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Budget Optimization And Allocation An Evolutionary Computing Based Model 1st Edition Sudip Kumar Sahana Moumita Khowas Keshav Sinha

  • SKU: BELL-51638150
Budget Optimization And Allocation An Evolutionary Computing Based Model 1st Edition Sudip Kumar Sahana Moumita Khowas Keshav Sinha
$ 31.00 $ 45.00 (-31%)

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Budget Optimization And Allocation An Evolutionary Computing Based Model 1st Edition Sudip Kumar Sahana Moumita Khowas Keshav Sinha instant download after payment.

Publisher: Bentham Science Publishers
File Extension: PDF
File size: 4.68 MB
Pages: 164
Author: Sudip Kumar Sahana; Moumita Khowas; Keshav Sinha
ISBN: 9781681087078, 1681087073
Language: English
Year: 2018
Edition: 1

Product desciption

Budget Optimization And Allocation An Evolutionary Computing Based Model 1st Edition Sudip Kumar Sahana Moumita Khowas Keshav Sinha by Sudip Kumar Sahana; Moumita Khowas; Keshav Sinha 9781681087078, 1681087073 instant download after payment.

Budget Optimization and Allocation: An Evolutionary Computing Based Model is a guide for computer programmers for writing algorithms for efficient and effective budgeting. It provides a balance of theory and practice. Chapters explain evolutionary computational techniques (genetic algorithms) and compare these techniques with traditional approaches to budget allocation. A case study on the complex and broad problem of union budgeting of India is presented. The macro and micro economic issues specific to the case discussed, with the growth rate being the final aim of the budget exercise. The authors also present a comparison of the budget allocation practices of different countries, consistent with other factors such as their local economy, culture, population, etc. The use of evolutionary computation to tackle incremental budgeting is also presented. Readers will be able to understand the synergies of modern computational techniques with tried and tested budgeting models. Budget Optimization and Allocation: An Evolutionary Computing Based Model is a useful reference for graduate students, business enterprise programmers, and evolutionary computing/AI researchers who seek to understand new methods of budgeting.

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