Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …

Abstract The Multiple Traveling Salesman Problem (MTSP) is among the most interesting
combinatorial optimization problems because it is widely adopted in real-life applications …

This paper proposes a nature-inspired swarm-based metaheuristic for solving global
optimization problems called Golden Eagle Optimizer (GEO). The core inspiration of GEO is …

This research proposes an Archive-based Multi-Objective Arithmetic Optimization Algorithm
(MAOA) as an alternative to the recently established Arithmetic Optimization Algorithm (AOA) …

This work proposes two novel optimization algorithms called Salp Swarm Algorithm (SSA)
and Multi-objective Salp Swarm Algorithm (MSSA) for solving optimization problems with …

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm
motivated by intelligent collective behavior of some animals such as flocks of birds or …

Complexity and variety of modern multiobjective optimisation problems result in the
emergence of numerous search techniques, from traditional mathematical programming to …

Due to the novelty of the Grey Wolf Optimizer (GWO), there is no study in the literature to
design a multi-objective version of this algorithm. This paper proposes a Multi-Objective …

A novel swarm intelligence optimization technique is proposed called dragonfly algorithm
(DA). The main inspiration of the DA algorithm originates from the static and dynamic …

This paper proposes a multi-objective version of the recently proposed Ant Lion Optimizer
(ALO) called Multi-Objective Ant Lion Optimizer (MOALO). A repository is first employed to …