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ÇAY HASADI ÇİZELGELEME İÇİN MATEMATİKSEL MODEL ÖNERİSİ

Year 2023, Volume: 11 Issue: 3, 925 - 938, 28.09.2023

Bedirhan Sarımehmet Hacı Mehmet Alakaş Mehmet Pınarbaşı Tamer Eren

https://doi.org/10.21923/jesd.1244145
Cited By: 1

Abstract

Uluslar sürdürülebilir tarım faaliyetleri gerçekleştirmek için toplumsal olarak karar mekanizması geliştirmeye ve optimizasyona ihtiyaç duymaktadır. Hasat çizelgeleme de bu karar verme ve optimizasyon problemlerinden biridir. Bu çalışmada, yılda ortalama üç kez hasat edilen çay bitkisi için bir hasat optimizasyonu gerçekleştirilmiştir. Çiftçilikle mevsimlik olarak ilgilenen insanların genellikle birincil meslekleri farklıdır. Hasat günlerinde çiftçiler bu birincil mesleklerini yerine getirememektedir. Bu nedenle, hasat çizelgesinin oluşturulması için çiftçilerin uygun gün tercihlerinin de dikkate alınması sürdürülebilir tarım adına önem taşımaktadır. Bu çalışmada fabrika ve alım yeri kapasitelerinin yanı sıra çiftçilerin uygun/uygun olmayan gün tercihlerini optimize etmek için hedef programlama modelleri geliştirilmiştir. Gerçekleştirilen vaka çalışması sahası şu özelliklere sahiptir: 12 alım yeri, 988 çiftçi ve 3392 dekar çay tarlası. Önerilen modelin performansının test edilmesi için çiftçi uygun/uygun olmayan günlerinin rassal olarak belirlendiği veri setleri üretilmiştir. Bu şekilde birbirinden farklı üretilen bin ayrı veri seti ile duyarlılık analizi yapılmıştır. Yapılan analizler önerilen modeller ile oluşturulan çizelgelerin çay hasat sürecindeki sürdürülebilirliği ve verimliliği artırdığını göstermiştir.

Keywords

Hasat Optimizasyonu Çay Hasadı Çizelgeleme Matematiksel Modelleme Hedef Programlama

