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Bowen Zhang

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First Name:Bowen
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Last Name:Zhang
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RePEc Short-ID:pzh800
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Articles

  1. Zhang, B. & Qiao, H. & Chen, Z.M. & Chen, B., 2016. "Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input–output analysis," Applied Energy, Elsevier, vol. 184(C), pages 1093-1105.
  2. Paredes, P. & Wei, Z. & Liu, Y. & Xu, D. & Xin, Y. & Zhang, B. & Pereira, L.S., 2015. "Performance assessment of the FAO AquaCrop model for soil water, soil evaporation, biomass and yield of soybeans in North China Plain," Agricultural Water Management, Elsevier, vol. 152(C), pages 57-71.
  3. B. Zhang & J.S. Lv & J.X. Zuo, 2014. "Theoretical and experimental study on solar ejector cooling system using R236fa," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 9(4), pages 245-249.
  4. B Zhang & C T Ng & T C E Cheng, 2014. "Multi-period empty container repositioning with stochastic demand and lost sales," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(2), pages 302-319, February.
  5. B Zhang & J Wang & L Meng & C Zhu & R Nie, 2014. "Estimating returns to scale of Chinese airport airside activities using the CCR-0-objective RTS method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(5), pages 755-762, May.
  6. B Zhang & P Murali & M M Dessouky & D Belson, 2009. "A mixed integer programming approach for allocating operating room capacity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(5), pages 663-673, May.
  7. W. Xu & B. Zhang & Z. Wang & S. Chu & W. Li & Z. Wu & R. Yu & X. Zhang, 2008. "Scaling law of anomalous Hall effect in Fe/Cu bilayers," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 65(2), pages 233-237, September.
  8. Z S Hua & B Zhang & J Yang & D S Tan, 2007. "A new approach of forecasting intermittent demand for spare parts inventories in the process industries," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(1), pages 52-61, January.
  9. Zhang, B. & Stein, M., 1993. "Kernel Approximations for Universal Kriging Predictors," Journal of Multivariate Analysis, Elsevier, vol. 44(2), pages 286-313, February.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Zhang, B. & Qiao, H. & Chen, Z.M. & Chen, B., 2016. "Growth in embodied energy transfers via China’s domestic trade: Evidence from multi-regional input–output analysis," Applied Energy, Elsevier, vol. 184(C), pages 1093-1105.

    Cited by:

    1. Yue Fu & Long Xue & Yixin Yan & Yao Pan & Xiaofang Wu & Ying Shao, 2021. "Energy Network Embodied in Trade along the Belt and Road: Spatiotemporal Evolution and Influencing Factors," Sustainability, MDPI, vol. 13(19), pages 1-29, September.
    2. Rocco, Matteo V. & Forcada Ferrer, Rafael J. & Colombo, Emanuela, 2018. "Understanding the energy metabolism of World economies through the joint use of Production- and Consumption-based energy accountings," Applied Energy, Elsevier, vol. 211(C), pages 590-603.
    3. José A. Camacho & Lucas Silva Almeida & Mercedes Rodríguez & Jesús Molina, 2022. "Domestic versus foreign energy use: an analysis for four European countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 4602-4622, April.
    4. Li, Yilin & Chen, Bin & Li, Chaohui & Li, Zhi & Chen, Guoqian, 2020. "Energy perspective of Sino-US trade imbalance in global supply chains," Energy Economics, Elsevier, vol. 92(C).
    5. Zhu, Bangzhu & Su, Bin & Li, Yingzhu & Ng, Tsan Sheng, 2020. "Embodied energy and intensity in China’s (normal and processing) exports and their driving forces, 2005-2015," Energy Economics, Elsevier, vol. 91(C).
    6. Sun, Yong & Liu, Baoyin & Sun, Zhongrui & Yang, Ruijia, 2023. "Inter-regional cooperation in the transfers of energy-intensive industry: An evolutionary game approach," Energy, Elsevier, vol. 282(C).
    7. Xiaopeng Wang & Xiang Chen & Yiman Cheng & Luyao Zhou & Yi Li & Yongliang Yang, 2020. "Factorial Decomposition of the Energy Footprint of the Shaoxing Textile Industry," Energies, MDPI, vol. 13(7), pages 1-13, April.
    8. Wang, Zhaohua & Zhang, Hongzhi & Li, Hao & Wang, Song & Wang, Zhenpo, 2023. "Identifying the key factors to China's unsustainable external circulation through the accounting of the flow of embodied energy and virtual water," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    9. Junbo Wang & Liu Chen & Lu Chen & Xiaohui Zhao & Minxi Wang & Yiyi Ju & Li Xin, 2019. "City-Level Features of Energy Footprints and Carbon Dioxide Emissions in Sichuan Province of China," Energies, MDPI, vol. 12(10), pages 1-14, May.
    10. Min Huang & Yimin Chen & Yuanying Zhang, 2018. "Assessing Carbon Footprint and Inter-Regional Carbon Transfer in China Based on a Multi-Regional Input-Output Model," Sustainability, MDPI, vol. 10(12), pages 1-13, December.
    11. Hao, Yan & Zhang, Menghui & Zhang, Yan & Fu, Chenling & Lu, Zhongming, 2018. "Multi-scale analysis of the energy metabolic processes in the Beijing–Tianjin–Hebei (Jing-Jin-Ji) urban agglomeration," Ecological Modelling, Elsevier, vol. 369(C), pages 66-76.
    12. Zheng, Hongmei & Li, Aimin & Meng, Fanxin & Liu, Gengyuan, 2020. "Energy flows embodied in China's interregional trade: Case study of Hebei Province," Ecological Modelling, Elsevier, vol. 428(C).
    13. Mi, Zhifu & Zhang, Yunkun & Guan, Dabo & Shan, Yuli & Liu, Zhu & Cong, Ronggang & Yuan, Xiao-Chen & Wei, Yi-Ming, 2016. "Consumption-based emission accounting for Chinese cities," Applied Energy, Elsevier, vol. 184(C), pages 1073-1081.
    14. Kan, S.Y. & Chen, B. & Wu, X.F. & Chen, Z.M. & Chen, G.Q., 2019. "Natural gas overview for world economy: From primary supply to final demand via global supply chains," Energy Policy, Elsevier, vol. 124(C), pages 215-225.
    15. Wang, Qiang & Song, Xiaoxin, 2021. "How UK farewell to coal – Insight from multi-regional input-output and logarithmic mean divisia index analysis," Energy, Elsevier, vol. 229(C).
    16. Ji, Xi & Han, Mengyao & Ulgiati, Sergio, 2020. "Optimal allocation of direct and embodied arable land associated to urban economy: Understanding the options deriving from economic globalization," Land Use Policy, Elsevier, vol. 91(C).
    17. Jinghui Liu & Tingting Geng & Xingwei Wang & Guojin Qin, 2020. "Determinants of Oil Footprints Embodied in Sino-US Trade: A Perspective from the Globalizing World," Energies, MDPI, vol. 13(15), pages 1-26, July.
    18. Shao, Ling & Li, Yuan & Feng, Kuishuang & Meng, Jing & Shan, Yuli & Guan, Dabo, 2018. "Carbon emission imbalances and the structural paths of Chinese regions," Applied Energy, Elsevier, vol. 215(C), pages 396-404.
