5,169 research outputs found
An inventory model for manufacturing systems with delivery time guarantees
No full textThis paper studies optimal (s,S) policies for production planning in one-machine manufacturing systems. The machine produces one type of product with delivery time guarantees on the products offered to the customers. The inter-arrival time of the demand and the processing time for one unit of product are assumed to be exponentially distributed. The total delivery time (total lead time) consists of two parts: the cycle time and the delivery time. The cycle time is the time between the arrival of an order and the time requested product leaves the manufacturing system. The delivery time is the time from the manufacturing system to the customer. We model the delivery time by a shifted exponential distribution. Unbiased and consistent estimators are derived for this distribution. The analytical form of the steady state probability distribution for the inventory levels is derived. The average profit of the system can be written in terms of the resulting probability distribution. Hence the optimal (s,S) policy can be obtained by varying different possible values of s and S
Markov-modulated poisson processes for multi-location inventory problems
No full textIn this paper we consider inventory systems of multi-location. It is common to allow emergency lateral transshipments from local locations to the main depot. Here we propose a new model for the inventory system of consumable items. The inventory system of each location and the main depot is modeled by Markovian queueing networks. The transshipments are modeled by the Markov-Modulated Poisson Process (MMPP) which is a generalization of the Poisson process
Circulant preconditioners for failure prone manufacturing systems
No full textThis paper studies the application of preconditioned conjugate-gradient methods in solving for the steady-state probability distribution of manufacturing systems. We consider the optimal hedging policy for a failure prone one-machine system. The machine produces one type of product, and its demand has finite batch arrival. The machine states and the inventory levels are modeled as Markovian processes. We construct the generator matrix for the machine-inventory system. The preconditioner is constructed by taking the circulant approximation of the near-Toeplitz structure of the generator matrix. We prove that the preconditioned linear system has singular values clustered around one when the number of inventory levels tends to infinity. Hence conjugate-gradient methods will converge very fast when applied to solving the preconditioned linear system. Numerical examples are given to verify our claim. The average running cost for the system can be written in terms of the steady state probability distribution. The optimal hedging point can then be obtained by varying different values of the hedging point
Markovian approximation for manufacturing systems of unreliable machines in tandem
No full textThis paper studies production planning of manufacturing systems of unreliable machines in tandem. The manufacturing system considered here produces one type of product. The demand is assumed to be a Poisson process and the processing time for one unit of product in each machine is exponentially distributed. A broken machine is subject to a sequence of repairing processes. The up time and the repairing time in each phase are assumed to be exponentially distributed. We study the manufacturing system by considering each machine as an individual system with stochastic supply and demand. The Markov Modulated Poisson Process (MMPP) is applied to model the process of supply. Numerical examples are given to demonstrate the accuracy of the proposed method. We employ (s, S) policy as production control. Fast algorithms are presented to solve the average running costs of the machine system for a given (s, S) policy and hence the approximated optimal (s, S) policy
Production scheduling. A production model with delivery time guarantee for manufacturing systems with early setup
No full textWe consider optimal (s, S) policies with delivery time guarantees for production planning in manufacturing systems with early set-up. The machine produces one type of product with delivery time guarantees on the products offered to the customers. The inter-arrival time of the demand and the processing time for one unit of product are assumed to be exponentially distributed. A set-up time is required for the machine. We model the set-up by the exponential distribution. The analytical form of the steady state probability distribution for the inventory levels is derived. The average profit of the system can be written in terms of this probability distribution. Hence the optimal (s, S) policy can be obtained by varying different possible values of s and S
Iterative methods for manufacturing systems of two stations in tandem
No full textThis paper studies the application of Preconditioned Conjugate Gradient (PCG) methods in solving the steady state probability distribution of two-station manufacturing systems under hedging point production policy. The manufacturing system produces one type of product, and its demand is modeled as a Poisson process. Preconditioner is constructed by taking circulant approximation of the generator matrix of the system. We prove that the preconditioned linear system has singular values clustered around one when the number of inventory levels tends to infinity. Hence, conjugate gradient methods will converge very fast when applied to the solution of the preconditioned linear system. Numerical examples are given to verify our claim
A note on the convergence of asynchronous greedy algorithm with relaxation in a multiclass queueing environment
No full textIn this letter, we consider the convergence of an asynchronous greedy algorithm with relaxation for Nash equilibrium in a noncooperative multiclass queueing environment. The process of an asynchronous greedy algorithm is equivalent to the iteration of the Jacobi method in solving a linear system. However, it has been proved that the algorithm converges only for some particular range of queueing parameters. Here we propose the asynchronous greedy algorithm with relaxation, which is in principle equivalent to solving a linear system by the Jacobi method with relaxation. We propose also some relaxation parameters such that our algorithm converges very fast
Recommended from our members
Wai-Yim Ching: Raffinement structurel et liaison intramoléculaire dans le SRAS-CoV-2 Protéine de pointe
No full textCette présentation a été faite par Wai-Yim Ching. Le titre de la présentation est: “Raffinement structurel et liaison intramoléculaire dans le SRAS-CoV-2 Protéine de pointe .”
--
Chaque mois, l'équipe COVID Information Commons (avec le Northeast Big Data Innovation Hub) rassemble un groupe de chercheurs étudiant de nombreux aspects de la pandémie actuelle, pour partager leurs recherches et répondre aux questions de notre communauté. Ces événements mettent en valeur les efforts continus des scientifiques dans la lutte contre le COVID-19, notamment les opportunités de collaboration
Recommended from our members
Wai-Yim Ching: Structural Refinement and Intramolecular Binding in SARS-CoV-2 Spike Protein
No full textThis presentation was made by Wai-Yim Ching, University of Missouri-Kansas City. The presentation’s title is: “Structural Refinement and Intramolecular Binding in SARS-CoV-2 Spike Protein.” Funded by NSF Mathematical & Physical Sciences / Division of Materials Research.
--
Every month, the COVID Information Commons Team (along with the Northeast Big Data Innovation Hub) brings together a group of researchers studying wide-ranging aspects of the current pandemic, to share their research and answer questions from our community. The events showcase scientists' ongoing efforts in the fight against COVID-19, including opportunities for collaboration
- …
