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

To optimize the solving efficiency of multi-objective path planning problems, this paper proposes an improved solution based on Whale Optimization Algorithm (IDWOA). First, a greedy strategy is ...

Second, the conversion to a single-objective optimization problem involves additional constraints. Third, since most real-world goal programming problems involve nonlinear criterion functions, the ...

Considering the undesirable characteristics of the balance shaft, such as cost, weight, friction, and noise, as well as dynamically inappropriate mass unbalancing method, this research proposes ...

Other algorithms, such as the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), break the optimization problem into smaller sub-problems, each representing a weighted combination ...

Computational optics integrates optical hardware and algorithms, enhancing imaging capabilities through joint optimization ...

Facing the requirement of efficient balanced operation of multiple distributed energy sources and loads, the multi-objective optimal scheduling task for microbalanced area grids relies on more ...