Hybrid Simulation/Analytic Models for Military Supply Chain Performance Analysis
Abstract
This research is intended to extend the knowledge base concerning logistical network modeling and design. Basic research techniques were developed to begin to model logistical networks within a hybrid simulation/analytic framework. The first step in this process is to develop robust approximations for portions of large-scale simulation models. This research examined the novel idea of utilizing neural networks as a meta-modeling technique to replace specific aspects of a simulation. This work started with the replacement of queueing stations within a logistics network. Any logistics network can be formulated as a network of material flowing through processes requiring resources. A new methodology was developed for forming approximations and improved approximators for queueing stations within a logistics network. The motivation for developing this approximation is the integration of such approximation in hybrid simulation/analytic methods for evaluating logistic networks. Future work should investigate the performance of these approximations within the larger logistical network context.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2004
- Accession Number
- ADA445893
Entities
People
- Manuel D. Rossetti
- Stephen Farris
Organizations
- University of Arkansas