A tutorial on learning with Bayesian networks
Learning in graphical models
Communications of the ACM
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
A dynamic distribution model for combat logistics
Computers and Operations Research
Application notes: MEBRA: multiobjective evolutionary-based risk assessment
IEEE Computational Intelligence Magazine
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This paper proposes a framework, that incorporates evolutionary computation and wargame simulation, to investigate the role of information networks in organizing efficient supply chains for military logistics. Under the proposed framework, evolutionary computation is used to evolve the information networks, which are subsequently evaluated by playing simulation wargames. Through a series of simulation studies, in which various supply scenarios have been simulated, we have found that information networks play a substantial role in efficient demand estimation. Depending on the level of information uncertainty, i.e. the hostile force strength distribution, different topological characteristics of the information networks, i.e. different information relationships between supply nodes, are favored. The objective of the paper is to discover the fundamental principles for information networks and their interaction with supply chains. These principles are significant for new and/or future military concepts such as network centric warfare. We believe that the proposal of the framework and the discovery of those emergent topological characteristics would significantly contribute to the organizing of efficient supply chains for military logistic operations.