American Institute of Mathematical Sciences

Advanced
  • Previous Article
    Statistical process control optimization with variable sampling interval and nonlinear expected loss
  • JIMO Home
  • This Issue
  • Next Article
    Convergence analysis of a nonlinear Lagrangian method for nonconvex semidefinite programming with subproblem inexactly solved
January  2015, 11(1): 83-104. doi: 10.3934/jimo.2015.11.83

Optimization analysis of the machine repair problem with multiple vacations and working breakdowns

Cheng-Dar Liou 1,

1. 

Department of Business Administration, National Formosa University, Huwei, Yunlin, 63201

Received  April 2013 Revised  December 2013 Published  May 2014

This paper investigates the M/M/1 warm-standby machine repair problem with multiple vacations and working breakdowns. We first apply a matrix-analytic method to obtain the steady-state probabilities. Next, we construct the total expected profit per unit time and formulate an optimization problem to find the maximum profit. The particle swarm optimization (PSO) algorithm is implemented to determine the optimal number of warm standbys and two variable service rates simultaneously at the optimal maximum profit. We compare the searching results of the PSO algorithm with those of Genetic algorithm (GA) and Exhaustive Search Method (ESM) to ensure the superior searching quality of the PSO algorithm. Sensitivity analysis with numerical illustrations is also provided to improve the design quality of system engineers.
Keywords: profit analysis., Warm-standby, particle swarm optimization, working breakdown, multiple vacations.
Mathematics Subject Classification: Primary: 90B22, 68M20; Secondary: 60K2.
Citation: Cheng-Dar Liou. Optimization analysis of the machine repair problem with multiple vacations and working breakdowns. Journal of Industrial & Management Optimization, 2015, 11 (1) : 83-104. doi: 10.3934/jimo.2015.11.83
References:
[1]

M. Clerc, Particle Swarm Optimization, Translated from the 2005 French original, ISTE, London, 2006. doi: 10.1002/9780470612163.  Google Scholar

[2]

B. T. Doshi, Queueing systems with vacations-a Survey, Queueing Systems, 1 (1986), 29-66. doi: 10.1007/BF01149327.  Google Scholar

[3]

R. C. Eberhart and Y. Shi, Particle swarm optimization: Developments, applications and resources, in Proceedings of IEEE International Conference on Evolutionary Computation, Coex, Seoul, 1 (2001), 81-86. doi: 10.1109/CEC.2001.934374.  Google Scholar

[4]

R. C. Eberhart and Y. Shi, Computational Intelligence: Concepts to Implementations, Morgan Kaufmann, Burlington, 2007. Google Scholar

[5]

S. W. Fuhrmann and R. B. Cooper, Stochastic decompositions in the M/G/1 queue with generalize vacations, Operations Research, 33 (1995), 1117-1129. doi: 10.1287/opre.33.5.1117.  Google Scholar

[6]

M. Gen and R. Cheng, Genetic Algorithms and Engineering Optimization, John-Wiley & Sons, Inc., New York, 2007. doi: 10.1002/9780470172261.  Google Scholar

[7]

N. Gharbi and M. Ioualalen, Numerical investigation of finite-source multi server systems with different vacation policies, Journal of Computational and Applied Mathematics, 234 (2010), 625-635. doi: 10.1016/j.cam.2009.11.040.  Google Scholar

[8]

W. J. Gray, P. P. Wang and M. Scott, A vacation queueing model with service breakdowns, Applied Mathematical Modelling, 24 (2000), 391-400. doi: 10.1016/S0307-904X(99)00048-7.  Google Scholar

[9]

S. M. Gupta, N-policy queueing system with finite source and warm spares, Journal of Operational Research Society of India, 36 (1999), 189-217.  Google Scholar

[10]

S. M. Gupta, Machine interference problem with warm spares, sever vacations and exhaustive service, Performance Evaluation, 29 (1997), 195-211. Google Scholar

[11]

L. Haque and M. J. Armstrong, A survey of the machine interference problem, European Journal of Operational Research, 179 (2007), 469-482. doi: 10.1016/j.ejor.2006.02.036.  Google Scholar

[12]

J. H. Holland, Adaptation in Natural and Artificial Systems, An introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Ann Arbor, Mich., 1975.  Google Scholar

[13]

