Genetic algorithm approach to an optimal scheduling problem for a large-scale complex manufacturing system

2003 ◽  
Author(s):  
N. Sannomiya ◽  
H. Iima
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Manufacturing System ◽  
Optimal Scheduling ◽  
Scheduling Problem ◽  
Genetic Algorithm Approach

Genetic Algorithm Approach to a Scheduling Problem for a Complex Manufacturing System

1998 ◽  
Vol 31 (20) ◽  
pp. 271-276
Author(s):  
Nobuo Sannomiya ◽  
Hitoshi Iima ◽  
Kagayaki Suzuki ◽  
Yasunori Kobayashi
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing System ◽  
Scheduling Problem ◽  
Genetic Algorithm Approach

Multi-Task Scheduling Based on QoS Evaluation in Cloud Manufacturing System

2017 ◽  
Author(s):  
Feng Li ◽  
Lin Zhang ◽  
Yuanjun Laili
Keyword(s):  
Genetic Algorithm ◽  
Task Scheduling ◽  
Manufacturing System ◽  
Comprehensive Evaluation ◽  
Effective Means ◽  
Cloud Manufacturing ◽  
Optimal Scheduling ◽  
Distributed Resources ◽  
Scheduling Strategies ◽  
Qos Evaluation

Cloud manufacturing (CMfg) mode provides an effective means to intensely utilize distributed resources and manufacturing capability for personalized production. Increasing personalized customization implies more and more heterogeneous tasks and hence more sorts of requirements for services. As the granularity of tasks vary with changing users and products, the solution (or scheme) of task scheduling should be different. In order to efficiently provide the most suitable solution for each kind of tasks, different scheduling ways should be adopted under different circumstances. In this paper, we study scheduling issues for heterogeneous tasks with variable granularity and present two kinds of optimal scheduling mode based on user-oriented comprehensive evaluation. Then different encoding schemes relied on the genetic algorithm are proposed according to different scheduling strategies.

A Game Theory Approach for Multiple Design Tasks Schedule

2010 ◽  
Vol 26-28 ◽  
pp. 163-166
Author(s):  
Guo Hai Zhang ◽  
Guang Hui Zhou ◽  
Xue Qun Su
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Game Theory ◽  
Solution Algorithm ◽  
Optimal Scheduling ◽  
Theory Approach ◽  
Scheduling Problem ◽  
Tasks Scheduling ◽  
Numerical Case Study

This paper presents a new kind of scheduling solution for multiple design tasks in networked developing environments. The main contributions of this study can be focused on three points: The first is to distinguish the concepts and contents of the task scheduling in the networked developing environments. The second is to construct a game-theory mathematical model to deal with this new multiple design tasks scheduling problem. In the presented mathematical model, the players, strategies and payoff are given separately. Therefore, obtaining the optimal scheduling results is determined by the Nash equilibrium (NE) point of this game. In order to find the NE point, a genetic algorithm (GA)-based solution algorithm to solve this mathematical model is proposed. Finally, a numerical case study is presented to demonstrate the feasibility of the methods.

Sign in / Sign up

Export Citation Format

Share Document