Proposes a scalable benchmark for DMOPs with changing objective counts by dynamically selecting subsets from fixed Minus-DTLZ and Minus-WFG problems to isolate the effect of objective number dynamics.
In: 2007 IEEE Congress on Evolutionary Computation
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A Scalable Benchmark Test Suite for Dynamic Multi-Objective Optimization with a Changing Number of Objectives
Proposes a scalable benchmark for DMOPs with changing objective counts by dynamically selecting subsets from fixed Minus-DTLZ and Minus-WFG problems to isolate the effect of objective number dynamics.