Results 21 to 30 of about 609,298 (293)

Decision variable contribution based adaptive mechanism for evolutionary multi-objective cloud workflow scheduling

Complex & Intelligent Systems, 2023
Workflow scheduling is vital to simultaneously minimize execution cost and makespan for cloud platforms since data dependencies among large-scale workflow tasks and cloud workflow scheduling problem involve large-scale interactive decision variables.
Jun Li, Lining Xing, Wen Zhong, Zhaoquan Cai, Feng Hou   +4 more
doaj   +1 more source

Pareto optimality in multilayer network growth [PDF]

, 2018
We model the formation of multi-layer transportation networks as a multi-objective optimization process, where service providers compete for passengers, and the creation of routes is determined by a multi-objective cost function encoding a trade-off ...
A. Cook, Andrea Santoro, E. Zitzler, G. K. Zipf, Giuseppe Nicosia, J. Tinbergen, K. Deb, K. Deb, K. Miettinen, M. E. J. Newman, P. Pöyhönen, V. Latora, Vincenzo Nicosia, Vito Latora   +13 more
core   +3 more sources

Distributed Parallel Particle Swarm Optimization for Multi-Objective and Many-Objective Large-Scale Optimization

IEEE Access, 2017
With the advent of big data era, complex optimization problems with many objectives and large numbers of decision variables are constantly emerging. Traditional research about multi-objective particle swarm optimization (PSO) focuses on multi-objective ...
Bin Cao, Jianwei Zhao, Zhihan Lv, Xin Liu, Shan Yang, Xinyuan Kang, Kai Kang   +6 more
doaj   +1 more source

Multiobjective topology optimization of planar trusses using stress trajectories and metaheuristic algorithms

Revista Facultad de Ingeniería Universidad de Antioquia, 2022
In civil engineering, structural optimization seeks an efficient use of material resources and the automatization of the design process of a wide range of structures such as frames, bridges, and other systems.
Luis Humberto Niño-Álvarez, Oscar Javier Begambre-Carrillo   +1 more
doaj   +1 more source

A New Chaotic-Based Approach for Multi-Objective Optimization

Algorithms, 2020
Multi-objective optimization problems (MOPs) have been widely studied during the last decades. In this paper, we present a new approach based on Chaotic search to solve MOPs. Various Tchebychev scalarization strategies have been investigated. Moreover, a
Nassime Aslimani, Talbi El-ghazali, Rachid Ellaia   +2 more
doaj   +1 more source

Optimal model parameters for multi-objective large-eddy simulations [PDF]

, 2006
A methodology is proposed for the assessment of error dynamics in large-eddy simulations. It is demonstrated that the optimization of model parameters with respect to one flow property can be obtained at the expense of the accuracy with which other flow ...
Batchelor G. K., Bernard J. Geurts, Geurts B. J., Johan Meyers, Lilly D. K., Pierre Sagaut, Sagaut P.   +6 more
core   +5 more sources

Petri-Net Based Multi-Objective Optimization in Multi-UAV Aided Large-Scale Wireless Power and Information Transfer Networks

Remote Sensing, 2021
Power consumption in wireless sensor networks is high, and the lifetime of a battery has become a bottleneck, restricting network performance. Wireless power transfer with a ground mobile charger is vulnerable to interference from the terrain and other ...
Huaiyu Qin, Buhui Zhao, Leijun Xu, Xue Bai   +3 more
doaj   +1 more source

A centerline symmetry and double-line transformation based algorithm for large-scale multi-objective optimization

Connection Science, 2022
The search space of large-scale multi-objective optimization problems (LSMOPs) is huge because of the hundreds or even thousands of decision variables involved.
Xiangjuan Wu, Yuping Wang, Ziqing Wang
doaj   +1 more source

Multi-Objective Optimization Scheduling of Active Distribution Network Considering Large-Scale Electric Vehicles Based on NSGAII-NDAX Algorithm

IEEE Access, 2023
With the rapid growth of electric vehicle (EV) ownership, the problem of increased peak loads on distribution networks due to large-scale EV integration needs to be addressed.
Jingwen Chen, Lei Mao, Yaoxian Liu, Jinfeng Wang, Xiaochen Sun   +4 more
doaj   +1 more source

Distributed Big-Data Optimization via Block Communications [PDF]

, 2017
We study distributed multi-agent large-scale optimization problems, wherein the cost function is composed of a smooth possibly nonconvex sum-utility plus a DC (Difference-of-Convex) regularizer.
Notarnicola, Ivano, Notarstefano, Giuseppe, Scutari, Gesualdo, Sun, Ying   +3 more
core   +2 more sources