Data analytics and artificial intelligence for inventory and supply chain management / / edited by Dinesh K. Sharma, Madhu Jain |
Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (293 pages) |
Disciplina | 260 |
Collana | Inventory Optimization |
Soggetto topico |
Business logistics - Data processing
Logística industrial Processament de dades |
Soggetto genere / forma | Llibres electrònics |
ISBN | 981-19-6337-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Foreword -- Preface -- Acknowledgements -- About This Book -- Contents -- Editors and Contributors -- 1 Markov Decision Processes of a Two-Tier Supply Chain Inventory System -- 1.1 Markov Decision Processes of a Supply Chain -- 1.2 M/M1 + M2/1 /K-Rule/f1-policy Queues + Inventory Model with Backorders -- 1.2.1 The Stable M/M1 + M/1 /K-rule/f1-policy Model -- 1.3 Performance Measures for the Inventory-Queueing System -- 1.4 Results for the SCM Attached to M/M/1 Queues with Zero Lead Time -- 1.5 SCM Attached M/M1 + M2/1/K-rule/f2-Policy with Dissatisfied Customers -- 1.5.1 Optimum Order Quantity "Q*" -- 1.6 Conclusion -- References -- 2 Nature-Inspired Optimization for Inventory Models with Imperfect Production -- 2.1 Introduction -- 2.2 An Imperfect Production Inventory Model -- 2.3 Inventory Production Systems with Process Reliability -- 2.4 Nature-Inspired Optimization at a Glance -- 2.5 Important Contributions on Nature-Inspired Optimization for Inventory Control -- 2.6 Economic Production Quantity (EPQ) Models and NIO Algorithms -- 2.7 Conclusions -- References -- 3 A Multi-objective Mathematical Model for Socially Responsible Supply Chain Inventory Planning -- 3.1 Introduction -- 3.2 Literature Survey -- 3.3 Assumptions and Notation -- 3.4 Multi-objective Model -- 3.4.1 Objective Functions -- 3.4.2 Constraints Sets -- 3.5 Solution Methodology and Result -- 3.6 Conclusions -- References -- 4 Artificial Intelligence Computing and Nature-Inspired Optimization Techniques for Effective Supply Chain Management -- 4.1 Introduction -- 4.2 Basic Concepts of AI -- 4.2.1 Categorization of AI -- 4.3 Nature-Inspired Optimization (NIO) -- 4.4 Supply Chain Management -- 4.4.1 Two Echelon Supply Chain Inventory Model -- 4.5 Role of AI and NIO Algorithm in SCM -- 4.5.1 Artificial Neural Network -- 4.5.2 Adaptive Neuro-Fuzzy Inference System (ANFIS).
4.5.3 Inventory Control and Planning -- 4.5.4 Transportation Network Design -- 4.5.5 Purchasing and Supply Management -- 4.5.6 e-Synchronized SCM -- 4.6 Adapted Model Related to Operational Decisions in Supply Chain (SC) Network -- 4.7 Literature Survey on AI, NIO, and Supply Chain Management (SCM) -- 4.8 Research Directions for the Future and Closing Remarks -- References -- 5 An EPQ Model for Imperfect Production System with Deteriorating Items, Price-Dependent Demand, Rework and Lead Time Under Markdown Policy -- 5.1 Introduction -- 5.2 Literature Survey -- 5.3 Assumptions and Notations -- 5.3.1 Notations -- 5.3.2 Assumptions -- 5.4 Mathematical Model -- 5.5 Numerical Illustration -- 5.6 Conclusions -- References -- 6 Retrial Inventory-Queueing Model with Inspection Processes and Imperfect Production -- 6.1 Introduction -- 6.2 Model Description -- 6.3 Joint