Livestock Ration Formulation for Dairy Cattle and Buffalo provides an interdisciplinary, integrative perspective and optimization on dairy cattle feed formulation problem solving. It helps dairy farmers by introducing them the right frequency and right amount of balanced diet to be fed to cattle’s and buffaloes at different body condition so that their feeding cost should be decreased and there should be increase in income for dairy farmers, as they don’t have enough knowledge of feeding practice. It helps animal nutritionist to work for dairy farmers which have very limited feed resources to fulfil nutrients requirement in terms of crude protein (CP), total digestible nutrient (TDN), calcium (Ca) and phosphorus (P) by developing a software programme to plan a balanced low budget diet.
Author(s): Ravinder Singh Kuntal, Radha Gupta, D. Rajendran, Vishal Patil
Publisher: CRC Press
Year: 2022
Language: English
Pages: 138
City: Boca Raton
Cover
Half Title
Title
Copyright
Dedication
Contents
List of Tables
List of Figures
Preface
Acknowledgments
Authors
List of Abbreviations
1. Introduction to Animal Nutrition
1.1 Operational Research
1.2 Animal Nutrition
1.3 Essential Nutrients
1.3.1 Energy
1.3.2 Protein
1.3.3 Minerals
1.4 Classification of Feedstuffs
1.5 Application Area
2. Review of Literature
2.1 Introduction
2.2 Linear Programming in Ration Formulation
2.2.1 Linear Programming Based Software
2.2.2 Limitations of Linear Programming in Ration Formulation
2.2.3 Overcoming the Limitations of Linear Programming
2.3 Nonlinear Programming
2.4 Goal Programming
2.5 Genetic Algorithm
3. Tools and Techniques
3.1 Computation of LP Model Using MS-Excel Based Solver
3.1.1 Simplex LP Method in MS-Excel Solver
3.1.2 GRG Nonlinear in MS-Excel Solver
3.1.3 Evolutionary Algorithm in MS-Excel Solver
3.1.4 MATLAB (Matrix-Laboratory)
3.1.4.1 Inputs of Genetic Algorithm
3.2 Data Handling and Nutrient Bound Calculator
4. Binary Coded Genetic Algorithm to Solve Ration Formulation Problem
4.1 Introduction
4.2 Linear and Nonlinear Programming Model for Animal Feed Formulation (Test Problem-1)
4.2.1 Linear Programming Formulation
4.2.2 Nonlinear Programming Formulation
4.2.3 Extended Work Using Genetic Algorithms
4.2.4 Solution of Nonlinear Programming Model by Genetic Algorithm
4.2.5 Graphical Results
4.3 Goal Programming Model (Test Problem-2)
4.3.1 Formulation of the Nonlinear Goal Programming Problem
4.3.2 Graphical Results
4.3.3 Conclusion
5. Least Cost Feed Formulation for Dairy Cattle During Pregnancy by Using Real Coded Genetic Algorithm: An Application
5.1 Introduction
5.1.1 Data Collection and Methodology
5.1.1.1 LP Model for Cattle-1
5.1.1.2 LP Model for Cattle-2
5.1.1.3 LP Model for Cattle-3
5.2 Implementation
5.2.1 Results and Discussions
5.2.2 Conclusion
5.3 A Goal Programming Approach to Ration Formulation Problem for Indian Dairy Cows
5.3.1 Goal Programming Approach
5.3.1.1 GP Model-1
5.3.1.2 GP Model-2
5.3.1.3 GP Model-3
5.3.2 Real Coded Genetic Algorithm with Hybrid Function
5.3.3 Results
5.3.4 Discussion
5.3.5 Conclusion
6. Study of Real Coded Hybrid Genetic Algorithm to Find Least Cost Ration for Non-Pregnant Dairy Buffaloes
6.1 Introduction
6.2 Data Collection and Data Handling
6.3 Problem Description
6.3.1 Linear Programming Model
6.3.2 Goal Programming Model-1
6.3.3 Goal Programming Model-2
6.3.4 Goal Programming Model-3 (Auxiliary Approach)
6.4 Development of Real Coded Hybrid Genetic Algorithm
6.4.1 Objective Function, Decision Variables, Representation of Plots
6.4.2 Crossover, Selection, Mutation and Elitism Operators
6.4.3 Global vs. Local Minima
6.5 Results on Dry Matter and As-Fresh Basis
6.6 Discussion
6.7 Conclusion
7. Conclusion
References
Index
