Volume 57 : 3
Liber Amicorum Dedicated to Prof. Marc Lambre
Tribute to Marc Lambrecht
Public Private Partnerships: Look before you Leap into Marriage
Mix, Time and Volume Flexibility: Valuation and Corporate Diversification
Matrix-Analytic Methods in Supply Chain Management: Recent Developments
Managing Variability in Manufacturing and Services
Combining a Quantitative Approach of Planning and Control with a Lean Approach: Reflections on a Case Study
Sales and Operations Planning Revisited: Linking Operational and Financial Performance
The Value of Multi-Echelon Models
Bullwhip in a Multi-Product Production Setting
The Return of the Bullwhip
Liber Amicorum Dedicated to Prof. Marc Lambre
Tribute to Marc Lambrecht
Public Private Partnerships: Look before you Leap into Marriage
Mix, Time and Volume Flexibility: Valuation and Corporate Diversification
Matrix-Analytic Methods in Supply Chain Management: Recent Developments
Managing Variability in Manufacturing and Services
Combining a Quantitative Approach of Planning and Control with a Lean Approach: Reflections on a Case Study
Sales and Operations Planning Revisited: Linking Operational and Financial Performance
The Value of Multi-Echelon Models
Bullwhip in a Multi-Product Production Setting
The Return of the Bullwhip
Year
2012
Volume
57
Number
3
Page
283
Language
English
Court
Reference
R.N. BOUTE e.a., “Matrix-Analytic Methods in Supply Chain Management: Recent Developments”, RBE 2012, nr. 3, 283-301
Recapitulation
Matrix-analytic methods are a popular modeling tool in a great number of fields, most notable in the analysis of telecommunication systems. Because of their ability to construct and analyze a wide class of stochastic models, they can also be applied in the analysis of complex supply chain problems where traditional analytical techniques or simulation analysis fall short. In this paper, we demonstrate the power of matrix-analytic methods in the analysis of four different supply chain problems: (1) to determine lead times in production/inventory models characterized by any arbitrary discrete (i.e., non-Poisson) demand distribution; (2) to gain insight in the upstream replenishment orders driven by (s,S) inventory policies; (3) to analyze waiting times and resource utilization in service systems that are driven by appointments (e.g., health care, legal services, administration); and (4) to determine the optimal maintenance policy/warranty in the aftermarket supply chain.