A Cross-Reference Line Method Based Multiobjective Evolutionary Algorithm to Enhance Population Diversity

Table 2

Settings of the number of objectives, the number of decision variables, and the maximal number of generations for each test problem.

Test problem	M	D	Pareto front
Regular Pareto front
DTLZ1	3, 5, 10	M −1 + 5	Linear
DTLZ3	3, 5, 10	M −1 + 10	Concave
DTLZ2, 4	3, 5, 10	M −1 + 10	Concave
WFG4-9	3, 5, 10	M −1 + 10	Concave
Irregular Pareto front
DTLZ5-6	3, 5, 10	M −1 + 10	Mostly degenerate
DTLZ7	3, 5, 10	M −1 + 20	Disconnected
WFG1	3, 5, 10	M −1 + 10	Sharp tails
WFG2	3, 5, 10	M −1 + 10	Disconnected
WFG3	3, 5, 10	M −1 + 10	Mostly degenerate
MaF3	3, 5, 10	M −1 + 10	Convex
MaF11	3, 5, 10	M −1 + 10	Convex disconnected
MaF15	3, 5, 10	20^∗M	Convex large scale