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A line up evolutionary algorithm for solving nonlinear constrained optimization problems
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AI
DOI：10.1016/j.cor.2003.11.015.png)
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Abstract
En 中文
In this work a complete framework is presented for solving nonlinear constrained optimization problems. based on the line-up differential evolution (LUDE) algorithm which is proposed for solving unconstrained problems. Linear and/or nonlinear constraints are handled by embodying them in an augmented Lagrangian function, where the penalty parameters and multipliers are adapted as the execution of the algorithm proceeds. The LUDE algorithm maintains a population of solutions.. which is continuously improved as it thrives From generation to generation. In each generation the solutions are lined up according to the corresponding objective function values. The position's in the line are very important.. since they determine to What extent the crossover and the mutation operators are applied to each particular solution. The efficiency of the proposed methodoloy is illustrated by solving numerous unconstrained and constrained optimization problems and comparing it With other optimization techniques that can be found in the literature. (C) 2003 Elsevier Ltd. All rights reserved.
Keywords:
evolutionary algorithms
constrained optimization
penalty adaptation
nonlinear programming
Journal
C
IF:
4.3
Papers:
6.5K
Citations:
1.8W
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