    19. Mohammad Delnavaz & Melika Norouzianpour & Ali Delnavaz & Shamim Amiri, 2024. "A comparative study on the environmental impact of cast in situ concrete and industrialized building systems: a life cycle assessment approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 26475-26493, October.
    20. Soares, N. & Martins, A.G. & Carvalho, A.L. & Caldeira, C. & Du, C. & Castanheira, É. & Rodrigues, E. & Oliveira, G. & Pereira, G.I. & Bastos, J. & Ferreira, J.P. & Ribeiro, L.A. & Figueiredo, N.C. & , 2018. "The challenging paradigm of interrelated energy systems towards a more sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 171-193.
    21. Jinghan Chen & Wen Zhou & Hongtao Yang, 2019. "Is Embodied Energy a Better Starting Point for Solving Energy Security Issues?—Based on an Overview of Embodied Energy-Related Research," Sustainability, MDPI, vol. 11(16), pages 1-22, August.
    22. Zhang, Zengkai & Zhu, Kunfu, 2017. "Border carbon adjustments for exports of the United States and the European Union: Taking border-crossing frequency into account," Applied Energy, Elsevier, vol. 201(C), pages 188-199.
    23. Hanspeter Wieland & Stefan Giljum & Nina Eisenmenger & Dominik Wiedenhofer & Martin Bruckner & Anke Schaffartzik & Anne Owen, 2020. "Supply versus use designs of environmental extensions in input–output analysis: Conceptual and empirical implications for the case of energy," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 548-563, June.
    24. Wu, X.F. & Chen, G.Q., 2017. "Energy use by Chinese economy: A systems cross-scale input-output analysis," Energy Policy, Elsevier, vol. 108(C), pages 81-90.
    25. Li, Junjie & Yan, Yulong & Wang, Yirong & Zhang, Yifu & Shao, Lianwei & Li, Menggang, 2024. "Spatial-successive transfer of virtual scarcity water along China's coal-based electric chain," Energy, Elsevier, vol. 288(C).
    26. Yawen Han & Shigemi Kagawa & Fumiya Nagashima & Keisuke Nansai, 2019. "Sources of China’s Fossil Energy-Use Change," Energies, MDPI, vol. 12(4), pages 1-16, February.
    27. Sun, Xudong & Li, Jiashuo & Qiao, Han & Zhang, Bo, 2017. "Energy implications of China's regional development: New insights from multi-regional input-output analysis," Applied Energy, Elsevier, vol. 196(C), pages 118-131.
    28. Rui Huang & Klaus Hubacek & Kuishuang Feng & Xiaojie Li & Chao Zhang, 2018. "Re-Examining Embodied SO 2 and CO 2 Emissions in China," Sustainability, MDPI, vol. 10(5), pages 1-17, May.
    29. Jing Li & Hong Fang & Siran Fang & Zhiming Zhang & Pengyuan Zhang, 2021. "Embodied Energy Use in China’s Transportation Sector: A Multi-Regional Input–Output Analysis," IJERPH, MDPI, vol. 18(15), pages 1-18, July.
    30. Zhang, Shuai & Yang, Dewei & Ji, Yijia & Meng, Haishan & Zhou, Tian & Zhang, Junmei & Yang, Hang, 2024. "Spatio-temporal patterns and cascading risks of embodied energy flows in China," Energy, Elsevier, vol. 298(C).
    31. Bai, Hongtao & Feng, Xiangyu & Hou, Huimin & He, Gang & Dong, Yan & Xu, He, 2018. "Mapping inter-industrial CO2 flows within China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 400-408.
    32. Gao, Cuixia & Su, Bin & Sun, Mei & Zhang, Xiaoling & Zhang, Zhonghua, 2018. "Interprovincial transfer of embodied primary energy in China: A complex network approach," Applied Energy, Elsevier, vol. 215(C), pages 792-807.
    33. Liu, Bingquan & Shi, Junxue & Wang, Hui & Su, Xuelin & Zhou, Peng, 2019. "Driving factors of carbon emissions in China: A joint decomposition approach based on meta-frontier," Applied Energy, Elsevier, vol. 256(C).
    34. Liao, Maolin & Zhang, Ze & Jia, Jin & Xiong, Jiao & Han, Mengyao, 2022. "Mapping China's photovoltaic power geographies: Spatial-temporal evolution, provincial competition and low-carbon transition," Renewable Energy, Elsevier, vol. 191(C), pages 251-260.
    35. Zhuang, Mufan & Gao, Ziyan & Geng, Yong & Xiao, Shijiang, 2022. "Spatial distribution pattern of embodied natural resources use in China and its relationship with socioeconomic development: From an exergetic perspective," Resources Policy, Elsevier, vol. 79(C).
    36. Long, Yin & Yoshida, Yoshikuni, 2018. "Quantifying city-scale emission responsibility based on input-output analysis – Insight from Tokyo, Japan," Applied Energy, Elsevier, vol. 218(C), pages 349-360.