M. Jain and R. S. Maheshwari, N-policy for a machine repair system with spares and reneging, Applied Mathematical Modelling, 28 (2004), 513-531. doi: 10.1016/j.apm.2003.10.013.  Google Scholar

[14]

J. Jia and S. Wu, A replacement policy for a repairable system with its repairman having multiple vacations, Computers and Industrial Engineering, 57 (2009), 156-160. doi: 10.1016/j.cie.2008.11.003.  Google Scholar

[15]

F. Karaesmen and S. M. Gupta, The finite GI/M/1 queue with server vacations, Journal of the Operational Research Society, 47 (1996), 817-828. doi: 10.2307/3010289.  Google Scholar

[16]

J. C. Ke, The optimal control of an M/G/1 queueing system with server vacations, startup and breakdowns, Computers and Industrial Engineering, 44 (2003), 567-579. doi: 10.1016/S0360-8352(02)00235-8.  Google Scholar

[17]

J. C. Ke, Vacation policies for machine interference problem with an unreliable server and state-dependent service rate, Journal of the Chinese Institute of Engineers, 23 (2006), 100-114. Google Scholar

[18]

J. C. Ke and C. H. Lin, Sensitivity analysis of machine repair problems in manufacturing systems with service interruptions, Applied Mathematical Modelling, 32 (2008), 2087-2105. doi: 10.1016/j.apm.2007.07.004.  Google Scholar

[19]

J. C. Ke and C. H. Lin, A markov repairable system involving an imperfect service station with multiple vacations, Asia Pacific Journal of Operational Research, 22 (2005), 555-582. doi: 10.1142/S021759590500073X.  Google Scholar

[20]

J. C. Ke, C. H. Lin, H. I. Huang and Z. G. Zhang, An algorithm analysis of multi-server vacation model with service interruptions, Computers and Industrial Engineering, 61 (2011), 1302-1308. doi: 10.1016/j.cie.2011.08.003.  Google Scholar

[21]

J. C. Ke and K. H. Wang, Cost analysis of the M/M/R machine repair problem with balking, reneging, and server breakdowns, Journal of the Operational Research Society, 50 (1999), 275-282. doi: 10.2307/3010691.  Google Scholar

[22]

J. C. Ke and K. H. Wang, Vacation policies for machine repair problem with two type spares, Applied Mathematical Modelling, 31 (2007), 880-894. doi: 10.1016/j.apm.2006.02.009.  Google Scholar

[23]

J. Kennedy and R. C. Eberhart, Particle swarm optimization, in Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, (1995), 1942-1948. Google Scholar

[24]

J. Kennedy, R. C. Eberhart and Y. Shi, Swarm Intelligence, Morgan Kaufmann, CA, 2001. Google Scholar

[25]

B. K. Kumar and S. P. Madheswari, An M/M/2 queueing system with heterogeneous servers and multiple vacations, Mathematical and Computer Modelling, 41 (2005), 1415-1429. doi: 10.1016/j.mcm.2005.02.002.  Google Scholar

[26]

Y. Li and J. Xu, A deteriorating system with its repairman having multiple vacations, Applied Mathematics and Computation, 217 (2011), 4980-4989. doi: 10.1016/j.amc.2010.11.048.  Google Scholar

[27]

C. J. Lin and C. Y. Lee, Non-linear system control using a recurrent fuzzy neural network based on improved particle swarm optimization, International Journal of Systems and Science, 41 (2010), 381-395. Google Scholar

[28]

C. D. Liou, Note on "Cost analysis of the M/M/R machine repair problem with second optional repair: Newton-Quasi method'', Journal of Industrial and Management Optimization, 8 (2012), 727-732. doi: 10.3934/jimo.2012.8.727.  Google Scholar

[29]

L. D. Servi and S. G. Finn, M/M/1 queue with working vacation (M/M/1/WV), Performance Evaluation, 50 (2002), 41-52. doi: 10.1016/S0166-5316(02)00057-3.  Google Scholar

[30]

Y. Shi and R. C. Eberhart, Parameter selection in particle swarm optimization, Lecture Notes in Computer Science, 1447 (1998), 591-600. doi: 10.1007/BFb0040810.  Google Scholar

[31]

K. E. Stecke and J. E. Aronson, Review of operator/machine interference models, International Journal of Production Research, 23 (1985), 129-151. doi: 10.1080/00207548508904696.  Google Scholar

[32]

