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Mathematical Problems in Engineering
Volume 2014, Article ID 151394, 13 pages
Research Article

Simulated Annealing Algorithm Combined with Chaos for Task Allocation in Real-Time Distributed Systems

College of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, China

Received 17 May 2014; Revised 24 July 2014; Accepted 3 August 2014; Published 14 August 2014

Academic Editor: Jun-Juh Yan

Copyright © 2014 Wenbo Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper addresses the problem of task allocation in real-time distributed systems with the goal of maximizing the system reliability, which has been shown to be NP-hard. We take account of the deadline constraint to formulate this problem and then propose an algorithm called chaotic adaptive simulated annealing (XASA) to solve the problem. Firstly, XASA begins with chaotic optimization which takes a chaotic walk in the solution space and generates several local minima; secondly XASA improves SA algorithm via several adaptive schemes and continues to search the optimal based on the results of chaotic optimization. The effectiveness of XASA is evaluated by comparing with traditional SA algorithm and improved SA algorithm. The results show that XASA can achieve a satisfactory performance of speedup without loss of solution quality.