Enhanced Simulated Annealing Techniques for Multiprocessor Scheduling
The problem of multiprocessor scheduling can be stated as scheduling a general task graph on a multiprocessor system such that a set of performance criteria will be optimized. This study investigates the use of near optimal scheduling strategies in multiprocessor scheduling problem. The multiprocessor scheduling problem is modeled and simulated using five different simulated annealing algorithms and a genetic algorithm. In this paper, the comparison of the simulation results of the simulated annealing algorithm, the modified versions of simulated annealing algorithms, and the genetic algorithm is presented. In addition, results of sensitivity analysis on the simulated annealing algorithm, the modified simulated annealing algorithms, and the genetic algorithm are included.  1999 AAAI. All rights reserved. (http://www.aaai.org)
In the overall ownership cost of enterprise system, the maintenance cost consists of a major percentage. During the lifetime of an enterprise system, process customization is the most frequent maintenance efforts. However, current processing method has limited scalability and efficiency. In this case study, we explained how a scalable and efficient customization processing method was implemented. This method used the carbon emission trading mechanism to facilitate the cost benefit analysis of customization request. It also used distributed processing principle to improve the overall processing efficiency. Feedback from a pilot implementation in a large manufacturer included.