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Mixed-Integer Linear Program for the Operational Harvest Scheduling Problem: An Application to the Thai Sugar Industry

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Published:21 September 2020Publication History

ABSTRACT

Thai sugar industry is relatively unique due to the existence of local restrictions and practices, such as grower equity and sugarcane farm burning. All of which are interrelated and stipulated by different conflicting objectives of different key supply chain actors. In order to address these issues, a mixed-integer linear programming model for this so-called Operational Harvest Scheduling Problem (OHSP) is formulated and solved under four different aspects: (i) maximizing sugarcane input, (ii) maximizing grower profits, (iii) minimizing industrial yield loss, and (iv) minimizing environmental impact. Our preliminary computational results on 30 fictitious instances indicated that, regardless of the chosen objectives, the resulting sugarcane input did not differ much, with the maximal gap around 10% across four settings. Nonetheless, the other three objective values differed greatly and depended on the harvesting resource selection. More specifically, green sugarcane harvesting was the best in terms of both carbon emission and grower interests, while burnt sugarcane harvesting was the best in terms of extractable sugar amount. We also found that the number of harvesting resources largely affected the quality of the OHSP solutions.

References

  1. Kanjana Sethanan. 2015. Metaheuristics and Application for Industry. Klungnana Vitthaya, Bangkok, Thailand.Google ScholarGoogle Scholar
  2. Valentina Pagani et al. 2017. Forecasting sugarcane yields using agro-climatic indicators and Canegro model: A case study in the main production region in Brazil. Agricultural System, Vol.154 (Jun. 2017), 45--52. DOI: http://dx.doi.org/10.1016/j.agsy.2017.03.002.Google ScholarGoogle Scholar
  3. Yu Zhao et al. Dynamics modeling for sugarcane sucrose estimation using time series satellite imagery. SPIE, Vol.9998 (Oct. 2016), 99980J. DOI: https://doi.org/10.1117/12.2242490.Google ScholarGoogle Scholar
  4. Surached Thuankaewsing et al. Harvest scheduling algorithm to equalize supplier benefits: A case study from the Thai sugar cane industry. Computers and Electronics in Agriculture, Vol. 110 (Jan. 2015), 42--55. DOI: http://dx.doi.org/10.1016/j.compag.2014.10.005.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Kriengkri Kaewtrakulpong. 2008. Multi-objective Optimization for Cost Reduction of Mechanical Sugarcane Harvesting and Transportation in Thailand. Ph.D. Dissertation. Graduate School of Life and Environmental Science, University of Tsukuba, Tsukuba, Japan. Retrieved December 11, 2019 from http://hdl.handle.net/2241/101176.Google ScholarGoogle Scholar
  6. TGO. Thailand Greenhouse Gas Management Organization. 2019. Emission Factor. (October 2019). Retrieved February 17, 2020 from http://thaicarbonlabel.tgo.or.th/products_emission/products_emission.pnc.Google ScholarGoogle Scholar
  7. PTT. PTT Pubic Company Limited. 2019. Metropolitan Bangkok retail oil prices for the year 2019. (December 2019). Retrieved February 17, 2020 from https://web1.pttplc.com/en/Media-Center/Oil-Price/Pages/Bangkok-Oil-Price.asp.Google ScholarGoogle Scholar
  8. Wichai Opanukul et al. 2012. Study of Sugarcane Harvester Used in Thailand. In proceeding of the 13th. Annual Conference of Thai Society of Agricultural Engineering (TSAE), International Conference on Agricultural Engineering, April 3 -- 4, 2012, Chiang Mai, Thailand. TSAE, 106--115. Retrieved December 11, 2019 from http://www.tsae.asia/data/2012conf/pdf/AME/AME14.pdf.Google ScholarGoogle Scholar
  9. S. Solomon et al. 2007. An assessment of postharvest sucrose losses in sugarcane billets under sub--tropical conditions. In proceeding of the 26th International Society of Sugar Cane Technologists (ISSCT), July 26 -- August 2, 2007, Durban, South Africa. ISSCT, 1513 -- 1521. Retrieved December 14, 2019 from http://www.issct.org/proceedings/2007.html.Google ScholarGoogle Scholar

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  1. Mixed-Integer Linear Program for the Operational Harvest Scheduling Problem: An Application to the Thai Sugar Industry

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          cover image ACM Other conferences
          IMMS '20: Proceedings of the 3rd International Conference on Information Management and Management Science
          August 2020
          120 pages
          ISBN:9781450375467
          DOI:10.1145/3416028

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          Publication History

          • Published: 21 September 2020

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