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Son Hâsılat Kesim Planlarının Amaç Programlama Kullanılarak Hazırlanması

Yıl 2021, Cilt: 17 Sayı: 1, 116 - 141, 30.06.2021

Öz

Bu çalışmada, aynıyaşlı koru ormanlarının son hâsılat kesim planlarının hazırlanmasında amaç programlamanın kullanımı incelenmiştir. Çalışmada kullanılan doğrusal amaç programlama modelinin amaç satırı, yıllık gençleştirme sahası (82,84 ha) ve yıllık son hâsılat etası (15.692 m3) hedeflerinden sapmaları en aza indirmektedir. Çalışmanın kısıtlarını ise toplamları 25 ha veya daha fazla olan komşu bölmecik çiftlerinin erteleme süresi (3 yıl) boyunca birlikte gençleştirilmemesi ile toplamları 6 ha veya daha az olan komşu bölmecik çiftlerinin aynı yıl gençleştirilmesi oluşturmaktadır. Model, Lingo 18 kullanılarak 11 farklı senaryo için çözülmüştür. Alan ve hacim sapmaları birlikte değerlendirildiğinde en iyi sonucu veren senaryo 3’te, yıllık gençleştirme alanı hedefinden toplam sapma 1,64 ha, diğer bir deyişle periyodik gençleştirme alanının sadece %0.20’si kadardır. Yıllık son hâsılat etası hedefinden toplam sapma ise 303 m3tür (periyodik son hâsılat etasının %0,19’u kadar). Çalışmada uygulanan yöntem özellikle kızılçam ormanlarının son hâsılat kesim planlarının ve detay silvikültür planlarının hazırlanmasında rahatlıkla kullanılabilir.

Teşekkür

Çalışmada kullanılan veriler Orman Genel Müdürlüğü Orman İdaresi ve Planlama Dairesi Başkanlığı tarafından sağlanmıştır. Bu vesileyle Orman İdaresi ve Planlama Dairesi Başkanlığı yöneticilerine ve teknik personeline şükranlarımızı sunarız.

