Integrating genetic algorithms and interactive simulations for airbase logistics planning

Schneider, Nicole L.; Narayanan, S.; Patel, Chintan

doi:10.1007/978-1-4471-0509-1_26

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…Simulation modeling is also quite adept at examining future concepts or even finding best solutions in complex planning environments, such as aircraft maintenance. Schneider et al 21 examined how well a genetic algorithm might interface with a discrete event simulation model to find solutions to problems associated with flight line repair processes. In the aircraft maintenance world, one such future concept is failure anticipation, or what is often referred to as prognostics.…”

Section: Related Logistics Research In Modeling and Simulationmentioning

confidence: 99%

Using simulation to analyze the maintenance architecture for a USAF weapon system

Garza¹,

Hill

Mattioda

2012

SIMULATION

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The United States Air Force (USAF) is investigating the use of three levels of repair with its aircraft maintenance managerial structure. This study provides an initial look at the effect of maintenance resource collaboration among maintenance locations and the use of a centralized repair facility focusing on a critical line replacement unit for a major USAF weapon system. Maintenance data for prior year maintenance experiences are collected, fit into appropriate probability distributions and implemented in a discrete event simulation model. This model is then used within an experimental design framework to examine the potential impact of organizational changes to the USAF hierarchical maintenance structure.

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Section: Related Logistics Research In Modeling and Simulationmentioning

confidence: 99%

Using simulation to analyze the maintenance architecture for a USAF weapon system

Garza¹,

Hill

Mattioda

2012

SIMULATION

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“…Soft Computing is the fusion of methodologies that were designed to model and enable solutions to real world problems, which are too difficult to model, mathematically. Soft computing is a consortium of methodologies that works synergistically and provides, in one form or another, flexible information processing capability for handling real-life ambiguous situations [1] [2]. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning and partial truth in order to achieve robustness and low-cost solutions [3].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Three Tank Process using Soft Computing Techniques

Srinivas¹,

K²

2015

International Journal of Innovative Research in Electrical, Ele

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Most of the process systems exhibits non-linear behaviour, so conventional controllers are not able to provide accurate data. At present, various soft computing techniques are used to overcome imprecision and uncertainty effects of conventional controllers. Various soft computing techniques like fuzzy logic, genetic algorithm and particle swarm optimization have been suggested for optimum setting of PID controller parameters. In this paper, the performance of all the three soft computing techniques is compared for three tank level process control system. This comparative study is carried out for set point tracking of three tank level process using MATLAB/ SIMULINK. The simulation results shows that tuning the PID controller using PSO provides fast and stable system with low overshoot.

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