Probability Distributions -- 6.3.1 Governing Equations -- 6.3.2 Derivation of Joint Probability Distribution Function -- 6.4 System Performance Indices -- 6.5 Cost Optimization -- 6.6 Numerical Illustration and Sensitivity Analysis -- 6.7 Conclusions -- References -- 7 Inventory Model for Growing Items and Its Waste Management -- 7.1 Introduction -- 7.1.1 Literature Survey -- 7.1.2 Motivation -- 7.2 Mathematical Model and Analysis -- 7.3 Profit Function -- 7.4 Profit from Waste Management -- 7.5 Conclusions -- References -- 8 Pavement Cracks Inventory Survey with Machine Deep Learning Models -- 8.1 Introduction -- 8.2 Literature Survey -- 8.3 Technical Background -- 8.3.1 Convolution -- 8.3.2 Activation -- 8.3.3 Max Pooling -- 8.3.4 Flatten Layer -- 8.3.5 Fully Connected Layers -- 8.3.6 Classifcation -- 8.4 Experimental Work -- 8.5 Observations on the Results -- 8.6 Conclusion -- References -- 9 Decarbonisation Through Production of Rhino Bricks From the Waste Plastics: EPQ Model. 9.1 Introduction -- 9.2 Motivation and Problem Description -- 9.3 Notations -- 9.4 Assumptions -- 9.5 Model Formulation -- 9.6 Solution Procedure -- 9.7 Numerical Illustration -- 9.8 Sensitivity Analysis -- 9.9 Managerial Implications -- 9.10 Conclusions -- References -- 10 Cost Analysis of Supply Chain Model for Deteriorating Inventory Items with Shortages in Fuzzy Environment -- 10.1 Introduction -- 10.2 Assumptions and Notations -- 10.3 Development and Analysis of the Model in Crisp Form -- 10.4 Developing Model and Computing Its Solution by Using FP -- 10.5 System of Non-Linear Equations and Its Solution -- 10.6 Numerical Computing and Sensitivity Analysis -- 10.7 Conclusions -- References -- 11 Multi-echelon Inventory Planning in Supply Chain -- 11.1 Introduction -- 11.2 Literature Survey -- 11.3 Model Description -- 11.4 Expected Lead Time -- 11.5 Optimal Policy -- 11.6 Some Special Cases -- 11.7 Cost Minimization Analysis -- 11.8 Numerical Results -- 11.9 Conclusions -- References -- 12 Impact of Renewable Energy on a Flexible Production System Under Preorder and Online Payment Discount Facility -- 12.1 Introduction -- 12.2 Review of Literature -- 12.3 Notations and Assumptions -- 12.3.1 Notations -- 12.3.2 Assumptions -- 12.4 Mathematical Modeling -- 12.5 Solution Methodology -- 12.6 Numerical Illustration -- 12.7 Concavity -- 12.8 Sensitivity Analysis -- 12.9 Observation -- 12.10 Conclusion -- References -- 13 Impact of Preservation Technology Investment and Order Cost Reduction on an Inventory Model Under Different Carbon Emission Policies -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Notations and Assumptions -- 13.3.1 Notations -- 13.3.2 Assumptions -- 13.4 Mathematical Modeling -- 13.4.1 Profit Function Under Different Carbon Tax Regulations -- 13.5 Numerical Illustration -- 13.6 Concavity -- 13.7 Sensitivity Analysis. 