Marine Predators Algorithm for Sizing Optimization of Truss Structures with Continuous Variables

Abstract

In this study, the newly developed Marine Predators Algorithm (MPA) is formulated to minimize the weight of truss structures. MPA is a swarm-based metaheuristic algorithm inspired by the efficient foraging strategies of marine predators in oceanic environments. In order to assess the robustness of the proposed method, three normal-sized structural benchmarks (10-bar, 60-bar, and 120-bar spatial dome) and three large-scale structures (272-bar, 942-bar, and 4666-bar truss tower) were selected from the literature. Results point to the inherent strength of MPA against all state-of-the-art metaheuristic optimizers implemented so far. Moreover, for the first time in the field, a quantitative evaluation and an answer to the age-old question of the proper convergence behavior (exploration vs. exploitation balance) in the context of structural optimization is conducted. Therefore, a novel dimension-wise diversity index is adopted as a methodology to investigate each of the two schemes. It was concluded that the balance that produced the best results was about 90% exploitation and 10% exploration (on average for the entire computational process).

Improvement in Sizing Constrained Analog IC via Ts-CPD Algorithm

“…More recently, evolutionary algorithms have been successfully applied to component value selection for analog active filters [18,19], facility location problem [20], truss structures [21], and to the analog integrated circuits design as in [22], where the sizing is achieved using a Particle Swarm Optimization (PSO) algorithm implemented in MATLAB R2008a and the results verified at the end with SPICE. In [23], a CMOS differential amplifier and a two stages CMOS op-amp are optimized to occupy the minimal possible area by the circuits and to improve their performances using the gravitational search algorithm in combination with the particle swarm optimization (GSA-PSO).…”