A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Peloton Dynamics Optimization: Algorithm for Discrete Structural Optimization
A discrete variable optimization algorithm is presented based on peloton dynamics that occur during bicycle racing. Peloton dynamics are mainly attributable to the physical capacity of cyclists, energy saving by the coupling effects of drafting, and the capacity for cyclists to pass others. It also includes cooperating with other cyclists by changing positions inside the peloton, competitors’ positions, and their relative energy levels. The algorithm’s performance is tested on nine discrete benchmark truss structures subjected to multiple loading conditions. The performance of the peloton dynamics optimization (PDO) algorithm is compared with other optimization algorithms based on the success rate (ability to find the best solution) and computational effort (number of structural analyses required). Other metaheuristic methods generally consist of different components, and these components have several parameters that need to be set manually. As a result, it is not uncommon that these parameters need to be tuned to just the right values to obtain better results and are often specific to the problem to be solved. For the present algorithm, only two parameters are needed: the number of cyclists (solutions) and the maximum number of iterations. Results demonstrate that the performance of the PDO algorithm in terms of finding near optimum solutions and convergence behavior is comparable or better than various alternative optimization methods but with less user-specific parameter settings.
Peloton Dynamics Optimization: Algorithm for Discrete Structural Optimization
A discrete variable optimization algorithm is presented based on peloton dynamics that occur during bicycle racing. Peloton dynamics are mainly attributable to the physical capacity of cyclists, energy saving by the coupling effects of drafting, and the capacity for cyclists to pass others. It also includes cooperating with other cyclists by changing positions inside the peloton, competitors’ positions, and their relative energy levels. The algorithm’s performance is tested on nine discrete benchmark truss structures subjected to multiple loading conditions. The performance of the peloton dynamics optimization (PDO) algorithm is compared with other optimization algorithms based on the success rate (ability to find the best solution) and computational effort (number of structural analyses required). Other metaheuristic methods generally consist of different components, and these components have several parameters that need to be set manually. As a result, it is not uncommon that these parameters need to be tuned to just the right values to obtain better results and are often specific to the problem to be solved. For the present algorithm, only two parameters are needed: the number of cyclists (solutions) and the maximum number of iterations. Results demonstrate that the performance of the PDO algorithm in terms of finding near optimum solutions and convergence behavior is comparable or better than various alternative optimization methods but with less user-specific parameter settings.
Peloton Dynamics Optimization: Algorithm for Discrete Structural Optimization
Poitras, Gérard Jacques (author) / Cormier, Gabriel (author) / Nabolle, Armel Stanislas (author)
2021-08-07
Article (Journal)
Electronic Resource
Unknown
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