and Technology Talents Project (DPST) Scholarship, 1990-2004.
RESEARCH AREAS
Linear programming, Integer programming, Network optimization, Simulation, Supply chain management.
RESEARCH INTERESTS
Large-Scale Simulation and Optimization
Many problems in the real world are large and complex. Researchers in this field are trying to improve the algorithm and utilize available computational technology such as parallelism or grid computing to solve such problems where their resulting models are also very large. This technology also enables researchers to have a detail model which is close to the real world problem. Some examples of these problems are transportation problem in the urban area (where there consists of millions of people driving on thousands of streets), financial simulation, bioinformatics, and large-scale planning.
Supply Chain Management (SCM)
The researches in SCM involve the study of the process of planning, implementing, and controlling the operations of the supply chain with the purpose of reducing cost and increasing efficiency. SCM includes all movement and storage of raw materials, work-in-process inventory, and finished goods from origin to consumption. There are many problems that can be modeled by simulation and optimization models.
LIST OF PUBLICATIONS
Jeenanunta, C. (2023). Pandemic Effect on the Industry 4.0 Readiness: A Case Study in Vietnamese Industry. Journal of Engineering, Project & Production Management, 13(3).
Truong, H. Q., & Jeenanunta, C. (2022). Fuzzy mixed integer linear programming model for national level monthly unit commitment under price-based uncertainty: A case study in Thailand. Electric Power Systems Research, 209, 107963.
Worawattawechai, T., Intiyot, B., Jeenanunta, C., & Ferrell Jr, W. G. (2022). A learning enhanced golden ball algorithm for the vehicle routing problem with backhauls and time windows. Computers & Industrial Engineering, 168, 108044.
Phyo, P. P., & Jeenanunta, C. (2022). Advanced ml-based ensemble and deep learning models for short-term load forecasting: Comparative analysis using feature engineering. Applied Sciences, 12(10), 4882.
Chumnumporn, K., Jeenanunta, C., Simpan, S., Srivat, K., & Sanprasert, V. (2022). The role of a leader and the effect of a customer's smart factory investment on a firm's industry 4.0 technology adoption in Thailand. International Journal of Technology, 13(1).
Tieng, K., Jeenanunta, C., Chea, P., & Rittippant, N. (2022). Roles of customers in upgrading manufacturing firm technological capabilities toward industry 4.0. Engineering Management Journal, 34(2), 329-340.
Intalar, N., Chumnumporn, K., Jeenanunta, C., & Tunpan, A. (2021). Towards Industry 4.0: digital transformation of traditional safety shoes manufacturer in Thailand with a development of production tracking system. Engineering Management in Production and Services, 13(4), 79-94.
Laisupannawong, T., Intiyot, B., & Jeenanunta, C. (2021). Improved Mixed-Integer Linear Programming Model for Short-Term Scheduling of the Pressing Process in Multi-Layer Printed Circuit Board Manufacturing. Mathematics, 9(21), 2653.
Ketudat, S., & Jeenanunta, C. (2021). Impact of the COVID-19 pandemic on logistics firms and their resilience: case studies in Thailand. Engineering Management in Production and Services, 13(3), 86-98.
Kaeo-Tad, N., Jeenanunta, C., Chumnumporn, K., Nitisahakul, T., & Sanprasert, V. (2021). Resilient manufacturing: Case studies in Thai automotive industries during the COVID-19 pandemic. Engineering Management in Production and Services, 13(3), 99-113.
Laisupannawong, T., Intiyot, B., & Jeenanunta, C. (2021). Mixed-integer linear programming model and heuristic for short-term scheduling of pressing process in multi-layer printed circuit board manufacturing. Mathematics, 9(6), 653.
Phyo, P. P., & Jeenanunta, C. (2021). Daily load forecasting based on a combination of classification and regression tree and deep belief network. IEEE Access, 9, 152226-152242.
Tieng, K., Javed, A., Jeenanunta, C., & Kohda, Y. (2021). Mechanisms for engineers to promote product and process innovation: Thai manufacturing context. International Journal of Management Practice, 14(2), 146-173.
Jeenanunta, C., Kongtarat, V., & Buddhakulsomsiri, J. (2021). A simulation-optimisation approach to determine optimal order-up-to level for inventory system with long lead time. International Journal of Logistics Systems and Management, 38(2), 253-276.
