It is possible to conclude that the parallelization has a positive effect on the convergence and diversity of the optimization process for problems with many objectives. However, there is no single strategy that is the best results for all classes of problems. In terms of scalability, for higher...
Nevertheless, balancing proximity and diversity using one single criterion is not an easy task [76], [38], [69], [68], especially for a many-objective optimization problem in which the conflict between the objectives is generally more serious than that in an MOP with two or three objectives...
Kang, Z.et al.(2007). A New Evolutionary Decision Theory for Many-Objective Optimization Problems. In: Kang, L., Liu, Y., Zeng, S. (eds) Advances in Computation and Intelligence. ISICA 2007. Lecture Notes in Computer Science, vol 4683. Springer, Berlin, Heidelberg. https://doi.org/1...
Inspired by these two observations, BiGE converts a given multi-objective optimization problem into a bi-goal (objective) optimization problem regarding proximity and diversity, and then handles it using the Pareto dominance relation in this bi-goal domain. Implemented with estimation methods of ...
More complex than multi-objective optimization, which copes with two or three objectives, many-objective optimization represents a challenging problem due to the complex trade-off relationships among the optimization objectives. In this study, a four-objective optimization system was proposed for reducing...
A key question when tackling such a set problem is how to define the optimization criterion. Many multiobjective evo- lutionary algorithms (MOEAs) implement a combination of Pareto dominance on sets and a diversity measure based on Euclidean distance in the objective space, e.g., NSGA-II ...
A many-objective evolutionary algorithm based on three states for solving many-objective optimization problem Article Open access 19 August 2024 A new optimization algorithm to solve multi-objective problems Article Open access 13 October 2021 External archive guided radial-grid multi objective diffe...
many-objective problemoptimizationevolutionary computationsmemetic I-DBEAThe pickup and delivery problem (PDP) is a very common and important problem, which has a large number of real-world applications in logistics and transportation. In PDP, customers send transportation requests to pick up an ...
(Many-Objective Optimization Problem) A multi/many-objective optimization problem with m minimization objectives is formalized as 1.minF(x)=(f1(x),f2(x),...,fm(x))s.t.gi(x)≤0i=1,2,...,q,hj(x)=0j=1,2,...,p. where m is the number of objectives, fm(x) is the mth obje...
this class of problems, since a DM will eventually need to select a single solution from the huge number of Pareto-optimal ones—in other words, solving the problem of finding Pareto-optimal points does not necessarily mean that one has solved the practical many-objective optimization problem. ...