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Task Assigning and Optimizing of Genetic-Simulated Annealing Based on MAS

  • Yong Liu
  • Shujuan Li
  • Yan Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

This paper suggests the optimization method of task assigning based on genetic-simulated annealing algorithm focus on the alternative scheme of bidding invitation parameters obtained in the bidding process in MAS. Through reasonable assessing the bidding documents from bid, bidding result determined is obtained, viz. the task assigning scheme. All of the tasks’ assigning optimization is carried out by setting the parameters of genetic-simulated annealing algorithm; the algorithm can search steadily the optimal scheme and overcome the flaws of traditional simulated annealing algorithm such as big undulation and poor astringency. It is found via the analysis of experiment data that the algorithm can improve assignment scheme further rationality and feasibility.

Keywords

Schedule Scheme Production Schedule Resource Agent Assembly Line Balance Task Assigning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yong Liu
    • 1
  • Shujuan Li
    • 1
  • Yan Li
    • 1
  1. 1.School of mechanical & instrumental engineering, Xi’an University of Technology, 710048 Xi’anChina

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