Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Model Checking of Probabalistic and Nondeterministic Systems
Proceedings of the 15th Conference on Foundations of Software Technology and Theoretical Computer Science
Quantitative verification: models techniques and tools
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Probabilistic model checking of complex biological pathways
Theoretical Computer Science
Mergers & acquisitions from a to z, second edition
Mergers & acquisitions from a to z, second edition
An MTBDD-based implementation of forward reachability for probabilistic timed automata
ATVA'05 Proceedings of the Third international conference on Automated Technology for Verification and Analysis
PRISM: a tool for automatic verification of probabilistic systems
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
A multi-criteria optimization framework for industrial shop scheduling using fuzzy set theory
Integrated Computer-Aided Engineering
Optimising operational costs using Soft Computing techniques
Integrated Computer-Aided Engineering
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Supply chain strategy has become an important factor that dictates the successes of companies in today's competitive world. Nowadays more and more companies are tapping into the mergers and acquisitions in hope of getting the synergistic gain in supply chain consolidation. In this paper we use a model-checking-based approach to study the impact of different consolidation strategies on risks in supply chains and compare their capacity of risk reduction. We model stochastic behaviors of supply chains using an extension of Markov Decision Processes and translate the goal of risk analysis into a temporal logic. We then apply probabilistic model checking to analyzing risks inherent in a stochastic supply chain model. In our computational study, we consider three different consolidation strategies initially modeled in [18] and compare their capability of risk reduction in a generic three-echelon supply chain network. Our results reveal some key factors that improve the benefit of supply chain consolidation on risk reduction.