Genetic Algorithm Design and Simulation for Job-Shop Scheduling Problem

Gui Cong Wang; Xi Jie Tian; Chuan Peng Li; Na Na Yang

doi:10.4028/www.scientific.net/AMM.157-158.1436

Paper Titles

Research and Implementation on Multi-Database System Based on XML
p.1413

Design and Implementation of Remote Disaster Backup Solution to Oracle Lob
p.1420

Long-Distance Slurry Pipeline Valve Monitoring System Design and Application
p.1427

A Prototype Target Tracking Network System for Robot Feedback Control
p.1431

Genetic Algorithm Design and Simulation for Job-Shop Scheduling Problem
p.1436

Technique Influence on Cast-Iron Surface Textures Induced by LST
p.1441

Data Fusion Algorithm for Asynchronous Radar Networks under Blanket Jamming
p.1446

Design of the Heating Regulation Controller Based on ARM
p.1453

The Visual Extraction of the Autonomous Lawnmower Navigation Route
p.1458

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 157-158Genetic Algorithm Design and Simulation for...

Genetic Algorithm Design and Simulation for Job-Shop Scheduling Problem

Abstract:

This paper proposes an effective genetic algorithm for the job-shop scheduling problem (JSP) to minimize makespan time. An effective chromosome representation based on real coding is used to conveniently represent a solution of the JSP, and different strategies for selection, crossover and mutation are adopted. Simulation experimental results have shown that the scheduling model using the algorithm can allocate jobs efficiently and effectively.