Kaynakça

  • Aldea, J., Martínez-Peña, F., Romero, C. & Diaz-Balteiro, L. (2014). Participatory goal programming in forest management: An application integrating several ecosystem services. Forests, 5(12), 3352-3371.
  • Alp, S. (2008). Doğrusal Hedef Programlama Yönteminin Otobüsle Kent İçi Toplu Taşıma Sisteminde Kullanılması, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, Yıl:7 Sayı:13, 73-91.
  • Augustynczik, A.L.D., Arce, J.E. & da Silva, A.C.L. (2016). Aggregating forest harvesting activities in forest plantations through integer linear programming and goal programming. Journal of Forest Economics, 24, 72-81.
  • Bagdon, B.A., Huang, C.-H. & Dewhurst, S. (2016). Managing for ecosystem services in northern Arizona ponderosa pine forests using a novel simulation-to-optimization methodology. Ecological Modelling, 324, 11-27.
  • Bertomeu, M. & Romero, C. (2001). Managing forest biodiversity: a zero-one goal programming approach. Agricultural Systems, 68, 197-213.
  • Bertomeu, M. & Romero, C. (2002). Forest management optimization models and habitat diversity: a goal programming approach. Journal of the Operational Research Society, 53, 1175-1184.
  • Bell, E.F. (1975). Problems with goal programming on a national forest planning unit. Systems Analysis and Forest Resource Management, 119-126, Athens, Georgia.
  • Charnes, A. & Cooper, W.W. (1961). Management models and industrial applications of linear programming: Vol 1. New York: John Wiley & Sons.
  • Chen, Y.-T. & Chang, C.-T. (2014). Multi-coefficient goal programming in thinning schedules to increase carbon sequestration and improve forest structure. Annals of Forest Science, 71(8), 907-915.
  • Chen, Y.-T., Zheng, C. & Chang, C.-T. (2011). 3-level MCGP: An efficient algorithm for MCGP in solving multi-forest management problems. Scandinavian Journal of Forest Research, 26(5), 457-465.
  • Cyr, G., Raulier, F., Fortin, D. & Pothier, D. (2017). Using operating area size and adjacency constraints to mitigate the effects of harvesting activities on boreal caribou habitat. Landscape Ecology, 32(2), 377-395.
  • Dahlin, B. & Sallnäs, O. (1993). Harvest scheduling under adjacency constraints-a case study from the Swedish sub-alpine region. Scandinavian Journal of Forest Research, 8, 281-290.
  • De Kluyver, C.A. (1979). An exploration of various goal programming formulations - with application to advertising media scheduling. Journal of the Operational Research Society, 30(2), 167-171.
  • Demirci, M. (2018). Orman Amenajman Planlamasında Karışık Tamsayılı Amaç Programlamanın Kullanılması: Akören Plan Ünitesi Örneği. Doktora Tezi, İstanbul Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • Demirci, M. & Bettinger, P. (2015). Using mixed integer multi-objective goal programming for stand tending block designation: A case study from Turkey. Forest Policy and Economics, 55, 28-36.
  • Demirci, M., Yeşil, A. & Bettinger, P. (2020). Using mixed integer goal programming in final yield harvest planning: A case study from the Mediterranean region of Turkey. Forests, 11(7), 744.
  • Diaz-Balteiro, L. & Romero, C. (2003). Forest management optimization models when carbon captured is considered: a goal programming approach. Forest Ecology and Management, 174, 447-457.
  • Eraslan, İ. (1982). Orman Amenajmanı. İstanbul: İ.Ü. Orman Fakültesi.
  • Etemad, S.S., Limaei, S.M., Olsson, L. & Yousefpour, R. (2019). Forest management decision-making using goal programming and fuzzy analytic hierarchy process approaches (case study: Hyrcanian forests of Iran). Journal of Forest Science, 65, 368-379.
  • FAO (2020). Global Forest Resources Assessment 2020 – Main report. Roma: FAO.
  • Field, D.B. (1973). Goal programming for forest management. Forest Science, 19(2), 125-135.
  • Gómez, T., Hernández, M., Molina, J., León, M.A., Aldana, E. & Caballero, R. (2011). A multi objective model for forest planning with adjacency constraints. Annals of Operations Research, 190(1), 75-92.
  • Hossain, S.M.Y. & Robak, E.W. (2010). A forest management process to incorporate multiple objectives: A framework for systematic public input. Forests, 1(3), 99-113.
  • Jones, D.F. (1995). The Design and Development of an Intelligent Goal Programming System. PhD Dissertation. University of Portsmouth, Portsmouth.