13.8 Observations -- 13.9 Conclusion -- References -- 14 The Impact of Corporate Credibility on Inventory Management Decisions -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Objective of Study -- 14.4 Research Methodology -- 14.5 Discussion -- 14.5.1 Genetic Algorithm (NSGA-II) -- 14.5.2 Neural Algorithm -- 14.6 Conclusion -- References -- 15 A Bidirectional Neural Network Dynamic Inventory Control Model for Reservoir Operation -- 15.1 Introduction -- 15.2 Basics of Dynamic Inventory Control and Dynamic Reservoir Operations -- 15.3 Structure of the Bidirectional Recurrent Neural Network-Based Dynamic Inventory Control Model -- 15.4 Design of Neuro-Fuzzy Irrigation Reservoir Operation Using Bidirectional Recurrent Neural Network (BRNN) -- 15.4.1 Input Layer: Water Demand and Supply Analysis -- 15.4.2 Output Layer -- 15.4.3 Fuzzy Interface -- 15.4.4 Hidden Layer -- 15.5 Training and Validation of the Irrigation Model Using Data -- 15.5.1 Training -- 15.5.2 Evaluation of Model Performance -- 15.6 Conclusion -- References. |
Record Nr. | UNISA-996499871103316 |
Singapore : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. di Salerno | ||
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Data analytics and artificial intelligence for inventory and supply chain management / / edited by Dinesh K. Sharma, Madhu Jain |
Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (293 pages) |
Disciplina | 260 |
Collana | Inventory Optimization |
Soggetto topico |
Business logistics - Data processing
Logística industrial Processament de dades |
Soggetto genere / forma | Llibres electrònics |
ISBN | 981-19-6337-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Foreword -- Preface -- Acknowledgements -- About This Book -- Contents -- Editors and Contributors -- 1 Markov Decision Processes of a Two-Tier Supply Chain Inventory System -- 1.1 Markov Decision Processes of a Supply Chain -- 1.2 M/M1 + M2/1 /K-Rule/f1-policy Queues + Inventory Model with Backorders -- 1.2.1 The Stable M/M1 + M/1 /K-rule/f1-policy Model -- 1.3 Performance Measures for the Inventory-Queueing System -- 1.4 Results for the SCM Attached to M/M/1 Queues with Zero Lead Time -- 1.5 SCM Attached M/M1 + M2/1/K-rule/f2-Policy with Dissatisfied Customers -- 1.5.1 Optimum Order Quantity "Q*" -- 1.6 Conclusion -- References -- 2 Nature-Inspired Optimization for Inventory Models with Imperfect Production -- 2.1 Introduction -- 2.2 An Imperfect Production Inventory Model -- 2.3 Inventory Production Systems with Process Reliability -- 2.4 Nature-Inspired Optimization at a Glance -- 2.5 Important Contributions on Nature-Inspired Optimization for Inventory Control -- 2.6 Economic Production Quantity (EPQ) Models and NIO Algorithms -- 2.7 Conclusions -- References -- 3 A Multi-objective Mathematical Model for Socially Responsible Supply Chain Inventory Planning -- 3.1 Introduction -- 3.2 Literature Survey -- 3.3 Assumptions and Notation -- 3.4 Multi-objective Model -- 3.4.1 Objective Functions -- 3.4.2 Constraints Sets -- 3.5 Solution Methodology and Result -- 3.6 Conclusions -- References -- 4 Artificial Intelligence Computing and Nature-Inspired Optimization Techniques for Effective Supply Chain Management -- 4.1 Introduction -- 4.2 Basic Concepts of AI -- 4.2.1 Categorization of AI -- 4.3 Nature-Inspired Optimization (NIO) -- 4.4 Supply Chain Management -- 4.4.1 Two Echelon Supply Chain Inventory Model -- 4.5 Role of AI and NIO Algorithm in SCM -- 4.5.1 Artificial Neural Network -- 4.5.2 Adaptive Neuro-Fuzzy Inference System (ANFIS).
