A Note on Optimization Problems of a Parallel System With a Random Number of Units

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2017

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World Scientific Publ Co Pte Ltd

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Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

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Abstract

This paper is concerned with a parallel system that have a random number of units. The distribution of the number of units is assumed to follow a power series class of distributions which contains well-known distributions such as modified or truncated Poisson, geometric, and logarithmic distributions. Optimal number of units and replacement time for the system which minimizes the mean cost rate are computed. The results extend the results in the literature from Poisson distribution to a wider class of distributions.

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Eryilmaz, Serkan/0000-0002-2108-1781

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Optimal replacement time, parallel system, reliability

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10

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24

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5

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