    37. Wang, Heming & Wang, Guoqiang & Qi, Jianchuan & Schandl, Heinz & Li, Yumeng & Feng, Cuiyang & Yang, Xuechun & Wang, Yao & Wang, Xinzhe & Liang, Sai, 2020. "Scarcity-weighted fossil fuel footprint of China at the provincial level," Applied Energy, Elsevier, vol. 258(C).
    38. Wang, Zhaohua & Li, Yiming & Cai, Hailin & Yang, Yuantao & Wang, Bo, 2019. "Regional difference and drivers in China's carbon emissions embodied in internal trade," Energy Economics, Elsevier, vol. 83(C), pages 217-228.
    39. Zhang, Pengfei & Cai, Wenqiu & Yao, Mingtao & Wang, Zhiyou & Yang, Luzhen & Wei, Wendong, 2020. "Urban carbon emissions associated with electricity consumption in Beijing and the driving factors," Applied Energy, Elsevier, vol. 275(C).
    40. Mengyao Han & Shuchang Li, 2021. "Transfer Patterns and Drivers of Embodied Agricultural Land within China: Based on Multi-Regional Decomposition Analysis," Land, MDPI, vol. 10(2), pages 1-16, February.
    41. Song, Xiaoxin & Li, Rongrong, 2023. "Tracing and excavating critical paths and sectors for embodied energy consumption in global supply chains: A case study of China," Energy, Elsevier, vol. 284(C).
    42. Peng Chen & Hanwen Wang & Mingxing Guo & Jianjun Wang & Sinan Cai & Min Li & Kaining Sun & Yukun Wang, 2022. "Decomposition Analysis of Regional Embodied Carbon Flow and Driving Factors—Taking Shanghai as an Example," Sustainability, MDPI, vol. 14(17), pages 1-16, September.
    43. Duan, Cuncun & Chen, Bin & Feng, Kuishuang & Liu, Zhu & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2018. "Interregional carbon flows of China," Applied Energy, Elsevier, vol. 227(C), pages 342-352.
    44. Xin Li & Xiandan Cui & Minxi Wang, 2017. "Analysis of China’s Carbon Emissions Base on Carbon Flow in Four Main Sectors: 2000–2013," Sustainability, MDPI, vol. 9(4), pages 1-13, April.
    45. Tian, Xu & Chen, Bin & Geng, Yong & Zhong, Shaozhuo & Gao, Cuixia & Wilson, Jeffrey & Cui, Xiaowei & Dou, Yi, 2019. "Energy footprint pathways of China," Energy, Elsevier, vol. 180(C), pages 330-340.
    46. Mi, Zhifu & Zheng, Jiali & Meng, Jing & Zheng, Heran & Li, Xian & Coffman, D'Maris & Woltjer, Johan & Wang, Shouyang & Guan, Dabo, 2019. "Carbon emissions of cities from a consumption-based perspective," Applied Energy, Elsevier, vol. 235(C), pages 509-518.
    47. Zhang, Bo & Qu, Xue & Meng, Jing & Sun, Xudong, 2017. "Identifying primary energy requirements in structural path analysis: A case study of China 2012," Applied Energy, Elsevier, vol. 191(C), pages 425-435.
    48. Wang, Zhenyu & Meng, Jing & Zheng, Heran & Shao, Shuai & Wang, Daoping & Mi, Zhifu & Guan, Dabo, 2018. "Temporal change in India’s imbalance of carbon emissions embodied in international trade," Applied Energy, Elsevier, vol. 231(C), pages 914-925.
    49. Zhang, Zengkai & Lin, Jintai, 2018. "From production-based to consumption-based regional carbon inventories: Insight from spatial production fragmentation," Applied Energy, Elsevier, vol. 211(C), pages 549-567.
    50. de Carvalho, Ariovaldo Lopes & Antunes, Carlos Henggeler & Freire, Fausto, 2016. "Economic-energy-environment analysis of prospective sugarcane bioethanol production in Brazil," Applied Energy, Elsevier, vol. 181(C), pages 514-526.
    51. Shi, Jianglan & Li, Chao & Li, Huajiao, 2022. "Energy consumption in China's ICT sectors: From the embodied energy perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    52. Kucukvar, Murat & Cansev, Bunyamin & Egilmez, Gokhan & Onat, Nuri C. & Samadi, Hamidreza, 2016. "Energy-climate-manufacturing nexus: New insights from the regional and global supply chains of manufacturing industries," Applied Energy, Elsevier, vol. 184(C), pages 889-904.
    53. Wu, X.D. & Guo, J.L. & Ji, Xi & Chen, G.Q., 2019. "Energy use in world economy from household-consumption-based perspective," Energy Policy, Elsevier, vol. 127(C), pages 287-298.
    54. Han, Mengyao & Xiong, Jiao & Wang, Siyuan & Yang, Yu, 2020. "Chinese photovoltaic poverty alleviation: Geographic distribution, economic benefits and emission mitigation," Energy Policy, Elsevier, vol. 144(C).

