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M. Li and X. Yao, What weights work for you? Adapting weights for any Pareto front shape in decomposition-based evolutionary multi-objective optimisation. Evolutionary Computation, 28(2), 2020. [PDF] [C code]
M. Li and X. Yao, What weights work for you? Adapting weights for any Pareto front shape in decomposition-based evolutionary multi-objective optimisation. Evolutionary Computation, 28(2), 2020. [PDF] [C code]
Idea:
Idea:
Updating the weights of the evolutionary population by contrasting it with a well-maintained archive set of non-dominated solutions
Updating the weights of the evolutionary population by contrasting it with a well-maintained archive set of non-dominated solutions
Results:
Results:
Solution sets obtained by AdaW and other 4 decomposition-based algorithms on problems with various Pareto front shapes.
Solution sets obtained by AdaW and other 4 decomposition-based algorithms on problems with various Pareto front shapes.
On the inverted simplex Pareto front (IDTLZ1)
On the inverted simplex Pareto front (IDTLZ1)
On the disconnected Pareto front (DTLZ7)
On the disconnected Pareto front (DTLZ7)
On the degenerate Pareto front (DTLZ5)
On the degenerate Pareto front (DTLZ5)
On the scaled Pareto front (SCH2)
On the scaled Pareto front (SCH2)
On the high-dimensional Pareto front (10-objective IDTLZ1)
On the high-dimensional Pareto front (10-objective IDTLZ1)
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