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Dolphin Pod Optimization

A Nature-Inspired Deterministic Algorithm for Simulation-Based Design
  • Andrea SeraniEmail author
  • Matteo Diez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10710)

Abstract

A novel nature-inspired, deterministic, global, and derivative-free optimization method, namely the dolphin pod optimization (DPO), is presented for solving simulation-based design optimization problems with costly objective functions. DPO is formulated for unconstrained single-objective minimization and based on a simplified social model of a dolphin pod in search for food. A parametric analysis is conducted to identify the most promising DPO setup, using 100 analytical benchmark functions and three performance criteria, varying pod size and initialization, coefficient set, and box-constraint method, resulting in more than 140,000 optimization runs. The most promising setup is compared with deterministic particle swarm optimization, central force optimization, and DIviding RECTangles and finally applied to the optimization of a destroyer hull form for reduced resistance and improved seakeeping.

Keywords

Dolphin pod optimization Deterministic optimization Global optimization Derivative-free optimization 

Notes

Acknowledgements

The work is supported by ONRG, NICOP grant N62909-15-1-2016, under the administration of Dr Woei-Min Lin, Dr. Salahuddin Ahmed, and Dr. Ki-Han Kim, and by the Italian Flagship Project RITMARE.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.CNR-INSEAN, National Research Council–Marine Technology Research InstituteRomeItaly

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