  • Liu, W.-Y., Lin, C.-C. & Su, K.-H. (2017). Modelling the spatial forest-thinning planning problem considering carbon sequestration and emissions. Forest Policy and Economics, 78, 51-66.
  • Maroto, C., Segura, M., Ginestar, C., Uriol, J. & Segura, B. (2013). Sustainable forest management in a Mediterranean region: Social preferences. Forest Systems, 22(3), 546-458.
  • Marinescu, M.V. & Maness, T.C. (2010). A hierarchical timber allocation model to analyze sustainable forest management decisions. Mathematical and Computational Forestry & Natural-Resource Sciences, 2(2), 117-134.
  • Masud, A.S. & Hwang, C.L. (1981). Interactive sequential goal programming. Journal of the Operational Research Society, 32, 391-400.
  • Mısır, M. (2001). Çok Amaçlı Orman Amenajman Planlarının Coğrafi Bilgi Sistemlerine Dayalı Olarak amaç Programlama Yöntemiyle Düzenlenmesi (Ormanüstü Planlama Birimi Örneği). Doktora Tezi. KTÜ Fen Bilimleri Enstitüsü, Trabzon.
  • Mısır, N. & Mısır, M. (2007). Developing a multi-objective forest planning process with goal programming: a case study. Pakistan Journal of Biological Sciences, 10, 514-522.
  • OGM (2008). Orman Amenajman Yönetmeliği (Sayı: 26778). Ankara: Orman Genel Müdürlüğü.
  • OGM (2013). Fethiye Orman İşletme Şefliği Fonksiyonel Orman Amenajman Planı. Ankara: Orman Genel Müdürlüğü.
  • OGM (2014). Silvikültürel Uygulamaların Teknik Esasları (Tebliğ No: 298). Ankara: Orman Genel Müdürlüğü, Silvikültür Dairesi Başkanlığı.
  • OGM (2015). Türkiye Orman Varlığı 2015. Ankara: Orman Genel Müdürlüğü.
  • OGM (2017). Ekosistem Tabanlı Fonksiyonel Orman Amenajman Planlarının Düzenlenmesine Ait Usul ve Esaslar (Tebliğ No: 299). Ankara: Orman Genel Müdürlüğü, Orman İdaresi ve Planlama Dairesi Başkanlığı.
  • O’Hara, A.J., Faaland, B.H. & Bare, B.B. (1989). Spatially constrained timber harvest scheduling. Canadian Journal of Forest Research, 19(6), 715-724.
  • Öhman, K. (2001). Forest planning with consideration to spatial relationships. Thesis Dissertation. Swedish University of Agricultural Sciences, Uppsala.
  • Özkan, M. (2014). Bulanık Hedef Programlama ve Bir İşletme Üzerinde Uygulama. Doktora Tezi. Sivas Cumhuriyet Üniversitesi, Sosyal Bilimler Enstitüsü, Sivas.
  • Porterfield, R.L. (1973). Predicted and potential gains from tree improvement programs-a goal programming analysis of program efficiency. PhD Dissertation. Yale University, New Haven, Connecticut.
  • Tamiz, M., Jones, D. & Romero, C. (1998). Goal programming for decision making: an overview of the current state-of-the-art. European Journal of Operational Research, 111(3), 569-581.
  • Tarp, P. & Helles, F. (1997). Spatial optimization by simulated annealing and linear programming. Scandinavian Journal of Forest Research, 12, 390-402.
  • Qin, H., Dong, L. & Huang, Y. (2017). Evaluating the Effects of Carbon Prices on Trade-Offs between Carbon and Timber Management Objectives in Forest Spatial Harvest Scheduling Problems: A Case Study from Northeast China. Forests, 8(2), 43.
  • Romero, C. (1991). Handbook of Critical Issues in Goal Programming. Oxford: Pergamon Press.
  • Romesburg, H.C. (1974). Scheduling models for wilderness recreation. Journal of Environmental Management, 2, 159-177.
  • Rustagi, K.P. 1973. Forest management planning for timber production: a goal programming approach. PhD Dissertation. Yale University, New Haven, Connecticut.
  • Schuler, A.T. & Meadows, J.C. (1975). Planning resource use on natural forests to achieve multiple objectives. Journal of Environmental Management, 3, 351-366.
  • Silva, M., Weintraub, A., Romero, C. & De la Maza, C. (2010). Forest harvesting and environmental protection based on the goal programming approach. Forest Science, 56(5), 460-472.
  • Weintraub, A., Barahona, F. & Epstein, R. (1994). A column generation algorithm for solving general forest planning problems with adjacency constraints. Forest Science, 40(1), 142-161.
  • Wildhelm, W.B. (1981). Extensions of goal programming models. Omega, 9, 212-214.
  • Zengin, H., Asan, Ü., Destan, S., Ünal, M.E., Yeşil, A., Bettinger, P. & Değermenci, A.S. (2015). Modeling harvest scheduling in multifunctional planning of forests for long term water yield optimization. Natural Resource Modeling, 28(1), 59-85.

