By Topic

Notice of Retraction
Application of plant growth simulation algorithm for job shop scheduling

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Tang Haibo ; Coll. of Manage., Univ. of Shanghai for Sci. & Technol., Shanghai, China ; Ye Chunming

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Based on Plant Growth Simulation Algorithm, we propose an intelligence optimization algorithm for solving job shop scheduling problems. Starting with the characteristic of job shop scheduling problem, combining disjunctive graph according to the sequence of scheduling, analyzing Scheduling options that decided by exchangeable set and alternative set, by simulating the process of plant growth, and then we can determine the optimal scheduling. Simulation results based on well-known benchmarks and comparisons with standard genetic algorithm demonstrate the effectiveness of the proposed bionic algorithm.

Published in:

Advanced Management Science (ICAMS), 2010 IEEE International Conference on  (Volume:1 )

Date of Conference:

9-11 July 2010