An enhanced colliding bodies optimization and its application

2019 ◽  
Vol 53 (2) ◽  
pp. 1127-1186
Author(s):  
Debao Chen ◽  
Renquan Lu ◽  
Suwen Li ◽  
Feng Zou ◽  
Yajun Liu
Keyword(s):  
Colliding Bodies Optimization ◽  
Enhanced Colliding Bodies Optimization

scholarly journals Discrete Optimum Design of Planar Steel Curved Roof and Pitched Roof Portal Frames Using Metaheuristic Algorithms

2021 ◽  
Author(s):  
Ali Kaveh ◽  
Mohammad Iman Karimi Dastjerdi ◽  
Ataollah Zaerreza ◽  
Milad Hosseini
Keyword(s):  
Optimal Design ◽  
Optimum Design ◽  
Population Based ◽  
Colliding Bodies Optimization ◽  
Industrial Buildings ◽  
Enhanced Colliding Bodies Optimization ◽  
Teaching Learning Based Optimization ◽  
Fire Stations ◽  
Teaching Learning ◽  
Discrete Optimum

Portal frames are single-story frame buildings including columns and rafters, and their rafters can be either curved or pitched. These are used widely in the construction of industrial buildings, warehouses, gyms, fire stations, agricultural buildings, hangars, etc. The construction cost of these frames considerably depends on their weight. In the present research, the discrete optimum design of two types of portal frames including planar steel Curved Roof Frame (CRF) and Pitched Roof Frame (PRF) with tapered I-section members are presented. The optimal design aims to minimize the weight of these frame structures while satisfying some design constraints based on the requirements of ANSI/AISC 360-16 and ASCE 7-10. Four population-based metaheuristic optimization algorithms are applied to the optimal design of these frames. These algorithms consist of Teaching-Learning-Based Optimization (TLBO), Enhanced Colliding Bodies Optimization (ECBO), Shuffled Shepherd Optimization Algorithm (SSOA), and Water Strider Algorithm (WSA). Two main objectives are followed in this paper. The first one deals with comparing the optimized weight of the CRF and PRF structures with the same dimensions for height and span in two different span lengths (16.0 m and 32.0 m), and the second one is related to comparing the performance of the considered metaheuristics in the optimum design of these portal frames. The obtained results reveal that CRF is more economical than PRF in the fair comparison. Moreover, comparing the results acquired by SSOA with those of other considered metaheuristics reveals that SSOA has better performance for the optimal design of these portal frames.

Chaotic enhanced colliding bodies optimization algorithm for structural reliability analysis

2019 ◽  
Vol 23 (3) ◽  
pp. 438-453
Author(s):  
Jiaming Cheng ◽  
Wei Zhao
Keyword(s):  
Reliability Analysis ◽  
Heuristic Algorithm ◽  
Optimization Algorithm ◽  
Structural Reliability ◽  
Chaotic Maps ◽  
Optimization Approach ◽  
Structural Reliability Analysis ◽  
Colliding Bodies Optimization ◽  
Enhanced Colliding Bodies Optimization ◽  
Reliability Method

It is of extreme importance to assess the failure probability and safety level of structural system in structural design. Nowadays, many researchers presented several approaches for structural reliability analysis, such as the first-order reliability method, Monte Carlo simulation, and the meta-heuristic algorithm. The meta-heuristic algorithm is not only efficient to solve global optimization problems but also shown to be an effective tool for structural reliability analysis. A recent meta-heuristic optimization approach, enhanced colliding bodies optimization, has emerged as a relatively simple implementation with a fast convergence speed. Chaos theory is characterized by its ergodicity, pseudo-randomness, and irregularity. This article thus presents a novel approach introducing chaotic maps into the enhanced colliding bodies optimization algorithm to promote the performance of convergence, named as chaotic enhanced colliding bodies optimization algorithm. The proposed algorithm uses chaotic maps to change the generation pattern of particles and improve convergence characteristics. A procedure based on the effective use of the represented chaotic enhanced colliding bodies optimization is then applied in structural reliability analysis. A variety of numerical and structural problems are tested in this article to demonstrate that the given method actually improves the performance of enhanced colliding bodies optimization in convergence as well as the accuracy for reliability analysis compared with the other methods existing in the literature.

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