Results 221 to 230 of about 188,484 (320)

An Immune-Inspired Approach with Interval Allocation in Solving Multimodal Multi-Objective Optimization Problems with Local Pareto Sets [PDF]

Weiwei Zhang, Jiaqiang Li, Chao Wang, Meng Li, Zhi Rao   +4 more
openalex   +1 more source

Modelling and improving approach for carrying capacity in multi-modal super network by considering travel time. [PDF]

PLoS One
Huang X.
europepmc   +1 more source

Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou, Juan Zou, Gan Ruan, Yuan Liu, Yizhang Xia   +4 more
wiley   +1 more source

Quantum approximate multi-objective optimization. [PDF]

Nat Comput Sci
Kotil A, Pelofske E, Riedmüller S, Egger DJ, Eidenbenz S, Koch T, Woerner S.   +6 more
europepmc   +1 more source

MOEA/D‐based multi‐row facility layout optimisation method with discontinuity perceiving of the Pareto front

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In a multi‐row facility layout problem (MRFLP), facilities are arranged in more than one row under the limited layout area. Considering different layout factors, various extensions of MRFLP have been modelled. However, the orientation of input/output (I/O) point in a facility, as a key factor that plays a direct impact on flow cost, is seldom ...
Yinan Guo, Yao Huang, Jian Cheng, Xiaoyu Ban, Xiaoxiao Zhao, Tianyu Liu   +5 more
wiley   +1 more source

Cross-sectional analysis of accuracy versus interpretability in Medicare Advantage risk adjustment. [PDF]

Health Policy Open
Lozinski M.
europepmc   +1 more source

Multi‐Objective Optimisation Framework for Heterogeneous Federated Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Federated learning is a distributed framework that trains a centralised model using data from multiple clients without transferring that data to a central server. Despite rapid progress, federated learning still faces several unsolved challenges. Specifically, communication costs and system heterogeneity, such as nonidentical data distribution,
Jamshid Tursunboev, Vikas Palakonda, Il‐Min Kim, Sunghwan Moon, Jae‐Mo Kang   +4 more
wiley   +1 more source

A Conceptual Framework for the Crystallizability of Organic Compounds. [PDF]

J Am Chem Soc
van de Streek J, Dietrich H, Firaha D, Ludwig M, Ovchinnikov A, Sasikumar K, DiPasquale AG, Iuzzolino L, Kelly AW, Lafarguette P, Lee AY, Robert B, Woollam GR, Neumann MA.   +13 more
europepmc   +1 more source

Set of Pareto solutions obtained by the results of Table 4.

Roberto Castro-Medina (21484990), Miguel Gabriel Villarreal-Cervantes (21484993), Leonel Germán Corona-Ramírez (21484996), Geovanni Flores-Caballero (21484999), Alejandro Rodríguez-Molina (6506204), Ramón Silva-Ortigoza (11421101), Víctor Darío Cuervo-Pinto (21485002), Andrés Abraham Palma-Huerta (21485005)   +7 more
openalex   +1 more source

Pareto Set as a Model for Dispatching Resources in Emergency Centres

, 2018
Ricardo Guedes, Vasco Furtado, Tarc�sio Pequeno, Joel J. P. C. Rodrigues   +3 more
openalex   +1 more source