Application of a Fuzzy Feasibility Bayesian Probabilistic Estimation of supply chain backorder aging, unfilled backorders, and customer wait time using stochastic simulation with Markov blankets-Reference-Cited by-同舟云学术

Application of a Fuzzy Feasibility Bayesian Probabilistic Estimation of supply chain backorder aging, unfilled backorders, and customer wait time using stochastic simulation with Markov blankets

Published:2014-11 Issue:16 Volume:41 Page:7005-7022
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Rodger James A.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference50 articles.

1. Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach;Agarwal;European Journal of Operational Research,2006

2. Ranking state financial management: A multilevel fuzzy rule-based system;Ammar;Decision Sciences,2000

3. Determination of recovery effort for a probabilistic recovery system under various inventory control policies;Bayındıra;Omega,2006

4. A heuristic method for RCPSP with fuzzy activity times;Bhaskar;European Journal of Operational Research,2011

5. A systematic approach for supply chain conflict detection with a hierarchical Petri net extension;Blackhurst;Omega,2008

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