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All issues Volume 302 (2021) E3S Web Conf., 302 (2021) 01003 References
Open Access
Issue
E3S Web Conf.
Volume 302, 2021
2021 Research, Invention, and Innovation Congress (RI2C 2021)
Article Number 01003
Number of page(s) 10
Section Energy Technology
DOI https://doi.org/10.1051/e3sconf/202130201003
Published online 10 September 2021
  1. A. Mecke, I. Lee, J.R. Bakerjr., M.M. Banaszak Holl, W. Wen, Q. Zhang, A design of straw acquisition mode for China’s straw power plant based on supply chain coordination, Renewable energy, 76 (2015): 369-374 [Google Scholar]
  2. F. Rosillo-Calle, L. Pelkmans, A. Walter, A global overview of vegetable oils, with reference to biodiesel. A report for the IEA Bioenergy Task, 40 (2009) [Google Scholar]
  3. Thailand Board of Investment, Thailand 4.0 – a new value-based economy. (2019) URL: https://www.boi.go.th/ [Accessed 15 May 2020] [Google Scholar]
  4. A. Raychaudhuri, S. K. Ghosh, Biomass Supply Chain in Asian and European Countries. Procedia Environmental Sciences, 35 (2016): 914-924 [Google Scholar]
  5. REN21 Renewables global status report. (2019) URL: https://www.ren21.net/ [Accessed 15 March 2020] [Google Scholar]
  6. Y.S. Cheng, P. Mutrakulcharoen, S. Chuetor, K. Cheenkachorn, P. Tantayotai, E.J. Panakkal, M. Sriariyanun, Recent Situation and Progress in Biorefining Process of Lignocellulosic Biomass: Toward Green Economy. Applied Science and Engineering Progress, 13, 4 (2020): 299-311 [Google Scholar]
  7. A. Martsri, N. Yodpijit, M. Jongprasithporn, S. Junsupasen, Energy, Economic and Environmental (3E) Analysis for Sustainable Development: A Case Study of a 9.9 MW Biomass Power Plant in Thailand. Applied Science and Engineering Progress, (2021): DOI: 10.14416/j.asep.2020.07.002 [Google Scholar]
  8. DEDE Department of Alternative Energy and Energy Conservation. (2019) URL: http://www.dede.go.th/ [Accessed 15 July 2020] [Google Scholar]
  9. DEDE Research and Development in the field of Energy conservation and renewable energy in Thailand (2012) URL: http://weben.dede.go.th/ [Accessed 15 July 2020] [Google Scholar]
  10. K. Ransikarbum, S.J. Mason, Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations, International Journal of Production Research, 54, 1 (2016): 49-68 [Google Scholar]
  11. K. Ransikarbum, S.J. Mason, Goal programmingbased post-disaster decision making for integrated relief distribution and early-stage network restoration, International Journal of Production Economics, 182 (2016): 324-341 [CrossRef] [Google Scholar]
  12. K. Ransikarbum, S. Ha, J. Ma, N. Kim, Multiobjective optimization analysis for part-to-Printer assignment in a network of 3D fused deposition modelling, Journal of Manufacturing Systems, 43 (2017): 35-46 [Google Scholar]
  13. K. Ransikarbum, R. Leksomboon, Criteria Analysis for Additive Manufacturing-based Healthcare Educational Media using Analytic Hierarchy Process. KKU Research Journal (Graduate Studies), 21, 1 (2021): 133-144 [Google Scholar]
  14. C. Puchongkawarin, K. Ransikarbum, An Integrative Decision Support System for Improving Tourism Logistics and Public Transportation in Thailand, Tourism Planning & Development, (2020): 1-16 [Google Scholar]
  15. K. Ransikarbum, R. Pitakaso, N. Kim, A DecisionSupport Model for Additive Manufacturing Scheduling Using an Integrative Analytic Hierarchy Process and Multi-Objective Optimization, Applied Sciences, 10, 15 (2020): 51-59 [Google Scholar]
  16. C. Chaiyaphan, K. Ransikarbum, Criteria analysis of food safety using the Analytic Hierarchy Process (AHP)-a case study of Thailand’s fresh markets, In E3S Web of Conferences (EDP Sciences), 141, (2020): 02001 [Google Scholar]
  17. P. Khamhong, C. Yingviwatanapong, K. Ransikarbum, Fuzzy Analytic Hierarchy Process (AHP)-based Criteria Analysis for 3D Printer Selection in Additive Manufacturing, In 2019 Research Invention, and Innovation Congress (IEEE), (2019): 1-5 [Google Scholar]
