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

Deb, K. (2001) Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, UK. has been cited by the following article: TITLE: Optimal Power Flow Using Firefly Algorithm with Unified Power Flow ...

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 ...

Solving constrained multi-objective optimization problems (CMOPs) is a challenging task due to the presence of multiple conflicting objectives and intricate constraints. In order to better address ...

Keywords: multi-objective optimization, sparse Gaussian process, surrogate model, adaptive grid multi-objective particle swarm optimization algorithm, wind power engineering Citation: Chen Y, Wang L ...

The multi-objective optimization program presented can be adapted to other environmental management problems, ... Multi-objective programming and planning. Mathematics in Science and Engineering, Vol.

The multimodal multi-objective optimization problem (MMOP) involves multiple distinct components of the Pareto set (PS), which correspond to the same Pareto front (PF). Most existing multimodal ...