Preparation of Final Yield Harvest Plans by Using Goal Programming

Yıl 2021, Cilt: 17 Sayı: 1, 116 - 141, 30.06.2021

Öz

In this study, the use of goal programming in preparing the final yield harvest plans of the even-aged high forests was examined. The objective function of the linear goal programming model used in the study minimized deviations from the annual regeneration area (82.84 ha) and the annual final yield harvest volume (15.692 m3) targets. The constraints of the study were that adjacent stand pairs with a total of 25 ha or more could not be regenerated together during the green-up period (3 years), and the adjacent stand pairs totaling 6 ha or less had to be regenerated in the same year. The model was solved for 11 different scenarios using Lingo 18. In scenario 3, which provided the best results, when the area and volume deviations are evaluated together, the total deviation from the annual regeneration area target was 1.64 ha, in other words, only 0.20% of the periodic regeneration area. The total deviation from the annual final yield harvest volume target was only 303 m3 (0.19% of the periodic final yield harvest volume). The method applied in the study can be used in the preparation of the final yield harvest plans and detailed silviculture plans of red pine forests.

Kaynakça

  • Aldea, J., Martínez-Peña, F., Romero, C. & Diaz-Balteiro, L. (2014). Participatory goal programming in forest management: An application integrating several ecosystem services. Forests, 5(12), 3352-3371.
  • Alp, S. (2008). Doğrusal Hedef Programlama Yönteminin Otobüsle Kent İçi Toplu Taşıma Sisteminde Kullanılması, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, Yıl:7 Sayı:13, 73-91.
  • Augustynczik, A.L.D., Arce, J.E. & da Silva, A.C.L. (2016). Aggregating forest harvesting activities in forest plantations through integer linear programming and goal programming. Journal of Forest Economics, 24, 72-81.
  • Bagdon, B.A., Huang, C.-H. & Dewhurst, S. (2016). Managing for ecosystem services in northern Arizona ponderosa pine forests using a novel simulation-to-optimization methodology. Ecological Modelling, 324, 11-27.
  • Bertomeu, M. & Romero, C. (2001). Managing forest biodiversity: a zero-one goal programming approach. Agricultural Systems, 68, 197-213.
  • Bertomeu, M. & Romero, C. (2002). Forest management optimization models and habitat diversity: a goal programming approach. Journal of the Operational Research Society, 53, 1175-1184.
  • Bell, E.F. (1975). Problems with goal programming on a national forest planning unit. Systems Analysis and Forest Resource Management, 119-126, Athens, Georgia.
  • Charnes, A. & Cooper, W.W. (1961). Management models and industrial applications of linear programming: Vol 1. New York: John Wiley & Sons.
  • Chen, Y.-T. & Chang, C.-T. (2014). Multi-coefficient goal programming in thinning schedules to increase carbon sequestration and improve forest structure. Annals of Forest Science, 71(8), 907-915.
  • Chen, Y.-T., Zheng, C. & Chang, C.-T. (2011). 3-level MCGP: An efficient algorithm for MCGP in solving multi-forest management problems. Scandinavian Journal of Forest Research, 26(5), 457-465.
  • Cyr, G., Raulier, F., Fortin, D. & Pothier, D. (2017). Using operating area size and adjacency constraints to mitigate the effects of harvesting activities on boreal caribou habitat. Landscape Ecology, 32(2), 377-395.
  • Dahlin, B. & Sallnäs, O. (1993). Harvest scheduling under adjacency constraints-a case study from the Swedish sub-alpine region. Scandinavian Journal of Forest Research, 8, 281-290.
  • De Kluyver, C.A. (1979). An exploration of various goal programming formulations - with application to advertising media scheduling. Journal of the Operational Research Society, 30(2), 167-171.
  • Demirci, M. (2018). Orman Amenajman Planlamasında Karışık Tamsayılı Amaç Programlamanın Kullanılması: Akören Plan Ünitesi Örneği. Doktora Tezi, İstanbul Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • Demirci, M. & Bettinger, P. (2015). Using mixed integer multi-objective goal programming for stand tending block designation: A case study from Turkey. Forest Policy and Economics, 55, 28-36.
  • Demirci, M., Yeşil, A. & Bettinger, P. (2020). Using mixed integer goal programming in final yield harvest planning: A case study from the Mediterranean region of Turkey. Forests, 11(7), 744.
  • Diaz-Balteiro, L. & Romero, C. (2003). Forest management optimization models when carbon captured is considered: a goal programming approach. Forest Ecology and Management, 174, 447-457.
  • Eraslan, İ. (1982). Orman Amenajmanı. İstanbul: İ.Ü. Orman Fakültesi.
  • Etemad, S.S., Limaei, S.M., Olsson, L. & Yousefpour, R. (2019). Forest management decision-making using goal programming and fuzzy analytic hierarchy process approaches (case study: Hyrcanian forests of Iran). Journal of Forest Science, 65, 368-379.
  • FAO (2020). Global Forest Resources Assessment 2020 – Main report. Roma: FAO.
  • Field, D.B. (1973). Goal programming for forest management. Forest Science, 19(2), 125-135.