N. Tian and Z. G. Zhang, Vacation Queueing Models: Theory and Applications, International Series in Operations Research and Management Science, Springer-Verlag, New York, LLC 2006.  Google Scholar

[33]

K. H. Wang, Profit analysis of the MRP with a single service station subject to breakdowns, Journal of the Operational Research Society, 41 (1990), 1153-1160. Google Scholar

[34]

K. H. Wang, W. L. Chen and D. Y. Yang, Optimal management of the machine repair problem with working vacation: Newton's method, Journal of Computational and Applied Mathematics, 233 (2009), 449-458. doi: 10.1016/j.cam.2009.07.043.  Google Scholar

[35]

K. H. Wang and M. Y. Kuo, Profit analysis of the M/Ek/1 machine repair problem with a non-reliable service station, Computers and Industrial Engineering, 32 (1997), 587-594. doi: 10.1016/S0360-8352(96)00313-0.  Google Scholar

[36]

K. H. Wang, C. D. Liou and Y. H. Lin, Comparative analysis of the machine repair problem with imperfect coverage and service pressure condition, Applied Mathematical Modelling, 37 (2013), 2870-2880. doi: 10.1016/j.apm.2012.06.024.  Google Scholar

[37]

K. H. Wang, C. D. Liou and Y. L. Wang, Profit Optimization of the Multiple-Vacation Machine Repair Problem Using Particle Swarm Optimization, International Journal of Systems and Science, 2014, (Accepted DOI:10.1080/00207721.2012.757378). Google Scholar

[38]

L. Yuan, Reliability analysis for a k-out-of-n: G system with redundant dependency and repairmen having multiple vacations, Applied Mathematics and Computation, 218 (2012), 11959-11969. doi: 10.1016/j.amc.2012.06.006.  Google Scholar

[39]

D. Yue, J. Yu and W. Yue, A Markovian queue with two heterogeneous servers and multiple vacations, Journal of Industrial and Management Optimization, 5 (2009), 453-465. doi: 10.3934/jimo.2009.5.453.  Google Scholar

[40]

D. Yue, W. Yue, Z. Saffer and X. Chen, Analysis of an M/M/1 queueing system with impatient customers and a variant of multiple vacation policy, Journal of Industrial and Management Optimization, 10 (2014), 89-112. doi: 10.3934/jimo.2014.10.89.  Google Scholar

show all references

References:
[1]

M. Clerc, Particle Swarm Optimization, Translated from the 2005 French original, ISTE, London, 2006. doi: 10.1002/9780470612163.  Google Scholar

[2]

B. T. Doshi, Queueing systems with vacations-a Survey, Queueing Systems, 1 (1986), 29-66. doi: 10.1007/BF01149327.  Google Scholar

[3]

R. C. Eberhart and Y. Shi, Particle swarm optimization: Developments, applications and resources, in Proceedings of IEEE International Conference on Evolutionary Computation, Coex, Seoul, 1 (2001), 81-86. doi: 10.1109/CEC.2001.934374.  Google Scholar

[4]

R. C. Eberhart and Y. Shi, Computational Intelligence: Concepts to Implementations, Morgan Kaufmann, Burlington, 2007. Google Scholar

[5]

S. W. Fuhrmann and R. B. Cooper, Stochastic decompositions in the M/G/1 queue with generalize vacations, Operations Research, 33 (1995), 1117-1129. doi: 10.1287/opre.33.5.1117.  Google Scholar

[6]

M. Gen and R. Cheng, Genetic Algorithms and Engineering Optimization, John-Wiley & Sons, Inc., New York, 2007. doi: 10.1002/9780470172261.  Google Scholar

[7]

N. Gharbi and M. Ioualalen, Numerical investigation of finite-source multi server systems with different vacation policies, Journal of Computational and Applied Mathematics, 234 (2010), 625-635. doi: 10.1016/j.cam.2009.11.040.  Google Scholar

[8]

W. J. Gray, P. P. Wang and M. Scott, A vacation queueing model with service breakdowns, Applied Mathematical Modelling, 24 (2000), 391-400. doi: 10.1016/S0307-904X(99)00048-7.  Google Scholar

[9]

S. M. Gupta, N-policy queueing system with finite source and warm spares, Journal of Operational Research Society of India, 36 (1999), 189-217.  Google Scholar

[10]

