With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that a
Budget Optimization and Allocation: an Evolutionary Computing Based Model
β Scribed by Sudip Kumar Sahana; Moumita Khowas; Keshav Sinha
- Publisher
- Bentham Science Publishers
- Year
- 2018
- Tongue
- English
- Leaves
- 164
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β¦ Subjects
Mathematical optimization.
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