References

  • Andrei, J. V., Popescu, G. H., Nica, E., Chivu, L., 2020. The Impact of Agrıcultural Performance on Foreign Trade Concentration and Competitiveness: Empirical Evidence From Romanian Agrıculture. Journal of Business Economics and Management, 21(2), 317–343.
  • Astika, I. W., Sasao, A., Djojomartono, M., Pertıwı, S., Wıryokusumo, H., 1997. Optimization of Sugarcane Planting-harvesting Schedule for Dry Land Sugarcane Plantations. Journal of the Japanese Society of Agricultural Machinery, 59(5), 73–81.
  • Budijati, S. M., Iskandar, B. P., 2018. Dynamic programming to solve picking schedule at the tea plantation. International Journal of Engineering and Technology, 7(4), 285-290.
  • Busato, P., Berruto, R., 2016. Minimising Manpower in Rice Harvesting and Transportation Operations. Biosystems Engineering, 151, 435–445.
  • Ceylan, Z., Karan, R. E., Bakırcı, Ç., Sabuncu, S., 2019. Single Machine Scheduling Problem with Sequence Dependent Setup Times: An Application in White Goods Industry. International Journal of Multidisciplinary Studies and Innovative Technologies, 3(1), 14–21.
  • Charnes, A., Cooper, W. W., Ferguson, R. O., 1955. Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138–151.
  • Çolak, R., Yiğit, T., 2021. Üniversite Ders Çizelgeleme Probleminin Genetik Algoritma ile Optimizasyonu. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 9(6), 150–166.
  • Cullum, J., Binns, J., Lonsdale, M., Abbassi, R., Garaniya, V., 2018. Risk-Based Maintenance Scheduling with Application to Naval Vessels and Ships. Ocean Engineering, 148, 476–485.
  • Çaykur 2019 Çay Sektörü Raporu. (2022, December 16). https://www.caykur.gov.tr/Pages/Yayinlar/YayinDetay.aspx?ItemType=5&ItemId=721
  • Dağdeviren, M., Eren, T., 2001. Tedarikçi Firma Seçiminde Analitik Hiyerarşi Prosesi ve 0-1 Hedef Programlama Yöntemlerinin Kullanılması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 16(1), 41–52.
  • Dündar, D. R., Sarıçiçek, İ., Yazıcı, A., 2021. Bakım Faaliyetlerini Dikkate Alan Makine Çizelgeleme: Literatür Araştırması. Uludağ University Journal of The Faculty of Engineering, 26(2), 737–756.
  • Edwards, G., Sørensen, C. G., Bochtis, D. D., Munkholm, L. J., 2015. Optimised Schedules for Sequential Agricultural Operations Using a Tabu Search Method. Computers and Electronics in Agriculture, 117, 102–113.
  • Eren, T., Bedir, N., Taş, C., 2018. 0-1 Tamsayılı Programlama ile Ders Programı Çizelgeleme Probleminin Çözümü: Bir Yükseköğretim Kurumunda Uygulama. Harran Üniversitesi Mühendislik Dergisi, 3(3), 166–175.
  • Fanjul-Peyro, L., Ruiz, R., Perea, F., 2019. Reformulations and an Exact Algorithm for Unrelated Parallel Machine Scheduling Problems with Setup Times. Computers & Operations Research, 101, 173–182.
  • Grunow, M., Günther, H.-O., Westinner, R., 2007. Supply Optimization for the Production of Raw Sugar. International Journal of Production Economics, 110(1), 224–239.
  • He, P., Li, J., Wang, X., 2018a. Wheat Harvest Schedule Model for Agricultural Machinery Cooperatives Considering Fragmental Farmlands. Computers and Electronics in Agriculture, 145, 226–234.
  • He, P., Li, J., Zhang, D., Wan, S., 2018b. Optimisation of the Harvesting Time Of rice in Moist and Non-Moist Dispersed Fields. Biosystems Engineering, 170, 12–23.
  • Higgins, A. J., Muchow, R. C., Rudd, A. v, Ford, A. W., 1998. Optimising Harvest Date in Sugar Production: A Case Study for the Mossman Mill Region in Australia: I. Development Of Operations Research Model And Solution. Field Crops Research, 57(2), 153–162.
  • Karlı, B., Gül, M., Kadakoğlu, B., 2018. Türkiye’de Tarımda Üretici Örgütlenmesinin Önemi ve Gelişimi. Akademia Sosyal Bilimler Dergisi, 318–329.
  • Lei, D., Liu, M., 2020. An Artificial Bee Colony with Division for Distributed Unrelated Parallel Machine Scheduling with Preventive Maintenance. Computers & Industrial Engineering, 141, 106320.
  • Lei, D., Yuan, Y., Cai, J., 2021. An İmproved Artificial Bee Colony for Multi-Objective Distributed Unrelated Parallel Machine Scheduling. International Journal of Production Research, 59(17), 5259–5271.
  • Leung, S. C. H., Wu, Y., Lai, K. K., 2003. Multi-Site Aggregate Production Planning with Multiple Objectives: A Goal Programming Approach. Production Planning & Control, 14(5), 425–436.
  • Naghdi Badi, H., Yazdani, D., Ali, S. M., Nazari, F., 2004. Effects of Spacing and Harvesting Time on Herbage Yield and Quality/Quantity of Oil in Thyme, Thymus Vulgaris L. Industrial Crops and Products, 19(3), 231–236.
  • Özcan, E., Danışan, T., Eren, T., 2020. Hidroelektrik Santrallarda Bakım Çizelgeleme İçin Hibrid Bir Model Önerisi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 35(4), 1815-1828.
  • Poltroniere, S. C., Aliano Filho, A., Caversan, A. S., Balbo, A. R., Florentino, H. de O., 2021. Integrated Planning for Planting and Harvesting Sugarcane and Energy-Cane for the Production of Sucrose and Energy. Computers and Electronics in Agriculture, 184, 105956.
  • Rollan, C. D., Li, R., San Juan, J. L., Dizon, L., Ong, K. B., 2018. A Planning Tool for Tree Species Selection and Planting Schedule in Forestation Projects Considering Environmental and Socio-Economic Benefits. Journal of Environmental Management, 206, 319–329.
  • Sajid, S. S., Hu, G., 2022. Optimizing Crop Planting Schedule Considering Planting Window and Storage Capacity. Frontiers in Plant Science, 13.
  • Sarımehmet, B., Pınarbaşı, M., Alakaş, H.M., Eren, T. 2023. Çiftçi ve Fabrika İş Birliği ile Sürdürülebilir Hasat Çizelgeleme. 5th International Conference on Applied Engineering and Natural Sciences, 1(1), 702-707.
  • Salassi, M. E., Breaux, J. B., Naquin, C. J., 2002. Modeling Within-Season Sugarcane Growth for Optimal Harvest System Selection. Agricultural Systems, 73(3), 261–278.
  • Thuankaewsing, S., Pathumnakul, S., Piewthongngam, K., 2011. Using an Artificial Neural Network and a Mathematical Model for Sugarcane Harvesting Scheduling. 2011 IEEE International Conference on Industrial Engineering and Engineering Management, 308–312.
  • Ünal, F. M., Eren, T., 2016. Hedef Programlama ile Nöbet Çizelgeleme Probleminin Çözümü. Academic Platform Journal of Engineering and Science, 4(1), 28-37.
  • Varlı, E., Eren, T., 2017a. Hemşire Çizelgeleme Problemi ve Hastanede Bir Uygulama. Academic Platform - Journal of Engineering and Science, 5(1), 34–40.
  • Winston, C., 1962. Management Models and Industrial Applications of Linear Programming, Vol. 1 (A. Charnes and WW Cooper). Society for Industrial and Applied Mathematics ,4(1), 38-91.
  • Yurtsal, A., Kaynar, O., 2022. Sezgisel Algoritmalar Yardımıyla Ders Programı Optimizasyonu. Uluslararası Ekonomi ve Yenilik Dergisi, 8(1), 1-18.

