Optimization in Reliability Engineering using Natural Computing

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Nadia Nedjah, Leandro dos Santos Coelho, Luiza de Macedo Mourelle (Eds.)

The design of modern engineering systems entails the consideration of a good trade-off between the several targets requirements to be satisfied along the system life such as high reliability, low redundancy, and low operational costs. These aspects are often in conflict with one another, hence a compromise solution has to be sought. The availability and reliability are good evaluations of a system performance. Their values depend on the system structure as well as on the component availability and reliability. These values decrease as the component ages increase, i.e. their serving times are influenced by their interactions with each others, applied maintenance policy and their environments.

In this context, the research field called "reliability" has gained an even greater concern in recent years, because high-tech industrial processes with increasing levels of sophistication exist in today's most engineering systems . Based on enhancing component reliability and providing redundancy while considering the trade-off between system performance and resources, optimal reliability design that aims at determining an optimal system-level configuration has long been an important topic in reliability engineering. It is important for design engineers to maximize a system's reliability subject to several constraints, such as cost, weight, and volume. System reliability problems can often be formulated as nonlinear integer programming or mixed-integer problems which aim to maximize system reliability subject to several constraints. In general terms, the redundancy-allocation problem involves selection of components and levels-of redundancy to maximize some defined objective function.

During the past two decades, numerous reliability design techniques have been proposed. Recently, the utilization of natural computing approaches, such as fuzzy systems, artificial neural networks, swarm intelligence, immune systems, fractal geometry, evolutionary computation, DNA computing, artificial life, and quantum computing has attracted considerable attention from the research community.

For this book, we seek original contributions and recent advances on any aspect related to optimization in the reliability engineering field using emergent natural computing methodologies. Applications of natural computing methodologies in reliability engineering to real-world system are welcome. The topics of interest include, but not limited to:

Self-adaptive natural computing approaches in reliability optimization Intelligent systems and bio-inspired optimization approaches in reliability optimization of multistate, series-parallel, and complex systems Natural computing in fault-tolerance mechanism linked to reliability engineering Natural computing in choice of redundacy strategies Natural computing to improve of the system performance in reliability systems Natural computing algorithms for multi-objective optimization in reliability Applications of natural computing in reliability problems

The time schedule for this publication is as follows:

1. Manuscript submission: May 28, 2010
2. Authors Notification: August 30, 2010
3. Camera-ready submission: September 25, 2010