Iterative Methods for Queuing and Manufacturing Systems
Iterative Methods for Queuing and Manufacturing Systems introduces the recent advances and developments in iterative methods for solving Markovian queuing and manufacturing problems.
Key highlights include:
- an introduction to simulation and simulation software packages;
- Markovian models with applications in inventory control and supply chains; future research directions.
With numerous exercises and fully-worked examples, this book will be essential reading for anyone interested in the formulation and computation of queuing and manufacturing systems but it will be of particular interest to students, practitioners and researchers in Applied Mathematics, Scientific Computing and Operational Research.
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applied to solving average profit average running cost backlog cost batch arrivals block matrix buffer central warehouse Chan Chapter Ching circulant approximation circulant matrix Circulant preconditioners classical iterative method Comput conjugate gradient method construct delivery time guarantee discussed eigenvalues exponentially distributed fast convergence rate Gauss-Seidel method GC~l given in Section Hence HPP policy inter-arrival inventory system irreducible iterations for convergence Jacobi method linear system machine-inventory system manufacturing systems Markov chain Markov process Markovian queuing maximum allowable backlog MMPP networks normal null space null vector number of iterations number of machines numerical examples O(nlogn obtained operations parameters PCG method PCG type methods Poisson process preconditioned linear system preconditioned matrix preconditioned system preconditioner Proof Proposition queue queuing system rank(G singular values clustered solve the preconditioned solving the steady-state steady-state probability distribution steady-state probability vector Toeplitz Toeplitz matrix unit of product unreliable machines waiting spaces zero