ENGINEERING DESIGN OPTIMIZATION USING A SWARM WITH AN INTELLIGENT INFORMATION SHARING AMONG INDIVIDUALS

By Tapabrata Ray, Pankaj Saini. 2001

348 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7aaead0b87023d54df709862ad6403ec645dc48c

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In Civil and Structural Engineering

In Computational Theory and Mathematics

In Statistics and Probability

Citations in the corpus

Society and civilization: An optimization algorithm based on the simulation of social behavior (2003, methodology): “Theresults of Rao [29], Li and Papalambros [30], and Azarm and Li [32] violate constraints presented in [22] and [28].”
Bat algorithm: a novel approach for global engineering optimization (2012, methodology): “Table VI presents the best solutions obtained by BA and those reported by Ray and Saini (2001) and Tsai (2005).”
Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems (2011, methodology): “Table 13 presents the solutions obtained by CS and those reported by Ray and Saini [33] and Tsai [34].”
Global optimization of nonlinear fractional programming problems in engineering design (2005, methodology): “The optimization problem of a spring design presented in Ray and Saini (2001) consists of minimizing the weight of a tension spring subject to constraints on minimum deflection, shear stress, surge frequency, and limits on the outside diameter and design variables.”
Prairie Dog Optimization Algorithm (2022, neutral): “19 [75].”
Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems (2010, background): “(13) 6059.7208 Ray and Saini (2001) and Ray and Liew (2003) also solved this problem using other optimization methods.”
Sequential Approximate Optimization using Radial Basis Function network for engineering optimization (2011, background): “Many researchers have used this as benchmark problem in the structural optimization (Coello Coello 2000; Ray and Saini 2001 ; H u et al.2003).”
Differential evolution with dynamic stochastic selection for constrained optimization (2008, methodology): “DSS-MDE Ray and Liew [22] Ray and Saini [ 29 ] Hernendez [33]”