S. M. Gupta, Machine interference problem with warm spares, sever vacations and exhaustive service, Performance Evaluation, 29 (1997), 195-211. Google Scholar

[11]

L. Haque and M. J. Armstrong, A survey of the machine interference problem, European Journal of Operational Research, 179 (2007), 469-482. doi: 10.1016/j.ejor.2006.02.036.  Google Scholar

[12]

J. H. Holland, Adaptation in Natural and Artificial Systems, An introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Ann Arbor, Mich., 1975.  Google Scholar

[13]

M. Jain and R. S. Maheshwari, N-policy for a machine repair system with spares and reneging, Applied Mathematical Modelling, 28 (2004), 513-531. doi: 10.1016/j.apm.2003.10.013.  Google Scholar

[14]

J. Jia and S. Wu, A replacement policy for a repairable system with its repairman having multiple vacations, Computers and Industrial Engineering, 57 (2009), 156-160. doi: 10.1016/j.cie.2008.11.003.  Google Scholar

[15]

F. Karaesmen and S. M. Gupta, The finite GI/M/1 queue with server vacations, Journal of the Operational Research Society, 47 (1996), 817-828. doi: 10.2307/3010289.  Google Scholar

[16]

J. C. Ke, The optimal control of an M/G/1 queueing system with server vacations, startup and breakdowns, Computers and Industrial Engineering, 44 (2003), 567-579. doi: 10.1016/S0360-8352(02)00235-8.  Google Scholar

[17]

J. C. Ke, Vacation policies for machine interference problem with an unreliable server and state-dependent service rate, Journal of the Chinese Institute of Engineers, 23 (2006), 100-114. Google Scholar

[18]

J. C. Ke and C. H. Lin, Sensitivity analysis of machine repair problems in manufacturing systems with service interruptions, Applied Mathematical Modelling, 32 (2008), 2087-2105. doi: 10.1016/j.apm.2007.07.004.  Google Scholar

[19]

J. C. Ke and C. H. Lin, A markov repairable system involving an imperfect service station with multiple vacations, Asia Pacific Journal of Operational Research, 22 (2005), 555-582. doi: 10.1142/S021759590500073X.  Google Scholar

[20]

J. C. Ke, C. H. Lin, H. I. Huang and Z. G. Zhang, An algorithm analysis of multi-server vacation model with service interruptions, Computers and Industrial Engineering, 61 (2011), 1302-1308. doi: 10.1016/j.cie.2011.08.003.  Google Scholar

[21]

J. C. Ke and K. H. Wang, Cost analysis of the M/M/R machine repair problem with balking, reneging, and server breakdowns, Journal of the Operational Research Society, 50 (1999), 275-282. doi: 10.2307/3010691.  Google Scholar

[22]

J. C. Ke and K. H. Wang, Vacation policies for machine repair problem with two type spares, Applied Mathematical Modelling, 31 (2007), 880-894. doi: 10.1016/j.apm.2006.02.009.  Google Scholar

[23]

J. Kennedy and R. C. Eberhart, Particle swarm optimization, in Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, (1995), 1942-1948. Google Scholar

[24]

J. Kennedy, R. C. Eberhart and Y. Shi, Swarm Intelligence, Morgan Kaufmann, CA, 2001. Google Scholar

[25]

B. K. Kumar and S. P. Madheswari, An M/M/2 queueing system with heterogeneous servers and multiple vacations, Mathematical and Computer Modelling, 41 (2005), 1415-1429. doi: 10.1016/j.mcm.2005.02.002.  Google Scholar

[26]

Y. Li and J. Xu, A deteriorating system with its repairman having multiple vacations, Applied Mathematics and Computation, 217 (2011), 4980-4989. doi: 10.1016/j.amc.2010.11.048.  Google Scholar

[27]

C. J. Lin and C. Y. Lee, Non-linear system control using a recurrent fuzzy neural network based on improved particle swarm optimization, International Journal of Systems and Science, 41 (2010), 381-395. Google Scholar

[28]

C. D. Liou, Note on "Cost analysis of the M/M/R machine repair problem with second optional repair: Newton-Quasi method'', Journal of Industrial and Management Optimization, 8 (2012), 727-732. doi: 10.3934/jimo.2012.8.727.  Google Scholar

[29]

L. D. Servi and S. G. Finn, M/M/1 queue with working vacation (M/M/1/WV), Performance Evaluation, 50 (2002), 41-52. doi: 10.1016/S0166-5316(02)00057-3.  Google Scholar

