Tarun Kumar Sharma - Butterfly Optimization Algorithm: Theory and Engineering Applications (SpringerBriefs in Applied Sciences and Technology)

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The brief presents hybrid variant of recently introduced Butterfly Optimization Algorithm (BOA) and its applications to solve real-world engineering design problems (linear and non-linear) with constraints, along with applications in pulp and paper industry. The results are compared with basic results available in the literature for that problem. So, this brief can also be referred as a review book for solving engineering design problems. It also describes hybridization and handling processes of the constraints.

This brief would help novel readers to understand the basic structure of algorithms, process of hybridization, and handling the constraints as well as importance of parametric statistical result analysis.

In Chap. presents modifications in the basic structure of BOA to enhance its employability. BOA is enhanced by embedding differential evolution (DE)/current-to-best/1 mutation strategy of DE optimization algorithm with a concept of bidirectional search. The complexity of the newly introduced hybrid variant is also discussed along with handling constraints.

In Chap. , the performance of a newly introduced hybrid variant, DBOA, is tested and verified on 13 unconstrained benchmark problems and 8 structural engineering design optimization problems. The proposal is further validated on 5 Himmelblaus nonlinear constrained optimization problems.

In Chap. , linear, non-linear, and bilinear with integer restrictions and nonconvex optimization problems of pulp and paper making process (Kraft pulping; load allocation to boilers; pulp drying process; and a problem of trim loss) are considered and solved.

Chapter concludes the brief with future directions and scope of the work. From the experience gained during the period of this work, it seems certain that the amount of work being done on swarm optimization algorithms is going to increase continuously. Large and ever increasing number of complex optimization problems awaits new researchers entering into the field. The work done in this brief is also going to further extend.

In the end, authors would like to thank Springer Nature team, especially Mr. Aninda Bose, Executive Editor and Ms. Divya Meiyazhagan, Project Coordinator, and all the people involved directly or indirectly in completing the process of this brief.