  2. Paredes, P. & Wei, Z. & Liu, Y. & Xu, D. & Xin, Y. & Zhang, B. & Pereira, L.S., 2015. "Performance assessment of the FAO AquaCrop model for soil water, soil evaporation, biomass and yield of soybeans in North China Plain," Agricultural Water Management, Elsevier, vol. 152(C), pages 57-71.

    Cited by:

    1. Han, Congying & Zhang, Baozhong & Chen, He & Liu, Yu & Wei, Zheng, 2020. "Novel approach of upscaling the FAO AquaCrop model into regional scale by using distributed crop parameters derived from remote sensing data," Agricultural Water Management, Elsevier, vol. 240(C).
    2. Ran, Hui & Kang, Shaozhong & Li, Fusheng & Tong, Ling & Ding, Risheng & Du, Taisheng & Li, Sien & Zhang, Xiaotao, 2017. "Performance of AquaCrop and SIMDualKc models in evapotranspiration partitioning on full and deficit irrigated maize for seed production under plastic film-mulch in an arid region of China," Agricultural Systems, Elsevier, vol. 151(C), pages 20-32.
    3. Li, Jiang & Song, Jian & Li, Mo & Shang, Songhao & Mao, Xiaomin & Yang, Jian & Adeloye, Adebayo J., 2018. "Optimization of irrigation scheduling for spring wheat based on simulation-optimization model under uncertainty," Agricultural Water Management, Elsevier, vol. 208(C), pages 245-260.
    4. Er-Raki, S. & Bouras, E. & Rodriguez, J.C. & Watts, C.J. & Lizarraga-Celaya, C. & Chehbouni, A., 2021. "Parameterization of the AquaCrop model for simulating table grapes growth and water productivity in an arid region of Mexico," Agricultural Water Management, Elsevier, vol. 245(C).
    5. Sandhu, Rupinder & Irmak, Suat, 2019. "Assessment of AquaCrop model in simulating maize canopy cover, soil-water, evapotranspiration, yield, and water productivity for different planting dates and densities under irrigated and rainfed cond," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    6. Pereira, Luis S. & Paredes, Paula & Rodrigues, Gonçalo C. & Neves, Manuela, 2015. "Modeling malt barley water use and evapotranspiration partitioning in two contrasting rainfall years. Assessing AquaCrop and SIMDualKc models," Agricultural Water Management, Elsevier, vol. 159(C), pages 239-254.
    7. Adeboye, Omotayo B. & Schultz, Bart & Adekalu, Kenneth O. & Prasad, Krishna C., 2019. "Performance evaluation of AquaCrop in simulating soil water storage, yield, and water productivity of rainfed soybeans (Glycine max L. merr) in Ile-Ife, Nigeria," Agricultural Water Management, Elsevier, vol. 213(C), pages 1130-1146.
    8. Panagiotis Christias & Ioannis N. Daliakopoulos & Thrassyvoulos Manios & Mariana Mocanu, 2020. "Comparison of Three Computational Approaches for Tree Crop Irrigation Decision Support," Mathematics, MDPI, vol. 8(5), pages 1-26, May.
    9. Ćosić, Marija & Stričević, Ružica & Djurović, Nevenka & Moravčević, Djordje & Pavlović, Miloš & Todorović, Mladen, 2017. "Predicting biomass and yield of sweet pepper grown with and without plastic film mulching under different water supply and weather conditions," Agricultural Water Management, Elsevier, vol. 188(C), pages 91-100.
    10. Zhang, Ting & Zuo, Qiang & Ma, Ning & Shi, Jianchu & Fan, Yuchuan & Wu, Xun & Wang, Lichun & Xue, Xuzhang & Ben-Gal, Alon, 2023. "Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop," Agricultural Water Management, Elsevier, vol. 286(C).
    11. Alex Zizinga & Jackson Gilbert Majaliwa Mwanjalolo & Britta Tietjen & Bobe Bedadi & Ramon Amaro de Sales & Dennis Beesigamukama, 2022. "Simulating Maize Productivity under Selected Climate Smart Agriculture Practices Using AquaCrop Model in a Sub-humid Environment," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    12. Nunes, H.G.G.C. & Farias, V.D.S. & Sousa, D.P. & Costa, D.L.P. & Pinto, J.V.N. & Moura, V.B. & Teixeira, E.O. & Lima, M.J.A. & Ortega-Farias, S. & Souza, P.J.O.P., 2021. "Parameterization of the AquaCrop model for cowpea and assessing the impact of sowing dates normally used on yield," Agricultural Water Management, Elsevier, vol. 252(C).
    13. Xu, Junzeng & Bai, Wenhuan & Li, Yawei & Wang, Haiyu & Yang, Shihong & Wei, Zheng, 2019. "Modeling rice development and field water balance using AquaCrop model under drying-wetting cycle condition in eastern China," Agricultural Water Management, Elsevier, vol. 213(C), pages 289-297.
    14. Ahmad, Mirza Junaid & Iqbal, Muhammad Anjum & Choi, Kyung Sook, 2020. "Climate-driven constraints in sustaining future wheat yield and water productivity," Agricultural Water Management, Elsevier, vol. 231(C).
    15. Toumi, J. & Er-Raki, S. & Ezzahar, J. & Khabba, S. & Jarlan, L. & Chehbouni, A., 2016. "Performance assessment of AquaCrop model for estimating evapotranspiration, soil water content and grain yield of winter wheat in Tensift Al Haouz (Morocco): Application to irrigation management," Agricultural Water Management, Elsevier, vol. 163(C), pages 219-235.
    16. Sandhu, Rupinder & Irmak, Suat, 2019. "Performance of AquaCrop model in simulating maize growth, yield, and evapotranspiration under rainfed, limited and full irrigation," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    17. Feng, Dingrui & Li, Guangyong & Wang, Dan & Wulazibieke, Mierguli & Cai, Mingkun & Kang, Jing & Yuan, Zicheng & Xu, Houcheng, 2022. "Evaluation of AquaCrop model performance under mulched drip irrigation for maize in Northeast China," Agricultural Water Management, Elsevier, vol. 261(C).
    18. Nyathi, M.K. & van Halsema, G.E. & Annandale, J.G. & Struik, P.C., 2018. "Calibration and validation of the AquaCrop model for repeatedly harvested leafy vegetables grown under different irrigation regimes," Agricultural Water Management, Elsevier, vol. 208(C), pages 107-119.
    19. Marjan Aziz & Sultan Ahmad Rizvi & Muhammad Sultan & Muhammad Sultan Ali Bazmi & Redmond R. Shamshiri & Sobhy M. Ibrahim & Muhammad A. Imran, 2022. "Simulating Cotton Growth and Productivity Using AquaCrop Model under Deficit Irrigation in a Semi-Arid Climate," Agriculture, MDPI, vol. 12(2), pages 1-18, February.

