A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry-Reference-Cited by-同舟云学术

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A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry

Published:2017-01 Issue: Volume:57 Page:61-79
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Lu Chao,Gao Liang,Li Xinyu,Xiao Shengqiang

Funder

National Natural Science Foundation of China

National Key Technology Support Program

Youth Science & Technology Chenguang Program

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference57 articles.

1. Group-shop scheduling with sequence-dependent set-up and transportation times;Ahmadizar;Appl. Math. Model.,2014

2. Multi-objective sequence dependent setup times permutation flowshop: a new algorithm and a comprehensive study;Ciavotta;Eur. J. Oper. Res.,2013

3. Using real time information for effective dynamic scheduling;Cowling;Eur. J. Oper. Res.,2002

4. A fast and elitist multiobjective genetic algorithm: nsga-ii;Deb;IEEE Trans. Evol. Comput.,2002

5. jMetal: a Java framework for multi-objective optimization;Durillo;Adv. Eng. Softw.,2011

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2. A Self-Learning Discrete Artificial Bee Colony Algorithm for Energy-Efficient Distributed Heterogeneous L-R Fuzzy Welding Shop Scheduling Problem;IEEE Transactions on Fuzzy Systems;2024-06

3. An improved memetic algorithm for multi-objective resource-constrained flexible job shop inverse scheduling problem: An application for machining workshop;Journal of Manufacturing Systems;2024-06

4. A cooperative grey wolf optimizer for the joint flowshop scheduling problem with sequence-dependent set-up time;Engineering Optimization;2024-04-12

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