Abstract
Yeşil tedarik zinciri uygulamalarına geçişin arkasında yükselen çevresel ve ekonomik endişeler bulunmaktadır. Düzenleyici kurumlar, karbon emisyonları ve gürültü kirliliği gibi unsurlara odaklanarak, taşımacılığın çevresel etkilerini hafifletmeyi amaçlamaktadırlar. Çalışmamız, ideal anadağıtım üssü konumlarını belirleyerek tek atamalı anadağıtım üssü kapsama akış problemiyle başa çıkan yenilikçi bir optimizasyon modeli sunmaktadır. Standart anadağıtım üssü problemlerinden farklı olarak, modelimiz anadağıtım üssü kapasite sınırlarını anlamaktadır. Bir kapasite maliyet fonksiyonunu sisteme entegre ederek, genel ağ emisyonlarını yönetirken kapasiteyi de yönlendirmektedir. Ayrıca, anadağıtım üssü kapasitelerinin kısıtlamaları gibi çeşitli parametrelerin, en iyi çözümleri nasıl dönüştürebileceğini de dikkate almaktadır. Geleneksel modelleri geride bırakmak için, endüstri ve geleneksel kaynaklardan elde edilen yeni bir veri seti oluşturulmuştur. Ardından, önerilen model kapasite düşüncelerini göz ardı eden modellerle karşılaştırılmıştır. Bu bütüncül anlayış, önerilen modellerin daha iyi performans ve yeşil sonuçlar sağladığını göstermektedir. Özünde, çevresel korumayı lojistik optimizasyon ile birleştirerek, tedarik zinciri yönetiminde yeni başlayan çağa katkıda bulunulmuştur. Diğer modellerin göz ardı ettiği karbon salınım maliyeti düşüncesini dikkate alarak daha verimli ve çevre bilincine sahip bir lojistik ağı oluşturulmuştur.
Keywords
References
- Alumur Alev, S., & Yetis Kara, B. (2009). A Hub Covering Network Design Problem for Cargo Applications in Turkey. The Journal of the Operational Research Society, 60(10), 1349-1359.
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- Campbell, J. F. (1994). Integer Programming Formulations of Discrete Hub Location Problems. European Journal of Operational Research, 72(2), 387-405.
- Correia, I., Nickel, S., & Saldanha-da-Gama, F. (2014). Multi-Product Capacitated Single-Allocation Hub Location Problems: Formulations and Inequalities. Networks and Spatial Economics, 14(1), 1-25.
- Dukkanci, O., Peker, M., & Kara, B. Y. (2019). Green hub location problem. Transportation Research Part E: Logistics and Transportation Review, 125, 116-139.
- Karimia, H., Bashiri, M., & Nickel, S. (2016). Capacitated Single Allocation P-Hub Covering Problem in Multi-modal Network Using Tabu Search. International Journal of Engineering, 29(6), 797-808.
- Lowe, T. J., & Sim, T. (2013). The hub covering flow problem. The Journal of the Operational Research Society, 64(7), 973-981.
- Mohammadi, M., Torabi, S. A., & Tavakkoli-Moghaddam, R. (2014). Sustainable hub location under mixed uncertainty. Transportation Research Part E: Logistics and Transportation Review, 62, 89-115.
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- Parsa, M., Nookabadi, A. S., Flapper, S. D., & Atan, Z. (2019). Green hub-and-spoke network design for aviation industry. Journal of Cleaner Production, 229, 1377-1396.
- Sener, N. (2020). New Optimization Models for the Hub Covering Location Problem. Graduate School of Science and Engineering, Galatasaray University.
- Sener, N., & Feyzioğlu, O. (2021). Capacitated Multiple Allocation Hub Covering Flow Problem. MANAS Journal of Engineering, 9, 72-84.
- Smart Freight Centre. (2021). Global Logistics Emissions Council Framework for Logistics Emissions. Tan, P. Z., & Yetis Kara, B. (2007). A Hub Covering Model for Cargo Delivery Systems. Networks, 49(1), 28-39.
- The World Bank. (2021). Carbon Pricing Dashboard. Geliş tarihi gönderen https://carbonpricingdashboard.worldbank.org/map_data
- Wagner, B. (2008). Model Formulations for Hub Covering Problems. The Journal of the Operational Research Society, 59(7), 932-938.
- Yetis Kara, B. (2017). Turkish Hub Data Set.