MATHEMATİCAL MODEL SUGGESTİON FOR TEA HARVEST SCHEDULİNG

Year 2023, Volume: 11 Issue: 3, 925 - 938, 28.09.2023

Bedirhan Sarımehmet Hacı Mehmet Alakaş Mehmet Pınarbaşı Tamer Eren

https://doi.org/10.21923/jesd.1244145
Cited By: 1

Abstract

Nations need social decision-making mechanism and optimization to realize sustainable agricultural activities. Harvest scheduling is one of these decision-making and optimization problems. In this study, a harvest optimization is performed for tea plant which is harvested three times a year on average. People who are seasonally interested in farming are often different from their primary professions. On harvest days, farmers are unable to fulfill these primary professions. For this reason, it is important for sustainable agriculture to consider the available day preferences of the farmers for the creation of the harvest schedule. In this study, goal programming models are developed to optimize the deviations from the available/unavailable days preference of the farmers, as well as the capacities of the factory and the storage location. The case study area has the following characteristics: 12 storage locations, 988 farmers and 3392 decares of tea fields. To test the proposed model performance, data set were generated in which farmer suitable/unsuitable days are determined randomly. In this way, sensitivity analysis are performed with a thousand data set generated differently from each other. The analyzes have shown that the schedules created with the proposed models increase the sustainability and efficiency in the tea harvesting process.

Keywords

Harvest Optimization Tea Harvest Scratches Mathematical Modeling Goal Programming

