Recently, meta-heuristic algorithms have made remarkable progress in solving types of
complex and NP-hard problems. So that, most of this algorithms are inspired by swarm …

Deep neuro-fuzzy systems (DNFSs) have been successfully applied to real-world problems
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …

Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

Parameters for defining photovoltaic models using measured voltage–current​
characteristics are essential for simulation, control, and evaluation of photovoltaic-based …

Multi-objective truss optimisation is a research topic that has been less investigated in the
literature compared to the single-objective cases. This paper investigates the comparative …

To handle the multiobjective optimization problems of truss-bar design, this paper introduces
a new metaheuristic multiobjective optimization algorithm. The proposed algorithm is based …

The present study investigates a novel Multiobjective Thermal Exchange Optimization
(MOTEO) algorithm for truss design. Established on Newton's law of cooling framework, this …

This paper proposes a new Multi-Objective Plasma Generation Optimization (MOPGO)
algorithm, and its non-dominated sorting mechanism is investigated for numerous …

Multi-objective (MO) problems are complex and challenging to solve due to multiple
conflicting objectives and incommensurate constraints. Heat Transfer Search is a recently …

The truss optimization problem has been extensively investigated, and the optimized trusses
have been widely used in various fields. Truss optimization is a challenging optimization …