[30]

Y. Shi and R. C. Eberhart, Parameter selection in particle swarm optimization, Lecture Notes in Computer Science, 1447 (1998), 591-600. doi: 10.1007/BFb0040810.  Google Scholar

[31]

K. E. Stecke and J. E. Aronson, Review of operator/machine interference models, International Journal of Production Research, 23 (1985), 129-151. doi: 10.1080/00207548508904696.  Google Scholar

[32]

N. Tian and Z. G. Zhang, Vacation Queueing Models: Theory and Applications, International Series in Operations Research and Management Science, Springer-Verlag, New York, LLC 2006.  Google Scholar

[33]

K. H. Wang, Profit analysis of the MRP with a single service station subject to breakdowns, Journal of the Operational Research Society, 41 (1990), 1153-1160. Google Scholar

[34]

K. H. Wang, W. L. Chen and D. Y. Yang, Optimal management of the machine repair problem with working vacation: Newton's method, Journal of Computational and Applied Mathematics, 233 (2009), 449-458. doi: 10.1016/j.cam.2009.07.043.  Google Scholar

[35]

K. H. Wang and M. Y. Kuo, Profit analysis of the M/Ek/1 machine repair problem with a non-reliable service station, Computers and Industrial Engineering, 32 (1997), 587-594. doi: 10.1016/S0360-8352(96)00313-0.  Google Scholar

[36]

K. H. Wang, C. D. Liou and Y. H. Lin, Comparative analysis of the machine repair problem with imperfect coverage and service pressure condition, Applied Mathematical Modelling, 37 (2013), 2870-2880. doi: 10.1016/j.apm.2012.06.024.  Google Scholar

[37]

K. H. Wang, C. D. Liou and Y. L. Wang, Profit Optimization of the Multiple-Vacation Machine Repair Problem Using Particle Swarm Optimization, International Journal of Systems and Science, 2014, (Accepted DOI:10.1080/00207721.2012.757378). Google Scholar

[38]

L. Yuan, Reliability analysis for a k-out-of-n: G system with redundant dependency and repairmen having multiple vacations, Applied Mathematics and Computation, 218 (2012), 11959-11969. doi: 10.1016/j.amc.2012.06.006.  Google Scholar

[39]

D. Yue, J. Yu and W. Yue, A Markovian queue with two heterogeneous servers and multiple vacations, Journal of Industrial and Management Optimization, 5 (2009), 453-465. doi: 10.3934/jimo.2009.5.453.  Google Scholar

[40]

D. Yue, W. Yue, Z. Saffer and X. Chen, Analysis of an M/M/1 queueing system with impatient customers and a variant of multiple vacation policy, Journal of Industrial and Management Optimization, 10 (2014), 89-112. doi: 10.3934/jimo.2014.10.89.  Google Scholar

[1]

Chia-Huang Wu, Kuo-Hsiung Wang, Jau-Chuan Ke, Jyh-Bin Ke. A heuristic algorithm for the optimization of M/M/$s$ queue with multiple working vacations. Journal of Industrial & Management Optimization, 2012, 8 (1) : 1-17. doi: 10.3934/jimo.2012.8.1
[2]

Zhanyou Ma, Pengcheng Wang, Wuyi Yue. Performance analysis and optimization of a pseudo-fault Geo/Geo/1 repairable queueing system with N-policy, setup time and multiple working vacations. Journal of Industrial & Management Optimization, 2017, 13 (3) : 1467-1481. doi: 10.3934/jimo.2017002
[3]

Pikkala Vijaya Laxmi, Seleshi Demie. Performance analysis of renewal input $(a,c,b)$ policy queue with multiple working vacations and change over times. Journal of Industrial & Management Optimization, 2014, 10 (3) : 839-857. doi: 10.3934/jimo.2014.10.839
[4]

Zhanyou Ma, Wenbo Wang, Linmin Hu. Performance evaluation and analysis of a discrete queue system with multiple working vacations and non-preemptive priority. Journal of Industrial & Management Optimization, 2020, 16 (3) : 1135-1148. doi: 10.3934/jimo.2018196
[5]

Dequan Yue, Wuyi Yue, Gang Xu. Analysis of customers' impatience in an M/M/1 queue with working vacations. Journal of Industrial & Management Optimization, 2012, 8 (4) : 895-908. doi: 10.3934/jimo.2012.8.895
[6]