References

  • Andrei, J. V., Popescu, G. H., Nica, E., Chivu, L., 2020. The Impact of Agrıcultural Performance on Foreign Trade Concentration and Competitiveness: Empirical Evidence From Romanian Agrıculture. Journal of Business Economics and Management, 21(2), 317–343.
  • Astika, I. W., Sasao, A., Djojomartono, M., Pertıwı, S., Wıryokusumo, H., 1997. Optimization of Sugarcane Planting-harvesting Schedule for Dry Land Sugarcane Plantations. Journal of the Japanese Society of Agricultural Machinery, 59(5), 73–81.
  • Budijati, S. M., Iskandar, B. P., 2018. Dynamic programming to solve picking schedule at the tea plantation. International Journal of Engineering and Technology, 7(4), 285-290.
  • Busato, P., Berruto, R., 2016. Minimising Manpower in Rice Harvesting and Transportation Operations. Biosystems Engineering, 151, 435–445.
  • Ceylan, Z., Karan, R. E., Bakırcı, Ç., Sabuncu, S., 2019. Single Machine Scheduling Problem with Sequence Dependent Setup Times: An Application in White Goods Industry. International Journal of Multidisciplinary Studies and Innovative Technologies, 3(1), 14–21.
  • Charnes, A., Cooper, W. W., Ferguson, R. O., 1955. Optimal estimation of executive compensation by linear programming. Management Science, 1(2), 138–151.
  • Çolak, R., Yiğit, T., 2021. Üniversite Ders Çizelgeleme Probleminin Genetik Algoritma ile Optimizasyonu. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 9(6), 150–166.
  • Cullum, J., Binns, J., Lonsdale, M., Abbassi, R., Garaniya, V., 2018. Risk-Based Maintenance Scheduling with Application to Naval Vessels and Ships. Ocean Engineering, 148, 476–485.
  • Çaykur 2019 Çay Sektörü Raporu. (2022, December 16). https://www.caykur.gov.tr/Pages/Yayinlar/YayinDetay.aspx?ItemType=5&ItemId=721
  • Dağdeviren, M., Eren, T., 2001. Tedarikçi Firma Seçiminde Analitik Hiyerarşi Prosesi ve 0-1 Hedef Programlama Yöntemlerinin Kullanılması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 16(1), 41–52.
  • Dündar, D. R., Sarıçiçek, İ., Yazıcı, A., 2021. Bakım Faaliyetlerini Dikkate Alan Makine Çizelgeleme: Literatür Araştırması. Uludağ University Journal of The Faculty of Engineering, 26(2), 737–756.
  • Edwards, G., Sørensen, C. G., Bochtis, D. D., Munkholm, L. J., 2015. Optimised Schedules for Sequential Agricultural Operations Using a Tabu Search Method. Computers and Electronics in Agriculture, 117, 102–113.
  • Eren, T., Bedir, N., Taş, C., 2018. 0-1 Tamsayılı Programlama ile Ders Programı Çizelgeleme Probleminin Çözümü: Bir Yükseköğretim Kurumunda Uygulama. Harran Üniversitesi Mühendislik Dergisi, 3(3), 166–175.
  • Fanjul-Peyro, L., Ruiz, R., Perea, F., 2019. Reformulations and an Exact Algorithm for Unrelated Parallel Machine Scheduling Problems with Setup Times. Computers & Operations Research, 101, 173–182.
  • Grunow, M., Günther, H.-O., Westinner, R., 2007. Supply Optimization for the Production of Raw Sugar. International Journal of Production Economics, 110(1), 224–239.
  • He, P., Li, J., Wang, X., 2018a. Wheat Harvest Schedule Model for Agricultural Machinery Cooperatives Considering Fragmental Farmlands. Computers and Electronics in Agriculture, 145, 226–234.
  • He, P., Li, J., Zhang, D., Wan, S., 2018b. Optimisation of the Harvesting Time Of rice in Moist and Non-Moist Dispersed Fields. Biosystems Engineering, 170, 12–23.
  • Higgins, A. J., Muchow, R. C., Rudd, A. v, Ford, A. W., 1998. Optimising Harvest Date in Sugar Production: A Case Study for the Mossman Mill Region in Australia: I. Development Of Operations Research Model And Solution. Field Crops Research, 57(2), 153–162.
  • Karlı, B., Gül, M., Kadakoğlu, B., 2018. Türkiye’de Tarımda Üretici Örgütlenmesinin Önemi ve Gelişimi. Akademia Sosyal Bilimler Dergisi, 318–329.
