A high-performance approach on mechanism isomorphism identification based on an adaptive hybrid genetic algorithm for digital intelligent manufacturing

2009 ◽  
Vol 25 (4) ◽  
pp. 397-403 ◽  
Author(s):  
Ping Yang ◽  
Kehan Zeng
Keyword(s):  
Genetic Algorithm ◽  
High Performance ◽  
Hybrid Genetic Algorithm ◽  
Intelligent Manufacturing ◽  
Isomorphism Identification

scholarly journals A Dynamic Scheduling Method for Logistics Tasks Oriented to Intelligent Manufacturing Workshop

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Wenxiang Xu ◽  
Shunsheng Guo ◽  
Xixing Li ◽  
Chen Guo ◽  
Rui Wu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Dynamic Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Intelligent Manufacturing ◽  
Automated Guided Vehicles ◽  
Scheduling Problem ◽  
Scheduling Model ◽  
Intelligent Logistics ◽  
Simultaneous Scheduling

Aiming at the logistics dynamic scheduling problem in an intelligent manufacturing workshop (IMW), an intelligent logistics scheduling model and response method with Automated Guided Vehicles (AGVs) based on the mode of “request-scheduling-response” were proposed, and they were integrated with Internet of Things (IoT) to meet the demands of dynamic and real time. Correspondingly, a mathematical model was developed and integrated with a double-level hybrid genetic algorithm and ant colony optimization (DLH-GA-ACO) to minimize the finish time with the minimum AGVs and limited time. The mathematical model optimized the logistics scheduling process on two dimensions which include the sequence of tasks assigned to an AGV and the matching relation between transfer tasks and AGVs (AGV-task). The effectiveness of the model was verified by a set of experiments, and comparison among DLH-GA-ACO, hybrid genetic algorithm and particle swarm optimization (H-GA-PSO), and tabu search algorithm (TSA) was performed. In the experiments, the DLH-GA-ACO ran in a distributed environment for a faster computing speed. According to the comparisons, the superiority and effectiveness of DLH-GA-ACO on dynamic simultaneous scheduling problem were proved and the intelligent logistics scheduling model was also proved to be an effective model.

High-performance hybrid genetic algorithm to solve transmission network expansion planning

2017 ◽  
Vol 11 (5) ◽  
pp. 1111-1118 ◽  
Author(s):  
Luis A. Gallego ◽  
Lina P. Garcés ◽  
Mohsen Rahmani ◽  
Ruben A. Romero
Keyword(s):  
Genetic Algorithm ◽  
High Performance ◽  
Hybrid Genetic Algorithm ◽  
Transmission Network ◽  
Network Expansion ◽  
Expansion Planning

Evaluation of Accidental Death Records Using Hybrid Genetic Algorithm

2020 ◽  
Author(s):  
Nikhil Sharma ◽  
Ila Kaushik ◽  
Rajat Rathi ◽  
Santosh Kumar
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Accidental Death

Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh
Keyword(s):  
Genetic Algorithm ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Genetic Algorithm ◽  
Online Reviews ◽  
Middle Tier ◽  
Complete Set ◽  
Mining Model

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.

A novel hybrid genetic algorithm-based firefly mating algorithm for solving Sudoku

2021 ◽  
Author(s):  
Sunanda Jana ◽  
Anamika Dey ◽  
Arnab Kumar Maji ◽  
Rajat Kumar Pal
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm

scholarly journals Multi-objective hybrid genetic algorithm for energy adaptive production scheduling in job shops

Procedia CIRP ◽  
2021 ◽  
Vol 98 ◽  
pp. 294-299
Author(s):  
Benedikt Grosch ◽  
Thomas Kohne ◽  
Matthias Weigold
Keyword(s):  
Genetic Algorithm ◽  
Production Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Job Shops ◽  
Multi Objective
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