Abstract This paper introduces a multi-objective variant of the marine predators algorithm (MPA) called improved (MOIMPA), which incorporates concepts from Quantum theory. By leveraging theory, MOIMPA aims to enhance MPA’s ability balance between exploration and exploitation find optimal solutions. The utilizes concept inspired by Schrödinger wave function determine position particles in search...

The main aim of the present paper is to propose efficient multi-objective optimization algorithms (MOOAs) to tackle truss structure optimization problems. The proposed meta-heuristic algorithms are based on the firefly algorithm (FA) and bat algorithm (BA), which have been recently developed for single-objective optimization. In order to produce a well distributed Pareto front, some improvement...

beneficial management practices (bmps) are important measures for reducing agricultural non-point source (nps) pollution. however, selection of bmps for placement in a watershed requires optimizing available resources to maximize possible water quality benefits. due to its iterative nature, the optimization typically takes a long time to achieve the bmp trade-off results which is not desirable ...

abstract in this paper, a fuzzy pid with new structure is proposed to solve the load frequency control in interconnected power systems. in this study, a new structure and effective of the fuzzy pid-type load frequency control (lfc) is proposed to solve the load frequency control in interconnected power systems. the main objective is to eliminate the deviations in the frequency of different area...

Most of the existing dynamic multi-objective evolutionary algorithms (DMOEAs) are effective, which focuses on searching for approximation Pareto-optimal front (POF) with well-distributed in handling optimization problems (DMOPs). Nevertheless, real-world scenarios, decision maker (DM) may be only interested a portion corresponding POF (i.e., region interest) different instances, rather than who...