  • Lei, D., Liu, M., 2020. An Artificial Bee Colony with Division for Distributed Unrelated Parallel Machine Scheduling with Preventive Maintenance. Computers & Industrial Engineering, 141, 106320.
  • Lei, D., Yuan, Y., Cai, J., 2021. An İmproved Artificial Bee Colony for Multi-Objective Distributed Unrelated Parallel Machine Scheduling. International Journal of Production Research, 59(17), 5259–5271.
  • Leung, S. C. H., Wu, Y., Lai, K. K., 2003. Multi-Site Aggregate Production Planning with Multiple Objectives: A Goal Programming Approach. Production Planning & Control, 14(5), 425–436.
  • Naghdi Badi, H., Yazdani, D., Ali, S. M., Nazari, F., 2004. Effects of Spacing and Harvesting Time on Herbage Yield and Quality/Quantity of Oil in Thyme, Thymus Vulgaris L. Industrial Crops and Products, 19(3), 231–236.
  • Özcan, E., Danışan, T., Eren, T., 2020. Hidroelektrik Santrallarda Bakım Çizelgeleme İçin Hibrid Bir Model Önerisi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 35(4), 1815-1828.
  • Poltroniere, S. C., Aliano Filho, A., Caversan, A. S., Balbo, A. R., Florentino, H. de O., 2021. Integrated Planning for Planting and Harvesting Sugarcane and Energy-Cane for the Production of Sucrose and Energy. Computers and Electronics in Agriculture, 184, 105956.
  • Rollan, C. D., Li, R., San Juan, J. L., Dizon, L., Ong, K. B., 2018. A Planning Tool for Tree Species Selection and Planting Schedule in Forestation Projects Considering Environmental and Socio-Economic Benefits. Journal of Environmental Management, 206, 319–329.
  • Sajid, S. S., Hu, G., 2022. Optimizing Crop Planting Schedule Considering Planting Window and Storage Capacity. Frontiers in Plant Science, 13.
  • Sarımehmet, B., Pınarbaşı, M., Alakaş, H.M., Eren, T. 2023. Çiftçi ve Fabrika İş Birliği ile Sürdürülebilir Hasat Çizelgeleme. 5th International Conference on Applied Engineering and Natural Sciences, 1(1), 702-707.
  • Salassi, M. E., Breaux, J. B., Naquin, C. J., 2002. Modeling Within-Season Sugarcane Growth for Optimal Harvest System Selection. Agricultural Systems, 73(3), 261–278.
  • Thuankaewsing, S., Pathumnakul, S., Piewthongngam, K., 2011. Using an Artificial Neural Network and a Mathematical Model for Sugarcane Harvesting Scheduling. 2011 IEEE International Conference on Industrial Engineering and Engineering Management, 308–312.
  • Ünal, F. M., Eren, T., 2016. Hedef Programlama ile Nöbet Çizelgeleme Probleminin Çözümü. Academic Platform Journal of Engineering and Science, 4(1), 28-37.
  • Varlı, E., Eren, T., 2017a. Hemşire Çizelgeleme Problemi ve Hastanede Bir Uygulama. Academic Platform - Journal of Engineering and Science, 5(1), 34–40.
  • Winston, C., 1962. Management Models and Industrial Applications of Linear Programming, Vol. 1 (A. Charnes and WW Cooper). Society for Industrial and Applied Mathematics ,4(1), 38-91.
  • Yurtsal, A., Kaynar, O., 2022. Sezgisel Algoritmalar Yardımıyla Ders Programı Optimizasyonu. Uluslararası Ekonomi ve Yenilik Dergisi, 8(1), 1-18.
There are 34 citations in total.

Details

Primary Language Turkish
Subjects Industrial Engineering
Journal Section Research Articles
Authors

Bedirhan Sarımehmet 0000-0002-6112-9460

Hacı Mehmet Alakaş 0000-0002-9874-7588

Mehmet Pınarbaşı 0000-0003-3424-2967

Tamer Eren 0000-0001-5282-3138

Publication Date September 28, 2023
Submission Date January 30, 2023
Acceptance Date August 15, 2023
Published in Issue Year 2023 Volume: 11 Issue: 3

Cite

APA Sarımehmet, B., Alakaş, H. M., Pınarbaşı, M., Eren, T. (2023). ÇAY HASADI ÇİZELGELEME İÇİN MATEMATİKSEL MODEL ÖNERİSİ. Mühendislik Bilimleri Ve Tasarım Dergisi, 11(3), 925-938. https://doi.org/10.21923/jesd.1244145

Cited By

Harvest optimization for sustainable agriculture: The case of tea harvest scheduling
Artificial Intelligence in Agriculture
https://doi.org/10.1016/j.aiia.2023.10.001
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