Performance assessment of the metaheuristic optimization algorithms: an exhaustive review
The simulation-driven metaheuristic algorithms have been successful in solving numerous
problems compared to their deterministic counterparts. Despite this advantage, the …
problems compared to their deterministic counterparts. Despite this advantage, the …
Performance indicators in multiobjective optimization
In recent years, the development of new algorithms for multiobjective optimization has
considerably grown. A large number of performance indicators has been introduced to …
considerably grown. A large number of performance indicators has been introduced to …
An improved multi-objective genetic algorithm with heuristic initialization for service placement and load distribution in edge computing
Edge Computing (EC) is a promising concept to overcome some obstacles of traditional
cloud data centers to support Internet of Things (IoT) applications, especially time-sensitive …
cloud data centers to support Internet of Things (IoT) applications, especially time-sensitive …
Energy aware scheduling in flexible flow shops with hybrid particle swarm optimization
This paper integrates energy awareness in the flexible flow shop scheduling system, where
two objectives are minimized simultaneously: total tardiness and electric power costs. We …
two objectives are minimized simultaneously: total tardiness and electric power costs. We …
Design and optimization of a magnetic-geared direct-drive machine with V-shaped permanent magnets for ship propulsion
This article presents a novel magnetic-geared direct-drive machine (MGDM) with V-shaped
permanent magnets (PMs) installed on its rotor. By extending the inner rotor shaft and …
permanent magnets (PMs) installed on its rotor. By extending the inner rotor shaft and …
A new LID spatial allocation optimization system at neighborhood scale: Integrated SWMM with PICEA-g using MATLAB as the platform
Despite the growing interest, limited studies have been conducted on LID spatial allocation
optimization (SAO) at neighborhood scale, and no study has applied modifications to the …
optimization (SAO) at neighborhood scale, and no study has applied modifications to the …
A novel approach of many-objective particle swarm optimization with cooperative agents based on an inverted generational distance indicator
Most evolutionary algorithms, including particle swarm optimization (PSO), use Pareto
dominance as a major selection criterion and face significant challenges when dealing with …
dominance as a major selection criterion and face significant challenges when dealing with …
Multi-objective colliding bodies optimization algorithm for design of trusses
A Kaveh, VR Mahdavi - Journal of Computational Design and …, 2019 - academic.oup.com
This article presents a new population-based optimization algorithm to solve the multi-
objective optimization problems of truss structures. This method is based on the recently …
objective optimization problems of truss structures. This method is based on the recently …
A non-revisiting quantum-behaved particle swarm optimization based multilevel thresholding for image segmentation
Z Yang, A Wu - Neural Computing and Applications, 2020 - Springer
Multilevel thresholding for image segmentation is one of the crucial techniques in image
processing. Even though numerous methods have been proposed in literature, it is still a …
processing. Even though numerous methods have been proposed in literature, it is still a …
[HTML][HTML] A bi-criteria approach to the truck-multidrone routing problem
PL Gonzalez-R, D Sanchez-Wells… - Expert Systems with …, 2024 - Elsevier
In the rapidly expanding field of e-commerce logistics, the optimisation of last-mile delivery
solutions is paramount. This paper introduces a novel methodology that addresses this …
solutions is paramount. This paper introduces a novel methodology that addresses this …