A multi-objective scheduling algorithm with self-evolutionary feature for job-shop-like knowledgeable manufacturing cell

2014 ◽  
Vol 28 (2) ◽  
pp. 337-351 ◽  
Author(s):  
Hong-Sen Yan ◽  
Wen-Chao Li
Keyword(s):  
Job Shop ◽  
Scheduling Algorithm ◽  
Manufacturing Cell ◽  
Multi Objective ◽  
Knowledgeable Manufacturing

A Self-Learning Algorithm Based on Support Vector Machine for Scheduling a Job-Shop-Like Knowledgeable Manufacturing Cell

2011 ◽  
Vol 148-149 ◽  
pp. 369-373
Author(s):  
Wen Chao Li ◽  
Hong Sen Yan
Keyword(s):  
Support Vector Machine ◽  
Job Shop ◽  
Learning Algorithm ◽  
Learning Ability ◽  
Small Samples ◽  
Support Vector ◽  
Manufacturing Cell ◽  
Cell Scheduling ◽  
Knowledgeable Manufacturing ◽  
Self Learning

The job-shop-like knowledgeable manufacturing cell scheduling is a NP-complete problem and there has not been a completely valid algorithm for it until now. An algorithm with self -learning ability is proposed through the addition of precedence constraint of operations on the basis of directed graph. A method based on support vector machine is constructed to choose accurately interchangeable operations by small samples earning to obtain the better scheduling. The classification accuracy can be improved by the continuous addition of new instances to the sample library. The results of simulation show that the algorithm performs well for the job-shop-like knowledgeable manufacturing cell.

Multi-Objective Scheduling Based on Weighted Combination of Heuristic Rules and the Simulation Method

2012 ◽  
Vol 424-425 ◽  
pp. 1132-1138
Author(s):  
Li Mei Ma ◽  
Jian Yong Li ◽  
Wen Sheng Xu ◽  
Ling Jun Kong
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Computational Study ◽  
Scheduling Algorithm ◽  
Simulation Method ◽  
Software Modeling ◽  
Heuristic Rules ◽  
Resource Configuration ◽  
Real Time Scheduling ◽  
Multi Objective

The soft (logical) reconfiguration mainly include re-programming of machines, re-scheduling, including re-planning, re-routing and increasing/decreasing of shifts or number of workers according to task changes. In order to solve multi-constrains and multi-objective flexible job-shop scheduling problem (FJSP), a multi-objective and real-time scheduling algorithm was presented based on resource configuration, task constrains and scheduling objectives. It overcomes the traditional difficulty to find optimal combined heuristic rules for multi-objective, meanwhile keeps the simpleness of the scheduling rules. Finally, Flexsim software modeling and simulation method was used to validate its feasibility and effectiveness. At the same time, resource configuration schemes were generated based on the presented algorithm and the optimal scheme was selected. The results obtained from the computational study have shown that the proposed algorithm is a viable and effective approach for the multi-objective FJSP

scholarly journals Unified Multi-Objective Genetic Algorithm for Energy Efficient Job Shop Scheduling

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Hongjing Wei ◽  
Shaobo Li ◽  
Huafeng Quan ◽  
Dacheng Liu ◽  
Shu Rao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficient ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

Control of knowledgeable manufacturing cell with an unreliable agent

2008 ◽  
Vol 20 (6) ◽  
pp. 671-682 ◽  
Author(s):  
Hong-Sen Yan ◽  
Hong-Bing Yang ◽  
Hao Dong
Keyword(s):  
Manufacturing Cell ◽  
Knowledgeable Manufacturing
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