  3. B. Zhang & J.S. Lv & J.X. Zuo, 2014. "Theoretical and experimental study on solar ejector cooling system using R236fa," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 9(4), pages 245-249.

    Cited by:

    1. Mosaffa, A.H. & Farshi, L. Garousi, 2018. "Thermodynamic and economic assessments of a novel CCHP cycle utilizing low-temperature heat sources for domestic applications," Renewable Energy, Elsevier, vol. 120(C), pages 134-150.

  4. B Zhang & C T Ng & T C E Cheng, 2014. "Multi-period empty container repositioning with stochastic demand and lost sales," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(2), pages 302-319, February.

    Cited by:

    1. Yang, Yu & Ridouane, Yassine & Boland, Natashia & Erera, Alan & Savelsbergh, Martin, 2022. "Substitution-based equipment balancing in service networks with multiple equipment types," European Journal of Operational Research, Elsevier, vol. 300(3), pages 966-978.
    2. Legros, Benjamin & Fransoo, Jan & Jouini, Oualid, 2024. "How to optimize container withholding decisions for reuse in the hinterland?," Other publications TiSEM 8c64b894-e9ee-415a-b396-1, Tilburg University, School of Economics and Management.
    3. Najafi, Mehdi & Zolfagharinia, Hossein, 2021. "Pricing and quality setting strategy in maritime transportation: Considering empty repositioning and demand uncertainty," International Journal of Production Economics, Elsevier, vol. 240(C).
    4. Dongping Song, 2021. "A Literature Review, Container Shipping Supply Chain: Planning Problems and Research Opportunities," Logistics, MDPI, vol. 5(2), pages 1-26, June.
    5. Lee, Chung-Yee & Song, Dong-Ping, 2017. "Ocean container transport in global supply chains: Overview and research opportunities," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 442-474.
    6. Zirui Liang & Ryuichi Shibasaki & Yuji Hoshino, 2021. "Do Foldable Containers Enhance Efficient Empty Container Repositioning under Demand Fluctuation?—Case of the Pacific Region," Sustainability, MDPI, vol. 13(9), pages 1-24, April.
    7. Wadhwa, Satpal Singh & Farahmand, Kambiz & Vachal, Kimberly, 2019. "A deterministic mathematical model to support future investment decisions for developing inland container terminals," Research in Transportation Economics, Elsevier, vol. 77(C).
    8. Amir Gharehgozli & Nima Zaerpour & Rene Koster, 2020. "Container terminal layout design: transition and future," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(4), pages 610-639, December.
    9. Ksciuk, Jana & Kuhlemann, Stefan & Tierney, Kevin & Koberstein, Achim, 2023. "Uncertainty in maritime ship routing and scheduling: A Literature review," European Journal of Operational Research, Elsevier, vol. 308(2), pages 499-524.
    10. Xie, Yangyang & Liang, Xiaoying & Ma, Lijun & Yan, Houmin, 2017. "Empty container management and coordination in intermodal transport," European Journal of Operational Research, Elsevier, vol. 257(1), pages 223-232.
    11. Legros, Benjamin & Fransoo, Jan & Jouini, Oualid, 2024. "How to optimize container withholding decisions for reuse in the hinterland?," European Journal of Operational Research, Elsevier, vol. 316(3), pages 930-941.
    12. Song, Zhuzhu & Tang, Wansheng & Zhao, Ruiqing, 2019. "Encroachment and canvassing strategy in a sea-cargo service chain with empty container repositioning," European Journal of Operational Research, Elsevier, vol. 276(1), pages 175-186.