4.5.3 Inventory Control and Planning -- 4.5.4 Transportation Network Design -- 4.5.5 Purchasing and Supply Management -- 4.5.6 e-Synchronized SCM -- 4.6 Adapted Model Related to Operational Decisions in Supply Chain (SC) Network -- 4.7 Literature Survey on AI, NIO, and Supply Chain Management (SCM) -- 4.8 Research Directions for the Future and Closing Remarks -- References -- 5 An EPQ Model for Imperfect Production System with Deteriorating Items, Price-Dependent Demand, Rework and Lead Time Under Markdown Policy -- 5.1 Introduction -- 5.2 Literature Survey -- 5.3 Assumptions and Notations -- 5.3.1 Notations -- 5.3.2 Assumptions -- 5.4 Mathematical Model -- 5.5 Numerical Illustration -- 5.6 Conclusions -- References -- 6 Retrial Inventory-Queueing Model with Inspection Processes and Imperfect Production -- 6.1 Introduction -- 6.2 Model Description -- 6.3 Joint Probability Distributions -- 6.3.1 Governing Equations -- 6.3.2 Derivation of Joint Probability Distribution Function -- 6.4 System Performance Indices -- 6.5 Cost Optimization -- 6.6 Numerical Illustration and Sensitivity Analysis -- 6.7 Conclusions -- References -- 7 Inventory Model for Growing Items and Its Waste Management -- 7.1 Introduction -- 7.1.1 Literature Survey -- 7.1.2 Motivation -- 7.2 Mathematical Model and Analysis -- 7.3 Profit Function -- 7.4 Profit from Waste Management -- 7.5 Conclusions -- References -- 8 Pavement Cracks Inventory Survey with Machine Deep Learning Models -- 8.1 Introduction -- 8.2 Literature Survey -- 8.3 Technical Background -- 8.3.1 Convolution -- 8.3.2 Activation -- 8.3.3 Max Pooling -- 8.3.4 Flatten Layer -- 8.3.5 Fully Connected Layers -- 8.3.6 Classifcation -- 8.4 Experimental Work -- 8.5 Observations on the Results -- 8.6 Conclusion -- References -- 9 Decarbonisation Through Production of Rhino Bricks From the Waste Plastics: EPQ Model. 9.1 Introduction -- 9.2 Motivation and Problem Description -- 9.3 Notations -- 9.4 Assumptions -- 9.5 Model Formulation -- 9.6 Solution Procedure -- 9.7 Numerical Illustration -- 9.8 Sensitivity Analysis -- 9.9 Managerial Implications -- 9.10 Conclusions -- References -- 10 Cost Analysis of Supply Chain Model for Deteriorating Inventory Items with Shortages in Fuzzy Environment -- 10.1 Introduction -- 10.2 Assumptions and Notations -- 10.3 Development and Analysis of the Model in Crisp Form -- 10.4 Developing Model and Computing Its Solution by Using FP -- 10.5 System of Non-Linear Equations and Its Solution -- 10.6 Numerical Computing and Sensitivity Analysis -- 10.7 Conclusions -- References -- 11 Multi-echelon Inventory Planning in Supply Chain -- 11.1 Introduction -- 11.2 Literature Survey -- 11.3 Model Description -- 11.4 Expected Lead Time -- 11.5 Optimal Policy -- 11.6 Some Special Cases -- 11.7 Cost Minimization Analysis -- 11.8 Numerical Results -- 11.9 Conclusions -- References -- 12 Impact of Renewable Energy on a Flexible Production System Under Preorder and Online Payment Discount Facility -- 12.1 Introduction -- 12.2 Review of Literature -- 12.3 Notations and Assumptions -- 12.3.1 Notations -- 12.3.2 Assumptions -- 12.4 Mathematical Modeling -- 12.5 Solution Methodology -- 12.6 Numerical Illustration -- 12.7 Concavity -- 12.8 Sensitivity Analysis -- 12.9 Observation -- 12.10 Conclusion -- References -- 13 Impact of Preservation Technology Investment and Order Cost Reduction on an Inventory Model Under Different Carbon Emission Policies -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Notations and Assumptions -- 13.3.1 Notations -- 13.3.2 Assumptions -- 13.4 Mathematical Modeling -- 13.4.1 Profit Function Under Different Carbon Tax Regulations -- 13.5 Numerical Illustration -- 13.6 Concavity -- 13.7 Sensitivity Analysis. 13.8 Observations -- 13.9 Conclusion -- References -- 14 The Impact of Corporate Credibility on Inventory Management Decisions -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Objective of Study -- 14.4 Research Methodology -- 14.5 Discussion -- 14.5.1 Genetic Algorithm (NSGA-II) -- 14.5.2 Neural Algorithm -- 14.6 Conclusion -- References -- 15 A Bidirectional Neural Network Dynamic Inventory Control Model for Reservoir Operation -- 15.1 Introduction -- 15.2 Basics of Dynamic Inventory Control and Dynamic Reservoir Operations -- 15.3 Structure of the Bidirectional Recurrent Neural Network-Based Dynamic Inventory Control Model -- 15.4 Design of Neuro-Fuzzy Irrigation Reservoir Operation Using Bidirectional Recurrent Neural Network (BRNN) -- 15.4.1 Input Layer: Water Demand and Supply Analysis -- 15.4.2 Output Layer -- 15.4.3 Fuzzy Interface -- 15.4.4 Hidden Layer -- 15.5 Training and Validation of the Irrigation Model Using Data -- 15.5.1 Training -- 15.5.2 Evaluation of Model Performance -- 15.6 Conclusion -- References. |
