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An improved differential evolution algorithm for optimization including linear equality constraints
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AI
DOI：10.1007/s12293-018-0268-3.png)
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A differential evolution algorithm (DE) is proposed to exactly satisfy the linear equality constraints present in a continuous optimization problem that may also include additional non-linear equality and inequality constraints. The proposed DE technique, denoted by DELEqC-II, is an extension of a previous method developed by the authors. In contrast to the previous approach, it uses both mutation and crossover strategies that maintain feasibility with respect to the linear equality constraints. Also, a procedure to correct numerical errors detected in the previous approach was incorporated in DELEqC-II. In the numerical experiments, scalable test-problems with linear equality constraints are used to analyze the performance of the new proposal.
Keyword:
Constraint handling
Linear equality constraints
Differential evolution
期刊
IF:
2.3
论文数:
453
被引数:
718
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