Results 221 to 230 of about 122,671 (350)
Research on multi-agent genetic algorithm based on tabu search for the job shop scheduling problem. [PDF]
Peng C, Wu G, Liao TW, Wang H.
europepmc +1 more source
A novel Variable Neighborhood Particle Swarm Optimization for multi-objective Flexible Job-Shop Scheduling Problems [PDF]
Hongbo Liu, Ajith Abraham, Crina Groşan
openalex +1 more source
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu +5 more
wiley +1 more source
Learnable evolutionary model for flexible job-shop scheduling [PDF]
Nhu Binh Ho
openalex +1 more source
Post‐surgical tumor therapy struggles with recurrence and inefficient healing. Anti‐tumor DNA aptamer functionalized gelatin hydrogels, Apt‐GelMA, simultaneously address both issues by suppressing tumor regrowth via targeted tumor cell inhibition and enhancing wound healing through improved cell adhesion and migration. Their biocompatibility, stability,
Tianyue Li +11 more
wiley +1 more source
A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling. [PDF]
Deng Q +5 more
europepmc +1 more source
A novel descriptor and a bottom‐up design principle are established to enable the rational design of hydrogen storage materials based on d‐block transition metal single‐atom COFs. By modulating H₂ adsorption through d‐orbital tuning, this approach achieves both high storage capacity and fast kinetics, while revealing a volcano‐type relationship between
Qiuyan Yue +24 more
wiley +1 more source
MULTI-AGENT APPROACH BASED ON TABU SEARCH FOR THE FLEXIBLE JOB SHOP SCHEDULING PROBLEM
Meriem Ennigrou, Khaled Ghédira
openalex +1 more source
Recycling of Thermoplastics with Machine Learning: A Review
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque +5 more
wiley +1 more source

