Results 281 to 290 of about 3,948 (333)

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Improved Discrete Particle Swarm Optimization Algorithm for Solving Fuzzy Flexible Job Shop Machines and Agvs Fusion Scheduling Problem

Xixing Li, Chenchen Wu, Rui Wu, Hongtao Tang, Yibing Li   +4 more
openalex   +1 more source

Scheduling optimization of ship plane block flow line considering dual resource constraints. [PDF]

Sci Rep
Li J, Lin P, Wu X, Song D, Yang B, Zhou L.   +5 more
europepmc   +1 more source

A hybrid evolution strategies algorithm for non-permutation flow shop scheduling problems. [PDF]

Sci Rep
Khurshid B, Maqsood S, Habib MS, Omair M, Hwang SJ.   +4 more
europepmc   +1 more source

Schedule optimization for chemical library synthesis. [PDF]

Digit Discov
Ai Q, Meng F, Wang R, Klein JC, Godfrey AG, Coley CW.   +5 more
europepmc   +1 more source

Energy-efficient scheduling for a flexible job shop problem considering rework processes and new job arrival

Emrah Albayrak, Semih Önüt
openalex   +1 more source

Dynamic job shop scheduling under multiple order disturbances using deep reinforcement learning. [PDF]

Sci Prog
Sun Z, Han W, Gao L, Zhu C, Lyu Q.
europepmc   +1 more source

An enhanced firefly algorithm approach for solving a flexible job-shop scheduling problem

, 2018
Apurva Gupta, Satpal Singh Kushwaha
openalex   +1 more source

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A genetic algorithm for the Flexible Job-shop Scheduling Problem

Computers and Operations Research, 2008
In this paper a genetic algorithm for the flexible job-shop scheduling problem is presented. Given are a set of machines and a set of jobs consisting of operations which have to be sequenced in a fixed order. Each operation can be processed by a subset of the machines and its processing time depends on the assigned machine.
G Morganti
exaly   +3 more sources

An effective genetic algorithm for the flexible job-shop scheduling problem

Expert Systems With Applications, 2011
In this paper, we proposed an effective genetic algorithm for solving the flexible job-shop scheduling problem (FJSP) to minimize makespan time. In the proposed algorithm, Global Selection (GS) and Local Selection (LS) are designed to generate high-quality initial population in the initialization stage.
Guohui Zhang, Liang Gao
exaly   +2 more sources