Record Nr. | UNINA-9910629299303321 |
Singapore : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. Federico II | ||
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Decision Science in Action [[electronic resource] ] : Theory and Applications of Modern Decision Analytic Optimisation / / edited by Kusum Deep, Madhu Jain, Said Salhi |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (276 pages) |
Disciplina | 658.403 |
Collana | Asset Analytics, Performance and Safety Management |
Soggetto topico |
Operations research
Statistics Operations Research/Decision Theory Operations Research, Management Science Statistics for Business, Management, Economics, Finance, Insurance |
ISBN | 981-13-0860-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1: π Fraction-based optimization of the pbm antenna benchmarks -- Chapter 2: Benchmark function generators for single-objective robust optimisation algorithms -- Chapter 3: Convergence of gravitational search algorithm on linear and quadratic functions -- Chapter 4: An algorithm of multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes -- Chapter 5: An artificial bee colony based hyper-heuristic for the single machine order acceptance and scheduling problem -- Chapter 6: A new evolutionary optimization method based on center of mass -- Chapter 7: Adaptive artificial physics optimization algorithm with pd controller -- Chapter 8: Nsga-ii based decision-making in fuzzy multi-objective optimization of system reliability -- Chapter 9: Ga based task scheduling algorithm for efficient utilization of available resources in computational grid -- Chapter 10: Statistical feature analysis of thermal images from electrical equipment -- Chapter 11: Performance of sine-cosine algorithm on large-scale optimization problems -- Chapter 12: Necessary and sufficient optimality conditions for fractional interval valued optimization problems -- Chapter 13: Application of constrained spider monkey optimization to solve portfolio optimization problem -- Chapter 14: Optimal configuration selection in reconfigurable manufacturing system -- Chapter 15: A comparative study of regularized long wave equations using collocation method with cubic b-spline -- Chapter 16: An enhanced fractal dimension based feature extraction for thermal face recognition -- Chapter 17: Seismic analysis of multistoried building with optimized damper properties -- Chapter 18: Effect of upper body motion on biped robot stability -- Chapter 19: Ant colony algorithm for routing alternate fuel vehicles in multi-depot vehicle routing problem -- Chapter 20: Semidefinite approximation of closed convex set. |
Record Nr. | UNINA-9910350214103321 |
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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Logistics, Supply Chain and Financial Predictive Analytics [[electronic resource] ] : Theory and Practices / / edited by Kusum Deep, Madhu Jain, Said Salhi |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (VII, 254 p. 54 illus., 38 illus. in color.) |
Disciplina | 658.4038 |
Collana | Asset Analytics, Performance and Safety Management |
Soggetto topico |
Big data
Business logistics Finance—Mathematics Big Data/Analytics Supply Chain Management Logistics Financial Mathematics |