  5. B Zhang & J Wang & L Meng & C Zhu & R Nie, 2014. "Estimating returns to scale of Chinese airport airside activities using the CCR-0-objective RTS method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(5), pages 755-762, May.

    Cited by:

    1. Andreas Dellnitz & Madjid Tavana & Rajiv Banker, 2023. "A novel median-based optimization model for eco-efficiency assessment in data envelopment analysis," Annals of Operations Research, Springer, vol. 322(2), pages 661-690, March.

  6. B Zhang & P Murali & M M Dessouky & D Belson, 2009. "A mixed integer programming approach for allocating operating room capacity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(5), pages 663-673, May.

    Cited by:

    1. Arne Schulz, 2023. "The balanced maximally diverse grouping problem with integer attribute values," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-27, July.
    2. Şeyda Gür & Tamer Eren & Hacı Mehmet Alakaş, 2019. "Surgical Operation Scheduling with Goal Programming and Constraint Programming: A Case Study," Mathematics, MDPI, vol. 7(3), pages 1-24, March.
    3. Mariana Oliveira & Filippo Visintin & Daniel Santos & Inês Marques, 2022. "Flexible master surgery scheduling: combining optimization and simulation in a rolling horizon approach," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 824-858, December.
    4. Zexian Zeng & Xiaolei Xie & Heidi Menaker & Susan G. Sanford-Ring & Jingshan Li, 2018. "Performance evaluation of operating room schedules in orthopedic surgery," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 198-223, June.
    5. Michael R. Miller & Robert J. Alexander & Vincent A. Arbige & Robert F. Dell & Steven R. Kremer & Brian P. McClune & Jane E. Oppenlander & Joshua P. Tomlin, 2017. "Optimal Allocation of Students to Naval Nuclear-Power Training Units," Interfaces, INFORMS, vol. 47(4), pages 320-335, August.
    6. Michael Samudra & Carla Van Riet & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2016. "Scheduling operating rooms: achievements, challenges and pitfalls," Journal of Scheduling, Springer, vol. 19(5), pages 493-525, October.
    7. Choi, Sangdo & Wilhelm, Wilbert E., 2014. "An approach to optimize block surgical schedules," European Journal of Operational Research, Elsevier, vol. 235(1), pages 138-148.
    8. Michael R. Wagner & Zinovy Radovilsky, 2012. "Optimizing Boat Resources at the U.S. Coast Guard: Deterministic and Stochastic Models," Operations Research, INFORMS, vol. 60(5), pages 1035-1049, October.
    9. Loïc Deklerck & Babak Akbarzadeh & Broos Maenhout, 2022. "Constructing and evaluating a master surgery schedule using a service-level approach," Operational Research, Springer, vol. 22(4), pages 3663-3711, September.
    10. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    11. Sebastian Rachuba & Brigitte Werners, 2017. "A fuzzy multi-criteria approach for robust operating room schedules," Annals of Operations Research, Springer, vol. 251(1), pages 325-350, April.
    12. van den Broek d’Obrenan, Anne & Ridder, Ad & Roubos, Dennis & Stougie, Leen, 2020. "Minimizing bed occupancy variance by scheduling patients under uncertainty," European Journal of Operational Research, Elsevier, vol. 286(1), pages 336-349.
    13. Francesca Guerriero & Rosita Guido, 2011. "Operational research in the management of the operating theatre: a survey," Health Care Management Science, Springer, vol. 14(1), pages 89-114, March.
    14. Mahdi Noorizadegan & Abbas Seifi, 2018. "An efficient computational method for large scale surgery scheduling problems with chance constraints," Computational Optimization and Applications, Springer, vol. 69(2), pages 535-561, March.
    15. Morteza Lalmazloumian & M. Fazle Baki & Majid Ahmadi, 2023. "A two-stage stochastic optimization framework to allocate operating room capacity in publicly-funded hospitals under uncertainty," Health Care Management Science, Springer, vol. 26(2), pages 238-260, June.
    16. Brecht Cardoen & Jeroen Beliën & Mario Vanhoucke, 2015. "On the design of custom packs: grouping of medical disposable items for surgeries," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7343-7359, December.

