Optimization for Engineering Design: Algorithms and Examples

By Kalyanmoy Deb, Deb Kalyanmoy. 2004

1,227 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/48556b84dd1bf424a45d4f6acd39e29a05cc9158

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Citations in the corpus

A genetic algorithmic approach for optimization of surface roughness prediction model (2002, background): “The three stages are (a) Reproduction (b) Cross-over (c) Mutation [8,10].”
Application of soft computing techniques in machining performance prediction and optimization: a literature review (2010, background): “For a minimization process, if the second point has smaller function value, then it replaces the first point; otherwise, it replaces the first point with a probability exp(−ΔE/T) [12].”
Genetic algorithms in materials design and processing (2004, methodology): “Genetic algorithms were successfully employed to compute the configurations of L–J clusters containing up to 309 atoms,(17,18) where some finer adjustments were made using a conjugate gradient technique.(8) Figure 8 is reconstructed using data provided by Barrón et al.”
A New Particle Swarm Algorithm and Its Globally Convergent Modifications (2011, background): “3 that above 50% of the positions of particles locate within [1, 2] during iterations.”
Two-dimensional optimization of material composition of functionally graded materials using meshless analyses and a genetic algorithm (2006, background): “The penalty parameter approach possesses a few significant drawbacks, including (a) the penalty parameters must be adjusted in order to direct the search to the feasible region and obtain the optimal solution and (b) the penalty term distorts the objective function, as shown by Deb [50].”
State and parameter estimation of hydrologic models using the constrained ensemble Kalman filter (2009, background): “If the orthogonal projection is outside of a surface, the minimum distance to the boundary of the surface needs to be identified [Deb, 1995].”
Pymoo: Multi-Objective Optimization in Python (2020, background): “However, without loss of generality an objective which is supposed to be maximized, can be multiplied by −1 and be minimized [8].”
Irrigation planning using Genetic Algorithms (2004, background): “Key words: cropping pattern, genetic algorithms, irrigation planning, linear programming”
Omni-optimizer: A generic evolutionary algorithm for single and multi-objective optimization (2008, unknown): “CVðaÞ 1⁄4 XJ j1⁄41 h gjðaÞi þ XK k1⁄41 j hkðaÞj; ð4Þ where hÆi is a bracket operator [2].”
Mathematical Modeling of Li-Ion Battery Using Genetic Algorithm Approach for V2G Applications (2014, methodology): “GA imitates the process of biological evolution, including selection, crossover, and mutation based on the principle; good individuals survive and breed good individuals [31].”
Many-Objective Optimization: An Engineering Design Perspective (2005, background): “Excellent descriptions of the history of EMO may be found, for example, in [8] and [6].”