ISBN | 981-13-0872-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1: Co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing -- Chapter 2: Determination of initial basic feasible solution for transportation problems using supply demand reparation method and continuous allocation method -- Chapter 3: Comparison study on exponential smoothing and arima model for the fuel price -- Chapter 4: An optimal policy for weibull distributed deteriorating items varying with ramp type demand rate and shortages -- Chapter 5: Inventory model with shortages and deterioration for three different demand rates -- Chapter 6: Outlier labeling methods for medical data -- Chapter 7: Goal programming model to budgetary allocation in garbage disposal plant -- Chapter 8: A validated model of a fault-tolerant system -- Chapter 9: Formation and designing of “least cost ration formulation application of cattle” using excel vba -- Chapter 10: New stable numerical inversion of generalized abel integral equation -- Chapter 11: Empirical analysis of probabilistic bounds -- Chapter 12: A graph-theoretical approach for comparison between the pair of allied ragas bhupali and deshkar of north indian classical music -- Chapter 13: A general class of tests for testing homogeneity of location parameters against ordered alternatives -- Chapter 14: Modelling of male age at marriage: evidences from western region of uttar pradesh (india) -- Chapter 15: Copula functions and applications in engineering -- Chapter 16: A preservation technology model for deteriorating items with advertisement dependent demand and trade credit -- Chapter 17: Time series model for stock price forecasting in india -- Chapter 18: asset pricing through capital market curve -- Chapter 19: Non-dominated sorting water cycle algorithm for optimal selection of cardinality constrained portfolio problem -- Chapter 20: Tqm indicators implemented by teachers of the primary school. |
Record Nr. | UNINA-9910350214803321 |
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models [[electronic resource] ] : Theory and Applications / / edited by Kusum Deep, Madhu Jain, Said Salhi |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (282 pages) |
Disciplina | 519.82 |
Collana | Asset Analytics, Performance and Safety Management |
Soggetto topico |
Big data
Operations research System safety Big Data/Analytics Operations Research/Decision Theory Quality Control, Reliability, Safety and Risk |
ISBN | 981-13-0857-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1: Mehar methods to solve intuitionistic fuzzy linear programming problems with trapezoidal intuitionistic fuzzy numbers -- Chapter 2: Solving lp models for multi-objective matrix games with i-fuzzy goals -- Chapter 3: Fuzzy integrated super-efficiency slack based measure model -- Chapter 4: Prioritizing of factors affecting the adoption of mobile financial services in emerging markets- a fuzzy ahp approach -- Chapter 5: Design of reliability single sampling plan by attributes based on exponentiated exponential distribution -- Chapter 6: Availability prediction of repairable fault tolerant system with imperfect coverage, reboot and common cause failure -- Chapter 7: Software reliability growth model in distributed environment subject to debugging time lag -- Chapter 8: Imperfect software reliability growth model using delay in fault correction -- Chapter 9: Busy period analysis of gi/g/c and map/g/c queues -- Chapter 10: F-policy for m/m/1/k retrial queueing model with state dependent rates -- Chapter 11: A time shared queue with additional server and nopassing customers -- Chapter 12: The effect of vacation interruptions policy on the queueing system with cost optimization -- Chapter 13: Balking strategies for a working vacation priority queuing system with two classes of customers -- Chapter 14: Mx /g/1 queue with optional service and server breakdowns -- Chapter 15: Performance analysis of series queue with customers blocking -- Chapter 16: Markovian multiserver queue with reneging and provision of additional removable servers -- Chapter 17: Analysis of queues with impatient clients: an application to online shopping -- Chapter 18: Designing bulk arrival queue model to an interdependent communication system with fuzzy parameters -- Chapter 19: Transient analysis of markov feedback queue with working vacation and discouragement -- Chapter 20: Transient and steady-state behavior of a two-heterogeneous servers queuing system with balking and retention of reneging customers. |
Record Nr. | UNINA-9910350214603321 |
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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