  7. Z S Hua & B Zhang & J Yang & D S Tan, 2007. "A new approach of forecasting intermittent demand for spare parts inventories in the process industries," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(1), pages 52-61, January.

    Cited by:

    1. Hua, Zhongsheng & Zhang, Bin, 2008. "Improving density forecast by modeling asymmetric features: An application to S&P500 returns," European Journal of Operational Research, Elsevier, vol. 185(2), pages 716-725, March.
    2. G. Peter Zhang & Yusen Xia & Maohua Xie, 2024. "Intermittent demand forecasting with transformer neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 1051-1072, August.
    3. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
    4. Aiping Jiang & Qiuguo Chi & Junjun Gao & Maoguo Wu, 2019. "An Integrated Approach to Forecasting Intermittent Demand for Electric Power Materials," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1309-1335, April.
    5. van Wingerden, E. & Basten, R.J.I. & Dekker, R. & Rustenburg, W.D., 2014. "More grip on inventory control through improved forecasting: A comparative study at three companies," International Journal of Production Economics, Elsevier, vol. 157(C), pages 220-237.
    6. Lifang Xiao & Xiangyang Chen & Hao Wang, 2021. "Calculation and realization of new method grey residual error correction model," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-13, July.
    7. Aysun Kapucugil Ikiz & Gizem Halil Utma, 2023. "Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 1-31, June.
    8. Pinçe, Çerağ & Turrini, Laura & Meissner, Joern, 2021. "Intermittent demand forecasting for spare parts: A Critical review," Omega, Elsevier, vol. 105(C).
    9. Sinan Apak, 2015. "A Bayesian Approach Proposal For Inventory Cost and Demand Forecasting," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(2), pages 41-48, December.
    10. Van der Auweraer, Sarah & Boute, Robert N. & Syntetos, Aris A., 2019. "Forecasting spare part demand with installed base information: A review," International Journal of Forecasting, Elsevier, vol. 35(1), pages 181-196.
    11. Jože Martin Rožanec & Blaž Fortuna & Dunja Mladenić, 2022. "Reframing Demand Forecasting: A Two-Fold Approach for Lumpy and Intermittent Demand," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    12. Aiping Jiang & Kwok Leung Tam & Xiaoyun Guo & Yufeng Zhang, 2020. "A new approach to forecasting intermittent demand based on the mixed zero‐truncated Poisson model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 69-83, January.
    13. Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
    14. Z Hua & J Yang & F Huang & X Xu, 2009. "A static-dynamic strategy for spare part inventory systems with nonstationary stochastic demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1254-1263, September.
    15. Rego, José Roberto do & Mesquita, Marco Aurélio de, 2015. "Demand forecasting and inventory control: A simulation study on automotive spare parts," International Journal of Production Economics, Elsevier, vol. 161(C), pages 1-16.
    16. Altay, Nezih & Rudisill, Frank & Litteral, Lewis A., 2008. "Adapting Wright's modification of Holt's method to forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 111(2), pages 389-408, February.
    17. Gary Mitchell & Meike Niederhausen, 2010. "On Replenishing Items with Seasonal Intermittent Demand," American Journal of Economics and Business Administration, Science Publications, vol. 2(1), pages 90-102, March.
    18. Zhang, Bin & Xu, Xiaoyan & Hua, Zhongsheng, 2009. "A binary solution method for the multi-product newsboy problem with budget constraint," International Journal of Production Economics, Elsevier, vol. 117(1), pages 136-141, January.

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