By A. Kaveh, V.R. Mahdavi
This booklet provides and applies a unique effective meta-heuristic optimization set of rules referred to as Colliding our bodies Optimization (CBO) for numerous optimization difficulties. the 1st a part of the ebook introduces the ideas and techniques concerned, whereas the second one is dedicated to the functions. even though optimum layout of buildings is the most subject, chapters on optimum research and functions in constructional administration also are included.
This set of rules is predicated on one-dimensional collisions among our bodies, with each one agent resolution being regarded as an item or physique with mass. After a collision of 2 relocating our bodies with certain plenty and velocities, those our bodies back separate, with new velocities. This collision reasons the brokers to maneuver towards higher positions within the seek space.
The major set of rules (CBO) is internally parameter self sustaining, environment it except formerly constructed meta-heuristics. This set of rules is stronger (ECBO) for extra effective purposes within the optimum layout of structures.
The algorithms are carried out in average machine programming languages (MATLAB and C++) and major codes are supplied for ease of use.
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Additional info for Colliding Bodies Optimization: Extensions and Applications
It should be noted that the no internal parameter tuning is needed in the proposed algorithm. References 1. Kaveh A, Mahdavai VR (2014) Colliding bodies optimization: a novel meta-heuristic method. Comput Struct 139:18–27 2. Kaveh A, Mahdavi VR (2015) Two-dimensional colliding bodies algorithm for optimal design of truss structures. Adv Eng Softw 83:70–79 3. Tolman RC (1979) The principles of statistical mechanics. Clarendon Press, Oxford (Reissued) 4. Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search.
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In the 2D-CBO, bodies or agents move toward to the saved best particles and collide to them to promote the exploitation ability of the CBO. A comparative study of 2D-CBO algorithm on two constrained functions is presented. The results of applying examples clearly indicate that 2D-CBO is competitive and even outperforms most of the standard algorithm. 3 Two-Dimensional Colliding Bodies Optimization 37 population size on all examples. The comparison of the function evaluation shows that 2D-CBO requires less evaluation and population size than the standard CBO algorithm on some of the selected benchmark test problems.
Colliding Bodies Optimization: Extensions and Applications by A. Kaveh, V.R. Mahdavi