<span>This book presents theory and applications of recently introduced butterfly optimization algorithm (BOA). It also highlights hybridization process in the basic structure of BOA with in-depth analysis of complexity. This book also describes the constraint handling process. The newly introduced
Butterfly Optimization Algorithm: Theory and Engineering Applications (SpringerBriefs in Applied Sciences and Technology)
✍ Scribed by Tarun Kumar Sharma, Om Prakash Verma
- Publisher
- Springer
- Year
- 2022
- Tongue
- English
- Leaves
- 94
- Edition
- 1st ed. 2022
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
This book presents theory and applications of recently introduced butterfly optimization algorithm (BOA). It also highlights hybridization process in the basic structure of BOA with in-depth analysis of complexity. This book also describes the constraint handling process. The newly introduced variant is implemented and validated on a set of linear and nonlinear real works problems of engineering and pulp and paper industry. The simulated results are compared with most of the basic algorithms. Comparative and nonparametric statistical result analysis illustrates the efficacy of the algorithm.
✦ Table of Contents
Preface
Contents
About the Authors
1 Butterfly Optimization Algorithm
1.1 Introduction
1.2 Butterfly Optimization Algorithm (BOA) and Related Literature
1.3 Related Work—BOA
1.4 Conclusions and Next Study
References
2 Differential Butterfly Optimization Algorithm—A Hybrid Variant
2.1 Proposed Algorithm: DBOA
2.1.1 Differential Evolution (DE)
2.1.2 Concept of Bidirectional Search
2.2 Experimental Settings, Constrained Handling and Complexity of DBOA
2.2.1 Parameter Settings
2.2.2 Computational Analysis and Complexity of DBOA
2.2.3 Constraint Handling
2.3 Conclusions and Future Study
References
3 Application of DBOA in Structural Engineering Design Problems
3.1 Introduction
3.2 Test Bed
3.2.1 Unconstrained Benchmark Problems [2]
3.2.2 Engineering Design Problems
3.2.3 Himmelblau’s Nonlinear Constrained Optimization Problem [12]
3.3 Result Discussions and Analysis
3.3.1 Comparative Simulated Results and Analysis on Unconstrained Benchmark Functions
3.3.2 Experimental Result of Engineering Design Problems
3.3.3 Non Linear Constrained Optimization Problems by Himmelblau’s [12]
3.4 Conclusions with Future Scope
References
4 Application of DBOA in Pulp and Paper Process Optimization
4.1 Introduction
4.2 Optimization Problem in Pulp and Paper Manufacturing Process
4.2.1 Kraft Pulping
4.2.2 Load Allocation to Boilers
4.2.3 Drying Process
4.2.4 Trim Loss
4.3 Result Analysis
4.4 Conclusions
References
5 Conclusion and Future Directions
5.1 Conclusion of the Work
5.2 Future Directions
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