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 $125
Printed Copy: US $105
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.

Preface

This book builds up an innovative framework for budget optimization and allocation using Evolutionary Computing (Genetic Algorithm) in addition to conventional techniques (OCBA, EA) to get synergy from each technique.

Budget allocation plays a significant role in the planning, managing and controlling aspects of developmental processes of any given setup. Funds generated from revenue and taxes, funds collected from different agencies are essential conditions for economic growth in any country. For overall growth of a country, it is required to analyze the gain or output of the budgeting and line up the proper budgeting system. This book concentrates on the issues of good budgeting and a design a framework for proper budgeting. The chapters of the book divided into four parts:

Chapter 1 gives the introduction about the budget and its importance and challenges of budget allocation in the national and global economy. The author explains the pros and cons of budget allocation.

Chapter 2 deals with the various traditional approaches for budget allocation. Moreover, a subsequent number of researchers performed by different researchers on this topic. In depth, literature has been presented in this chapter to make a foundation for creating a research methodology on this subject.

Chapter 3 presents the proposed methodology and models for allocation and optimization. Here, Growth Rate is displayed as a parameter for allocation, explaining how evolutionary computing technology is used for optimization in this chapter.

Chapter 4 highlights the results and discussions of the different test cases of proposed budget optimization technique and allocation of the budget applied to the different schemes in the secondary education system in the MHRD department as a case study. The output of budget allocation is drawn and compared to the current budget technique.

This book is research oriented and side by side, it has practical implementation details of the research theme. Textbooks and reference books are available in the market, but that discusses only standard theories. This book is specialized and has a credit to give new ideas and implementation details in this field.

Dr. Sudip Kumar Sahana
Birla Institute of Technology, Mesra,
Ranchi, Jharkhand,
India

RELATED BOOKS

.Multi-Objective Optimization In Theory and Practice II: Metaheuristic Algorithms.
.Arduino and SCILAB based Projects.
.Arduino meets MATLAB: Interfacing, Programs and Simulink.