Authors: Sudip Kumar Sahana, Moumita Khowas, Keshav Sinha

Budget Optimization and Allocation: An Evolutionary Computing Based Model

eBook: US $39 Special Offer (PDF + Printed Copy): US $114
Printed Copy: US $95
Library License: US $156
ISBN: 978-1-68108-708-5 (Print)
ISBN: 978-1-68108-707-8 (Online)
Year of Publication: 2018
DOI: 10.2174/97816810870781180101

Introduction

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.

Foreword

The book titled “Budget Optimization and Allocation: An Evolutionary Computing Based Model” caters to a critical need in today’s intellectual landscape, viz., the problem of budget optimization and distribution and its solution. The material covered in the book is an excellent balance of theory and practice. The techniques discussed the attempt to synergise evolutionary computation (mainly genetic algorithm) with traditional approaches to budget allocation like optimal allocation, equal allocation, etc.

The attractiveness of the book comes from the fact that it takes as a case study the complex and vast problem of union budget of India. The macro and micro issues discussed with attention to details, with the growth rate being the final aim of the budget exercise. The second attractive aspect is that the authors compare and contrast the budget allocation practices of different countries, consistent with country’s economy, culture, population, etc. The final attractiveness is the use of very modern methodologies like evolutionary computation to tackle incremental budgeting.

This book will be found useful by graduate students in their research. I congratulate the authors on taking up a very timely and relevant problem.

Dr. Pushpak Bhattacharyya
Computer Science and Engineering,
IIT Patna,
India
and
Department of Computer Science and Engineering,
IIT Bombay,
India


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