Solving Three-objective Optimization Problems Using Evolutionary Dynamic Weighted Aggregation: Results and Analysis
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چکیده
In this paper, evolutionary dynamic weighted aggregation methods are generalized to deal with three-objective optimization problems. Simulation results from two test problems show that the performance is quite satisfying. To take a closer look at the characteristics of the Pareto-optimal solutions in the parameter space, piecewise linear models are used to approximate the definition function in the parameter space that defines a Pareto-optimal front or the boundary of a Pareto-optimal surface. It is shown that such analyses are very helpful for recovering the true Pareto front.
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Solving Three-Objective Optimization Problems Using Evolutionary Dynamic Weighted Aggregation: Results and Analysis
The main purposes of this paper is twofold. First, the evolutionary dynamic weighted aggregation (EDWA) [1] approaches are extended to the optimization of three-objective problems. Fig. 1 shows two example patterns for weight change. Through two three-objective test problems [2], the methods have shown to be effective. Theoretical analyses reveal that the success of the weighted aggregation bas...
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