Miao Yu. A solution of TSP based on the ant colony algorithm improved by particle swarm optimization. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 979-987. doi: 10.3934/dcdss.2019066
[7]

Junyuan Lin, Timothy A. Lucas. A particle swarm optimization model of emergency airplane evacuations with emotion. Networks & Heterogeneous Media, 2015, 10 (3) : 631-646. doi: 10.3934/nhm.2015.10.631
[8]

Qifeng Cheng, Xue Han, Tingting Zhao, V S Sarma Yadavalli. Improved particle swarm optimization and neighborhood field optimization by introducing the re-sampling step of particle filter. Journal of Industrial & Management Optimization, 2019, 15 (1) : 177-198. doi: 10.3934/jimo.2018038
[9]

Amir Mohammad Fakoor Saghih, Azam Modares. A new dynamic model to optimize the reliability of the series-parallel systems under warm standby components. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021189
[10]

Min Zhang, Gang Li. Multi-objective optimization algorithm based on improved particle swarm in cloud computing environment. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1413-1426. doi: 10.3934/dcdss.2019097
[11]

Ning Lu, Ying Liu. Application of support vector machine model in wind power prediction based on particle swarm optimization. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1267-1276. doi: 10.3934/dcdss.2015.8.1267
[12]

Mohamed A. Tawhid, Kevin B. Dsouza. Hybrid binary dragonfly enhanced particle swarm optimization algorithm for solving feature selection problems. Mathematical Foundations of Computing, 2018, 1 (2) : 181-200. doi: 10.3934/mfc.2018009
[13]

Xia Zhao, Jianping Dou. Bi-objective integrated supply chain design with transportation choices: A multi-objective particle swarm optimization. Journal of Industrial & Management Optimization, 2019, 15 (3) : 1263-1288. doi: 10.3934/jimo.2018095
[14]

Abdulrazzaq T. Abed, Azzam S. Y. Aladool. Applying particle swarm optimization based on Padé approximant to solve ordinary differential equation. Numerical Algebra, Control & Optimization, 2021  doi: 10.3934/naco.2021008
[15]

Omar Saber Qasim, Ahmed Entesar, Waleed Al-Hayani. Solving nonlinear differential equations using hybrid method between Lyapunov's artificial small parameter and continuous particle swarm optimization. Numerical Algebra, Control & Optimization, 2021, 11 (4) : 633-644. doi: 10.3934/naco.2021001
[16]

Shaojun Lan, Yinghui Tang. Performance analysis of a discrete-time $ Geo/G/1$ retrial queue with non-preemptive priority, working vacations and vacation interruption. Journal of Industrial & Management Optimization, 2019, 15 (3) : 1421-1446. doi: 10.3934/jimo.2018102
[17]

Tao Zhang, Yue-Jie Zhang, Qipeng P. Zheng, P. M. Pardalos. A hybrid particle swarm optimization and tabu search algorithm for order planning problems of steel factories based on the Make-To-Stock and Make-To-Order management architecture. Journal of Industrial & Management Optimization, 2011, 7 (1) : 31-51. doi: 10.3934/jimo.2011.7.31
[18]

Shan Gao, Jinting Wang. On a discrete-time GI$^X$/Geo/1/N-G queue with randomized working vacations and at most $J$ vacations. Journal of Industrial & Management Optimization, 2015, 11 (3) : 779-806. doi: 10.3934/jimo.2015.11.779
[19]

Dequan Yue, Jun Yu, Wuyi Yue. A Markovian queue with two heterogeneous servers and multiple vacations. Journal of Industrial & Management Optimization, 2009, 5 (3) : 453-465. doi: 10.3934/jimo.2009.5.453
[20]

Annalisa Pascarella, Alberto Sorrentino, Cristina Campi, Michele Piana. Particle filtering, beamforming and multiple signal classification for the analysis of magnetoencephalography time series: a comparison of algorithms. Inverse Problems & Imaging, 2010, 4 (1) : 169-190. doi: 10.3934/ipi.2010.4.169

2020 Impact Factor: 1.801

Tools

Metrics

  • PDF downloads (75)
  • HTML views (0)
  • Cited by (5)

Other articles
by authors

[Back to Top]

Copyright © 2021 American Institute of Mathematical Sciences | Privacy Policy