A Probabilistic Approach to Growth Networks

Published Online:https://doi.org/10.1287/opre.2021.2195

References

  • Anselmi J, D’Auria B, Walton N (2013) Closed queueing networks under congestion: Nonbottleneck independence and bottleneck convergence. Math. Oper. Res. 38(3):469–491.LinkGoogle Scholar
  • Banerjee S, Freund D, Lykouris T (2022) Pricing and optimization in shared vehicle systems: An approximation framework. Oper. Res. Forthcoming.Google Scholar
  • Benjaafar S, Liu H, Wu S (2022) Dimensioning on-demand vehicle sharing systems. Management Sci. Forthcoming.Google Scholar
  • Berger A, Bregman L, Kogan Y (1999) Bottleneck analysis in multiclass closed queueing networks and its application. Queueing Systems 31(3–4):217–237.CrossrefGoogle Scholar
  • Braverman A, Dai J, Liu X, Yin L (2019) Empty-car routing in ridesharing systems. Oper. Res. 67(5):1437–1452.LinkGoogle Scholar
  • Chesarone-Cataldo M, Guérin C, Yu J, Wedlich-Soldner R, Blanchoin L, Goode B (2011) The myosin passenger protein Smy1 controls actin cable structure and dynamics by acting as a formin damper. Developmental Cell 21(2):217–230.CrossrefGoogle Scholar
  • Choudhury G, Leung K, Whitt W (1995) Calculating normalization constants of closed queueing networks by numerically inverting their generating functions. J. ACM 42(5):935–970.CrossrefGoogle Scholar
  • Gardner M, Zanic M, Gell C, Bormuth V, Howard J (2011) Depolymerizing kinesins Kip3 and MCAK shape cellular microtubule architecture by differential control of catastrophe. Cell 147:1092–1103.CrossrefGoogle Scholar
  • Goehring N, Hyman A (2012) Organelle growth control through limiting pools of cytoplasmic components. Current Biology 22(9):R330–R339.CrossrefGoogle Scholar
  • Good M, Vahey M, Skandarajah A, Fletcher D, Heald R (2013) Cytoplasmic volume modulates spindle size during embryogenesis. Sci. 342:856–860.CrossrefGoogle Scholar
  • Johnson K, Simchi-Levi D, Sun P (2014) Analyzing scrip systems. Oper. Res. 62(3):524–534.LinkGoogle Scholar
  • Knessl C, Tier C (1990) Asymptotic expansion for large closed queuing networks. J. ACM 37(1):144–174.CrossrefGoogle Scholar
  • Kogan Y (1992) Another approach to asymptotic expansions for large closed queueing networks. Oper. Res. Lett. 11(5):317–321.CrossrefGoogle Scholar
  • Marshall W (2016) Cell geometry: How cells count and measure size. Annual Rev. Biophysics 45:49–64.CrossrefGoogle Scholar
  • Marshall W, Qin H, Brenni M, Rosenbaum J (2005) Flagellar length control system: Testing a simple model based on intraflagellar transport and turnover. Molecular Biology Cell 16:270–278.CrossrefGoogle Scholar
  • McKenna J, Mitra D (1982) Integral representations and asymptotic expansions for closed Markovian queueing networks: Normal usage. Bell Systems Tech. J. 61(5):661–684.CrossrefGoogle Scholar
  • Michelot A, Drubin D (2011) Building distinct actin filament networks in a common cytoplasm. Current Biology 21:R560–R569.CrossrefGoogle Scholar
  • Mohapatra L, Goode B, Kondev J (2015) Antenna mechanism of length control of actin cables. PLOS Comput. Biology 11(6):e1004160.CrossrefGoogle Scholar
  • Mohapatra L, Goode B, Jelenković P, Phillips R, Kondev J (2016) Design principles of length control of cytoskeletal structures. Annual Rev. Biophysics 45:85–116.CrossrefGoogle Scholar
  • Mohapatra L, Lagny T, Harbage D, Jelenković P, Kondev J (2017) The limiting-pool mechanism fails to control the size of multiple organelles. Cell Systems 4(5):559–567.CrossrefGoogle Scholar
  • Pittel B (1979) Closed exponential networks of queues with saturation: The Jackson-type stationary distribution and its asymptotic analysis. Math. Oper. Res. 4(4):357–378.LinkGoogle Scholar
  • van Kreveld L, Boxma O, Dorsman JP, Mandjes M (2020) Scaling limits for closed product-form queueing networks. Perform. Evaluation 151:10220.Google Scholar
  • Weber S, Brangwynne C (2015) Inverse size scaling of the nucleolus by a concentration-dependent phase transition. Current Biology 25:641–646.CrossrefGoogle Scholar
  • Weiss A, Shwartz A (1995) Large Deviations for Performance Analysis: Queues, Communications, and Computing (Chapman & Hall, New York).Google Scholar
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