Optimization in Sample surveys and System Reliability
Mathematical Programming Approach in Reliability and Multivariate Sampling Problems
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Allocation problems arising in various fields with probabilistic parameters have been considered in the first two chapters. The problems are solved by first deriving the deterministic equivalents and then by using a suitable convex programming algorithm or by using the Chebyshev approximation technique. In many industrial environments, systems are required to perform a sequence of operations with finite breaks between each operation. During these breaks, some of the systems components are found deteriorated. It may be advantageous to perform repair on some of them and replace the others by new...
Allocation problems arising in various fields with probabilistic parameters have been considered in the first two chapters. The problems are solved by first deriving the deterministic equivalents and then by using a suitable convex programming algorithm or by using the Chebyshev approximation technique. In many industrial environments, systems are required to perform a sequence of operations with finite breaks between each operation. During these breaks, some of the systems components are found deteriorated. It may be advantageous to perform repair on some of them and replace the others by new once. A method is developed in chapter IV to find the optimum number of repairable and replaceable components so as to maximize the system reliability with limitations on maintenance resources. In the last chapter, I consider the recruitment of persons to various jobs according to required talents which is important in the growth of an organization. The groups are formed using cluster analysis. Assuming the job service time to follow Gamma distribution, a method is developed for determining the groups optionally based on their efficiency in completion of the assignment.
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