Abstract: 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 ...

Incorporating multiple constraints such as task completion time, UAV payload capacity, and flight range into path optimization algorithms allows for more efficient search patterns.

In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...

Tourism development in emerging destinations requires balancing economic benefits with ecological sustainability. In this study, we investigate the case of multi-attraction tourism planning in Qujing ...

Abstract: This paper studies the multi-objective optimization problems (MOPs) of Markovian jump systems (MJSs) closed by general controllers. Firstly, the linear quadratic regulator (LQR) problem of ...