Download e-book for iPad: Advances in Metaheuristic Algorithms for Optimal Design of by A. Kaveh

By A. Kaveh

ISBN-10: 3319055488

ISBN-13: 9783319055480

ISBN-10: 3319055496

ISBN-13: 9783319055497

This e-book provides effective metaheuristic algorithms for optimum layout of constructions. lots of those algorithms are constructed by way of the writer and his colleagues, which include Democratic Particle Swarm Optimization, Charged approach seek, Magnetic Charged approach seek, box of Forces Optimization, Dolphin Echolocation Optimization, Colliding our bodies Optimization, Ray Optimization. those are awarded including algorithms which have been constructed via different authors and feature been effectively utilized to numerous optimization difficulties. those encompass Particle Swarm Optimization, sizeable Bang-Big Crunch set of rules, Cuckoo seek Optimization, Imperialist aggressive set of rules, and Chaos Embedded Metaheuristic Algorithms. eventually a multi-objective optimization procedure is gifted to unravel large-scale structural difficulties in keeping with the Charged approach seek algorithm.

The options and algorithms provided during this publication aren't simply acceptable to optimization of skeletal constructions and finite aspect versions, yet can both be applied for optimum layout of different structures corresponding to hydraulic and electric networks.

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Additional resources for Advances in Metaheuristic Algorithms for Optimal Design of Structures

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In: Proceedings I999 ICEC, Washington, DC, 1951–1957 11. Bui LT, Soliman O, Abass HS (2007) A modified strategy for the constriction factor in particle swarm optimization. In: Randall M, Abass HS, Wiles J (eds) Lecture Notes in Artificial Intelligence 4828, pp 333–344 12. Kennedy J (2006) Swarm intelligence. In Handbook of Nature-Inspired and Innovative Computing, Springer, 187-219 13. Talbi EG (2009) Metaheuristics: from design to implementation. Wiley, UK 14. Shi Y, Eberhart RC (1998) Parameter selection in particle swarm optimization.

Math Prob Eng:11 (Article ID 607418) 57. Kaveh A, Talatahari S (2007) A discrete particle swarm ant colony optimization for design of steel frames. Asian J Civil Eng 9(6):563–575 58. Kennedy J, Eberhart RC (1997) A discrete binary version of the particle swarm algorithm. In: Proceedings of the conference on systems, man and cybernetics, Piscataway, New Jersey, pp 4104–4109 59. Chen WN, Zhang J, Chung HSH, Zhong WL, Wu WG, Shi Y (2010) A novel set-based particle swarm optimization method for discrete optimization problems.

12 is considered as the last example. This problem has been previously studied as a benchmark optimization problem with static constraints. This problem has been used as a size optimization problem with frequency constraints in [65]. Non-structural masses are attached to all free nodes as follows: 3,000 kg at node one, 500 kg at nodes 2 through 13 and 100 kg at the rest of the nodes. 11. The layout of the structure is kept unchanged during the optimization process. Hence, this is a sizing optimization problem.

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