  18. N. Wattanasaeng, K. Ransikarbum, Cost Optimization Model for Plant Assignment in Industrial Estate Planning, In 2019 Research Invention and Innovation Congress (IEEE), (2019): 1-6 [Google Scholar]
  19. K. Ransikarbum, N. Kim, Multi-criteria selection problem of part orientation in 3D fused deposition modeling based on analytic hierarchy process model: A case study, In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEE), (2017): 1455-1459 [Google Scholar]
  20. J.S. Liu, L.Y. Lu, W.M. Lu, B.J. Lin, Data envelopment analysis 1978–2010: A citation-based literature survey, Omega, 41(1), (2013): 3-15 [CrossRef] [Google Scholar]
  21. K. Ransikarbum, N. Kim, Data envelopment analysis-based multi-criteria decision making for part orientation selection in fused deposition modelling, In 2017 4th International Conference on Industrial Engineering and Applications, (2017): 81-85 [Google Scholar]
  22. K. Ransikarbum, R. Pitakaso, N. Kim, Evaluation of Assembly Part Build Orientation in Additive Manufacturing Environment using Data Envelopment Analysis, In MATEC Web of Conferences (EDP Sciences), 293 (2019): 02002 [Google Scholar]
  23. A. Charnes, W.W. Cooper, and E. Rhodes, Measuring the efficiency of decision making units. European journal of operational research, 2, 6 (1978): 429-444 [Google Scholar]
  24. R.D. Banker, A. Charnes, W.W. Cooper, Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management science, 30, 9 (1984): 1078-1092 [Google Scholar]
  25. OAE – Office of Agricultural Economics. (2019) URL: http://www.oae.go.th/ [Accessed 15 July 2020] [Google Scholar]
  26. M. Mirmozaffari, A. Boskabadi, G. Azeem, R. Massah, E. Boskabadi, H.A. Dolatsara, A. Liravian, Machine learning clustering algorithms based on the DEA optimization approach for banking system in developing countries. European Journal of Engineering and Technology Research, 5, 6 (2020): 651-658 [Google Scholar]
  27. K. Ransikarbum, N. Kim, S. Ha, R.A. Wysk, L. Rothrock, A highway-driving system design viewpoint using an agent-based modeling of an affordance-based finite state automata. IEEE Access, 6 (2017): 2193-2205 [Google Scholar]
  28. J. Kim, K. Ransikarbum, N. Kim, E. Paik, Agentbased simulation modeling of low fertility trap hypothesis. In Proceedings of the 2016 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, (2016): 83-86 [Google Scholar]
  29. A. Apornak, S. Raissi, M.R. Pourhassan, Solving flexible flow-shop problem using a hybrid multi criteria Taguchi based computer simulation model and DEA approach. Journal of Industrial and Systems Engineering, 13, 2 (2021): 264-276 [Google Scholar]
  30. A. Tayal, A. Solanki, S.P. Singh, Integrated frame work for identifying sustainable manufacturing layouts based on big data, machine learning, metaheuristic and data envelopment analysis. Sustainable Cities and Society, 62 (2020): 102383 [Google Scholar]
  31. N. Wattanasaeng, K. Ransikarbum, Model and Analysis of Economic-and Risk-Based Objective Optimization Problem for Plant Location within Industrial Estates Using Epsilon-Constraint Algorithms. Computation, 9, 4 (2021): 46 [Google Scholar]
  32. K. Ransikarbum, P. Khamhong, Integrated Fuzzy Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution for Additive Manufacturing Printer Selection. Journal of Materials Engineering and Performance, (2021): 1-12 [Google Scholar]
  33. W. Chanthakhot, K. Ransikarbum, Integrated IEWTOPSIS and Fire Dynamics Simulation for AgentBased Evacuation Modeling in Industrial Safety, Safety, 7, 2 (2021): 47 [Google Scholar]
  34. K. Ransikarbum, R. Pitakaso, N. Kim, J. Ma, Multicriteria decision analysis framework for part orientation analysis in additive manufacturing, Journal of Computational Design and Engineering, 8, 4 (2021): 1141-1157 [Google Scholar]

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