Multi-objective optimisation using evolutionary algorithms constitutes a powerful computational framework that addresses complex problems involving conflicting objectives. By emulating natural ...

To address this issue, we propose a novel robust multi-objective evolutionary optimization algorithm based on the concept of survival rate. The algorithm comprises two stages: the evolutionary ...

Dynamic interval multi-objective optimization problems, such as those encountered in wireless sensor network scheduling and portfolio selection, are increasingly prevalent. However, they present ...

Keywords: evolutionary computation, constrained optimization, sequence optimization, co-evolutionary algorithms, multi-obj ective optimization problems. Citation: Zhang J, Yue H, Wang Y, Guo R and ...

Results: The proposed two-objective problem model and DK-MOEA were tested on a fatigue detection task and four state-of-the-art multi-objective evolutionary algorithms were used for comparison. The ...

The structural diagram and simulation contour of the curved wing box are shown in Figure 4. (a) (b) (c) Figure 4. Simulation analysis diagram of the curved wing box. (a) Structural diagram of the ...

K. Deb, Nonlinear Goal Programming Using Multi-Objective Genetic Algorithms, The Journal of the Operational Research Society, Vol. 52, No. 3 (Mar., 2001), pp. 291-302 Free online reading for over 10 ...