Results 71 to 80 of about 5,089,183 (236)

Exploitation of a Medium-Sized Fuzzy Outranking Relation Based on Multi-objective Evolutionary Algorithms to Derive a Ranking

International Journal of Computational Intelligence Systems, 2016
We present a multi-objective evolutionary algorithm to exploit a medium-sized fuzzy outranking relation to derive a partial order of classes of alternatives (we call it RP-NSGA-II).
Juan Carlos Leyva López, Jesús Jaime Solano Noriega, Jorge Luis García Alcaraz, Diego Alonso Gastélum Chavira   +3 more
doaj   +1 more source

AI‐Driven Synthesis in Medicinal Chemistry: Integrating Large Language Models, Robotic Automation, and Sustainability Metrics to Accelerate Drug Discovery

Medicinal Research Reviews, EarlyView.
ABSTRACT Artificial intelligence (AI) is transforming synthetic chemistry from task‐specific predictors into integrated platforms that unify retrosynthesis, reaction optimization, and closed‐loop robotic automation. This review highlights how AI‐assisted planning and robotic execution shorten cycle times, reduce step counts, and improve route ...
Amit Gangwal, Antonio Lavecchia
wiley   +1 more source

AlloyDesignClaw: Optimizing Castability and Mechanical Properties of Nickel‐Based Superalloys

Materials Genome Engineering Advances, EarlyView.
A stepwise optimization method is proposed for castability and mechanical properties of nickel‐based superalloys, enabling interpretable dimensionality reduction and efficient multi‐objective optimization of the composition space. An alloy design multi‐agent framework was further developed, integrating large language models, CALPHAD calculation ...
Jiaxuan Ma, Songyang Chen, Rui Feng, Xin Hao, Hang Zheng, Chushan Yi, Qingbiao Tan, Guoliang Zhu   +7 more
wiley   +1 more source

An Enhanced NSGA-II Driven by Deep Reinforcement Learning to Mixed Flow Assembly Workshop Scheduling System with Constraints of Continuous Processing and Mold Changing

Systems
Mixed-flow assembly lines are widely employed in industrial manufacturing to handle diverse production tasks. For mixed flow assembly lines that involve mold changes and greater processing difficulties, there are currently two approaches: batch ...
Bihao Yang, Jie Chen, Xiongxin Xiao, Sidi Li, Teng Ren   +4 more
doaj   +1 more source

Designing γ‐TiAl Alloys With Refined Twin‐Lamellar Microstructures via Machine Learning‐Driven Phase‐Field Methods

Materials Genome Engineering Advances, EarlyView.
Dual‐phase γ‐TiAl alloys with refined twin‐lamellar (RTL) structures exhibit optimal strength‐ductility synergy. Here, phase‐field simulations reveal composition‐stress‐dependent refined twin‐lamellar (RTL) microstructure evolution. Machine learning (CatBoost + NSGA‐III) trained on phase‐field images predicts optimal RTL‐stress‐composition design space.
Jianwei Li, Zhenqiang Xiong, Chuanxin Liang, Tianjiao Dong, Heran Wang, Mengyuan Hao, Liqiang He, Tianlong Zhang, Dong Wang   +8 more
wiley   +1 more source

A Chance‐Constrained Model for a Production Routing Problem With Uncertain Availability of Vehicles

Networks, EarlyView.
ABSTRACT The Production Routing Problem (PRP) is a complex integrated problem that allows for the achievement of competitive advantages, such as better management of inventory, reduction in operational costs and lead times, improvement in efficiency and customer service, and better response to market changes.
Alline Zanette, Michel Gendreau, Walter Rei   +2 more
wiley   +1 more source

A Review of Advances in Composite Materials, Structural Optimization, and Machine Learning for Wind Turbine Blades: Challenges and Future Perspectives

Polymer Composites, EarlyView.
Overview of the holistic engineering lifecycle and core research pillars for wind turbine blades. ABSTRACT This paper reviews recent advancements across the lifecycle of wind turbine blades, focusing on three interconnected areas: advanced composites, structural optimization, and machine learning (ML) diagnostics. In materials, we highlight progress in
Kemal Hasirci, Denizhan Yavas, Alaeddin Burak Irez   +2 more
wiley   +1 more source

Translating Machine Learning Into Manufacturing Expertise—Actionable Interpretability and Stability for Precision Injection Molding

Polymer Engineering &Science, EarlyView.
This research aims to enhance confidence in using AI/ML models and address unpredicted defects occurred during injection molding (IM) through guided machine fine‐tuning. Integrated stability analysis and parallel coordinate visualization coupled with perturbation analysis are presented to augment domain‐specific XAI applications in the IM industry ...
Chung‐Yin Lin, Jinsu Gim, Andrea Pieressa, Demitri Shotwell, Kris Sankaran, Giovanni Lucchetta, Lih‐Sheng Turng   +6 more
wiley   +1 more source

Comparative Benchmarking of Multi-Objective Algorithms for Renewable Energy System Design Using Pareto Front Quality Metrics

Applied Sciences
Selecting the best multi-objective algorithms for photovoltaic energy storage system (PV-ESS) design remains challenging due to limited benchmarking across renewable energy studies.
Raphael I. Areola, Abayomi A. Adebiyi, Dwayne J. Reddy   +2 more
doaj   +1 more source

Freeway Traffic Congestion Reduction and Environment Regulation via Model Predictive Control

Algorithms, 2019
This paper proposes a model predictive control method based on dynamic multi-objective optimization algorithms (MPC_CPDMO-NSGA-II) for reducing freeway congestion and relieving environment impact simultaneously. A new dynamic multi-objective optimization
Juan Chen, Yuxuan Yu, Qi Guo
doaj   +1 more source