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Abstract
Driving the shift to green supply chain practices are rising environmental and economic concerns. Regulatory bodies aim to mitigate transportation's environmental repercussions, focusing on aspects such as carbon emissions and noise pollution. Our study introduces a revolutionary optimization model that handles a single allocation green hub covering flow problem by determining ideal hub locations. Distinct from standard hub issues, our model comprehends hub capacity limits. With a capacity cost function integrated into the system, it simultaneously manages overall network emissions while maneuvering the capacity. Additionally, this takes into account how various parameters, like the constraints of hub capacities, can transform optimal solutions. To outperform traditional models, we amalgamate a new dataset drawn from industry and conventional resources. Subsequently, we juxtapose our model with those foregoing capacity considerations. This holistic understanding displays how our model fosters enhanced performance and green outcomes. In essence, we are merging environmental preservation with logistics optimization, ushering a new era in supply chain management, taking into account the carbon emission cost considerations that most other models ignore, leading to a more efficient and environmentally conscious logistic network.
Keywords
References
- Alumur Alev, S., & Yetis Kara, B. (2009). A Hub Covering Network Design Problem for Cargo Applications in Turkey. The Journal of the Operational Research Society, 60(10), 1349-1359.
- Beasley, J. E. (1990). OR-Library.
- Calik, H., Alumur Alev, S., Yetis Kara, B., & Karasan, O. E. (2009). A Tabu-Search based Heuristic for the Hub Covering Problem over Incomplete Hub Networks . Computers & Operations Research , 36(12), 3088-3096.
- Campbell, J. F. (1994). Integer Programming Formulations of Discrete Hub Location Problems. European Journal of Operational Research, 72(2), 387-405.
- Correia, I., Nickel, S., & Saldanha-da-Gama, F. (2014). Multi-Product Capacitated Single-Allocation Hub Location Problems: Formulations and Inequalities. Networks and Spatial Economics, 14(1), 1-25.
- Dukkanci, O., Peker, M., & Kara, B. Y. (2019). Green hub location problem. Transportation Research Part E: Logistics and Transportation Review, 125, 116-139.
- Karimia, H., Bashiri, M., & Nickel, S. (2016). Capacitated Single Allocation P-Hub Covering Problem in Multi-modal Network Using Tabu Search. International Journal of Engineering, 29(6), 797-808.
- Lowe, T. J., & Sim, T. (2013). The hub covering flow problem. The Journal of the Operational Research Society, 64(7), 973-981.
- Mohammadi, M., Torabi, S. A., & Tavakkoli-Moghaddam, R. (2014). Sustainable hub location under mixed uncertainty. Transportation Research Part E: Logistics and Transportation Review, 62, 89-115.
- Niknamfar, A. H., & Niaki, S. T. A. (2016). Fair profit contract for a carrier collaboration framework in a green hub network under soft time-windows: Dual lexicographic max–min approach. Transportation Research Part E: Logistics and Transportation Review, 91, 129-151.
- Parsa, M., Nookabadi, A. S., Flapper, S. D., & Atan, Z. (2019). Green hub-and-spoke network design for aviation industry. Journal of Cleaner Production, 229, 1377-1396.
- Sener, N. (2020). New Optimization Models for the Hub Covering Location Problem. Graduate School of Science and Engineering, Galatasaray University.
- Sener, N., & Feyzioğlu, O. (2021). Capacitated Multiple Allocation Hub Covering Flow Problem. MANAS Journal of Engineering, 9, 72-84.
- Smart Freight Centre. (2021). Global Logistics Emissions Council Framework for Logistics Emissions. Tan, P. Z., & Yetis Kara, B. (2007). A Hub Covering Model for Cargo Delivery Systems. Networks, 49(1), 28-39.
- The World Bank. (2021). Carbon Pricing Dashboard. Geliş tarihi gönderen https://carbonpricingdashboard.worldbank.org/map_data
- Wagner, B. (2008). Model Formulations for Hub Covering Problems. The Journal of the Operational Research Society, 59(7), 932-938.
- Yetis Kara, B. (2017). Turkish Hub Data Set.
- Yetis Kara, B., & Tansel, B. (2003). The Single-Assignment Hub Covering Problem: Models and Linearizations. The Journal of the Operational Research Society, 54(1), 59-64.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Manufacturing and Service Systems, Optimization in Manufacturing |
| Journal Section | Industrial Engineering |
| Authors | |
| Publication Date | December 3, 2023 |
| Submission Date | August 7, 2023 |
| Published in Issue | Year 2023 |