Amanote Research
Register
Sign In
An Adaptive Multi-Population Artificial Bee Colony Algorithm for Multi-Objective Flexible Job Shop Scheduling Problem
doi 10.1109/ccdc.2019.8833005
Full Text
Open PDF
Abstract
Available in
full text
Date
June 1, 2019
Authors
Yang Cao
Haibo Shi
Publisher
IEEE
Related search
Hybrid Multi-Objective Particle Swarm Optimization for Flexible Job Shop Scheduling Problem
International Journal of Intelligent Systems and Applications
Control
Signal Processing
Human-Computer Interaction
Optimization
Computer Networks
Simulation
Communications
Computer Science Applications
Modeling
Artificial Intelligence
Hybrid Evolutionary Approach for Multi-Objective Job-Shop Scheduling Problem
Malaysian Journal of Computer Science
Computer Science
Multi-Objective Fuzzy Job Shop Scheduling
International Journal of Fuzzy Computation and Modelling
An Adaptive Scheduling Algorithm for Dynamic Jobs for Dealing With the Flexible Job Shop Scheduling Problem
Wirtschaftsinformatik
Information Systems
Ant Colony Optimisation for Scheduling of Flexible Job Shop With Multi-Resources Requirements
MATEC Web of Conferences
Materials Science
Engineering
Chemistry
Resolving Micro-Grid Energy Optimization Using Multi-Objective Artificial Bee Colony Algorithm
DEStech Transactions on Computer Science and Engineering
Approach of Solving Dual Resource Constrained Multi-Objective Flexible Job Shop Scheduling Problem Based on MOEA/D
International Journal of Online Engineering
Engineering
E-learning
Hybrid Intelligent Algorithm for Flexible Job-Shop Scheduling Problem Under Uncertainty
A Hybrid Evolutionary Algorithm for Solving Flexible Job Shop Scheduling Problem
IJCI. International Journal of Computers and Information
