The decomposition-based multi-objective evolutionary algorithm (MOEA/D) transforms a optimization problem (MOP) into set of single-objective subproblems for collaborative optimization. Mismatches between and solutions can lead to severe performance degradation MOEA/D. Most existing mismatch coping strategies only work when the L∞ scalarization is used. A strategy that use any Lp scalarization, ...

We analyze combinatorial optimization problems with ordinal, i.e., non-additive, objective functions that assign categories (like good, medium and bad) rather than cost coefficients to the elements of feasible solutions. review different optimality concepts for ordinal discuss their similarities differences. then focus on two prevalent are shown be equivalent. Our main lies investigation a bije...

The close limit approximation of binary black hole is a powerful method to study gravitational-wave emission from highly non-linear geometries. In this work, we use it as tool model spacetimes in theories gravity with new fundamental scalar degree freedom. As an example, consider Einstein-scalar-Gauss-Bonnet gravity, which admits solution the Schwarzschild geometry well holes hair. Accordingly,...

In this paper, we study the properties of Germeier’s scalarization applied for solving multicriteria games. The equilibria and equilibrium values such games, as a rule, make sets, problems parametrizing approximating these sets arise. Shapley proved that Nash matrix game can be found by two-parametric family scalar games obtained with help linear criteria vector. We show parametrizes using one-...