  • Gómez, T., Hernández, M., Molina, J., León, M.A., Aldana, E. & Caballero, R. (2011). A multi objective model for forest planning with adjacency constraints. Annals of Operations Research, 190(1), 75-92.
  • Hossain, S.M.Y. & Robak, E.W. (2010). A forest management process to incorporate multiple objectives: A framework for systematic public input. Forests, 1(3), 99-113.
  • Jones, D.F. (1995). The Design and Development of an Intelligent Goal Programming System. PhD Dissertation. University of Portsmouth, Portsmouth.
  • Liu, W.-Y., Lin, C.-C. & Su, K.-H. (2017). Modelling the spatial forest-thinning planning problem considering carbon sequestration and emissions. Forest Policy and Economics, 78, 51-66.
  • Maroto, C., Segura, M., Ginestar, C., Uriol, J. & Segura, B. (2013). Sustainable forest management in a Mediterranean region: Social preferences. Forest Systems, 22(3), 546-458.
  • Marinescu, M.V. & Maness, T.C. (2010). A hierarchical timber allocation model to analyze sustainable forest management decisions. Mathematical and Computational Forestry & Natural-Resource Sciences, 2(2), 117-134.
  • Masud, A.S. & Hwang, C.L. (1981). Interactive sequential goal programming. Journal of the Operational Research Society, 32, 391-400.
  • Mısır, M. (2001). Çok Amaçlı Orman Amenajman Planlarının Coğrafi Bilgi Sistemlerine Dayalı Olarak amaç Programlama Yöntemiyle Düzenlenmesi (Ormanüstü Planlama Birimi Örneği). Doktora Tezi. KTÜ Fen Bilimleri Enstitüsü, Trabzon.
  • Mısır, N. & Mısır, M. (2007). Developing a multi-objective forest planning process with goal programming: a case study. Pakistan Journal of Biological Sciences, 10, 514-522.
  • OGM (2008). Orman Amenajman Yönetmeliği (Sayı: 26778). Ankara: Orman Genel Müdürlüğü.
  • OGM (2013). Fethiye Orman İşletme Şefliği Fonksiyonel Orman Amenajman Planı. Ankara: Orman Genel Müdürlüğü.
  • OGM (2014). Silvikültürel Uygulamaların Teknik Esasları (Tebliğ No: 298). Ankara: Orman Genel Müdürlüğü, Silvikültür Dairesi Başkanlığı.
  • OGM (2015). Türkiye Orman Varlığı 2015. Ankara: Orman Genel Müdürlüğü.
  • OGM (2017). Ekosistem Tabanlı Fonksiyonel Orman Amenajman Planlarının Düzenlenmesine Ait Usul ve Esaslar (Tebliğ No: 299). Ankara: Orman Genel Müdürlüğü, Orman İdaresi ve Planlama Dairesi Başkanlığı.
  • O’Hara, A.J., Faaland, B.H. & Bare, B.B. (1989). Spatially constrained timber harvest scheduling. Canadian Journal of Forest Research, 19(6), 715-724.
  • Öhman, K. (2001). Forest planning with consideration to spatial relationships. Thesis Dissertation. Swedish University of Agricultural Sciences, Uppsala.
  • Özkan, M. (2014). Bulanık Hedef Programlama ve Bir İşletme Üzerinde Uygulama. Doktora Tezi. Sivas Cumhuriyet Üniversitesi, Sosyal Bilimler Enstitüsü, Sivas.
  • Porterfield, R.L. (1973). Predicted and potential gains from tree improvement programs-a goal programming analysis of program efficiency. PhD Dissertation. Yale University, New Haven, Connecticut.
  • Tamiz, M., Jones, D. & Romero, C. (1998). Goal programming for decision making: an overview of the current state-of-the-art. European Journal of Operational Research, 111(3), 569-581.
  • Tarp, P. & Helles, F. (1997). Spatial optimization by simulated annealing and linear programming. Scandinavian Journal of Forest Research, 12, 390-402.
  • Qin, H., Dong, L. & Huang, Y. (2017). Evaluating the Effects of Carbon Prices on Trade-Offs between Carbon and Timber Management Objectives in Forest Spatial Harvest Scheduling Problems: A Case Study from Northeast China. Forests, 8(2), 43.
  • Romero, C. (1991). Handbook of Critical Issues in Goal Programming. Oxford: Pergamon Press.
  • Romesburg, H.C. (1974). Scheduling models for wilderness recreation. Journal of Environmental Management, 2, 159-177.
  • Rustagi, K.P. 1973. Forest management planning for timber production: a goal programming approach. PhD Dissertation. Yale University, New Haven, Connecticut.
  • Schuler, A.T. & Meadows, J.C. (1975). Planning resource use on natural forests to achieve multiple objectives. Journal of Environmental Management, 3, 351-366.
  • Silva, M., Weintraub, A., Romero, C. & De la Maza, C. (2010). Forest harvesting and environmental protection based on the goal programming approach. Forest Science, 56(5), 460-472.
  • Weintraub, A., Barahona, F. & Epstein, R. (1994). A column generation algorithm for solving general forest planning problems with adjacency constraints. Forest Science, 40(1), 142-161.
  • Wildhelm, W.B. (1981). Extensions of goal programming models. Omega, 9, 212-214.
  • Zengin, H., Asan, Ü., Destan, S., Ünal, M.E., Yeşil, A., Bettinger, P. & Değermenci, A.S. (2015). Modeling harvest scheduling in multifunctional planning of forests for long term water yield optimization. Natural Resource Modeling, 28(1), 59-85.
Toplam 50 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Orman Endüstri Mühendisliği
Bölüm Haziran Sayısı 2021
Yazarlar

Mehmet Demirci 0000-0003-0456-7330

Yayımlanma Tarihi 30 Haziran 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 17 Sayı: 1

Kaynak Göster

APA Demirci, M. (2021). Son Hâsılat Kesim Planlarının Amaç Programlama Kullanılarak Hazırlanması. Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi, 17(1), 116-141.

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