CRNDP is an MO problem, while ABCLLS is a single-objective algorithm.
As the ABCLLS is a single objective algorithm and the CRNDP is an MO problem, we consider the elitist crowded comparison operator [[greater than or equal to].
Thus, several questions arise about how to implement this comparison: What quantitative measures should be employed to present the quality of the results so that the metaheuristics used to CRNDP can be compared in a meaningful way?
We employ two complementary measures to evaluate the tradeoff fronts produced by the metaheuristics to CRNDP.
We configure this common framework for studying the CRNDP.
Therefore, we chiefly address the CRNDP based on the data set with MO metaheuristics in this section.