Kimseng, T., Javed, A., Jeenanunta, C., & Kohda, Y. (2020). Sustaining innovation through joining global supply chain networks: The case of manufacturing firms in Thailand. Sustainability, 12(13), 5259.
Kimseng, T., Javed, A., Jeenanunta, C., & Kohda, Y. (2020). Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms. Journal of Open Innovation: Technology, Market, and Complexity, 6(2), 38.
Hnin, S. W., & Jeenanunta, C. (2020). A particle swarm optimised support vector regression for short-term load forecasting. International Journal of Energy Technology and Policy, 16(4), 399-412.
Sumetthapiwat, S., Intiyot, B., & Jeenanunta, C. (2020). A column generation on two-dimensional cutting stock problem with fixed-size usable leftover and multiple stock sizes. International Journal of Logistics Systems and Management, 35(2), 273-288.
Hnin, S. W., & Jeenanunta, C. (2019). Bayesian optimization in a support vector regression model for short-term electricity load forecasting. Engineering and Applied Science Research, 46(3), 267-275.
Phyo, P. P., Jeenanunta, C., & Hashimoto, K. (2019). Electricity load forecasting in Thailand using deep learning models. International Journal of Electrical and Electronic Engineering & Telecommunications, 8(4), 221-225.
Pongsathornwiwat, A., Jeenanunta, C., Huynh, V. N., & Udomvitid, K. (2019). How collaborative routines improve dynamic innovation capability and performance in tourism industry? A path-dependent learning model. Asia Pacific Journal of Tourism Research, 24(4), 281-295.
Le, C. T. D., Buddhakulsomsiri, J., Jeenanunta, C., & Dumrongsiri, A. (2019). Determining an optimal warehouse location, capacity, and product allocation in a multi-product, multi-period distribution network: a case study. International Journal of Logistics Systems and Management, 34(4), 510-532.
Pongsathornwiwat, A., Jeenanunta, C., Huynh, V. N., & Udomvitid, K. (2019). Can collaborative relationship stimulate innovation capability and improve performance in the hospitality industry?. International Journal of Innovation and Learning, 26(3), 321-342.
Intalar, N., & Jeenanunta, C. (2019). Effects of customer’s investment in ICT on partners’ decisions through the supply chain: an empirical study of the manufacturing industry in Thailand. Asian Journal of Technology Innovation, 27(2), 239-256.
Phyo, P. P., & Jeenanunta, C. (2019). Electricity load forecasting using a deep neural network. Engineering and Applied Science Research, 46(1), 10-17.
Tieng, K., Jeenanunta, C., & Hsieh, W. L. (2019). The role of knowledge sharing approaches to help internal knowledge sources to create firm innovation. International Journal of Knowledge Management Studies, 10(2), 157-174.
Worawattawechai, T., Intiyot, B., & Jeenanunta, C. (2019). An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows. Songklanakarin Journal of Science and Technology, 41(1), 151-158.
Jeenanunta, C., & Abeyrathna, K. D. (2019). Neural network with genetic algorithm for forecasting short-term electricity load demand. International Journal of Energy Technology and Policy, 15(2-3), 337-350.
Abeyrathna, K. D., & Jeenanunta, C. (2019). Hybrid particle swarm optimization with genetic algorithm to train artificial neural networks for short-term load forecasting. International Journal of Swarm Intelligence Research (IJSIR), 10(1), 1-14.
Jeenanunta, C., Rittippant, N., Chongphaisal, P., Machikita, T., Ueki, Y., & Tsuji, M. (2018). Examining the role of top management leadership style on transportation efficiency and profitability of logistics firms. Songklanakarin Journal of Science & Technology, 40(6).
Phusittrakool, A., Jeenanunta, C., & Prathombutr, P. (2018). Effects of predictive horizon on network performance under short‐term predictive information. IET Intelligent Transport Systems, 12(2), 113-119.
Intalar, N., Jeenanunta, C., Rittippant, N., Chongphaisal, P., & Komolavanij, S. (2018). The role of quality control circles on new product development: A case study of Thailand. Quality Management Journal, 25(3), 129-141.