Abstract:How to evaluate solutions effectively is a key to solving many-objective optimization problem. An inverted generation distance(IGD+S) indicator is proposed based on IGD indicator, incorporating weak dominance of IGD+ indicator and employing the concept of non-contributing individuals. Convergence and diversity of solution set are evaluated comprehensively. IGD+S indicator is embedded in the framework of evolutionary algorithms, and a multi-objective evolutionary algorithm based on IGD+S indicator is presented. In the process of environmental selection, excellent solutions are selected according to enhanced IGD+S indicator. Experimental results demonstrate that the proposed algorithm is competitive in DTLZ problems and WFG problems.
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