Application of Improved Genetic Algorithm to Traffic Equipment’s Rush-Repair in the Wartime

Abstract:

Traffic equipment’s rush-repairs in the wartime optimal assignment model was established. Combining the features of Job-shop scheduling problems, described the complexity of this problem. In order to find global optimal results efficiently, traditional GAs were improved and used for study of this problem. Though genetic algorithm, as an effective global search method, had been used in many problems, it had the disadvantages of slow convergence and poor stability in practical engineering. In order to overcome these problems, an improved genetic algorithm was proposed in terms of creation of the initial population, genetic operators, etc. At the end, the steps to solve the optimal model were put forward. With this model we had obtained ideal results. This shows that the method can offer a scientific and effective support for a decision maker in command automation of the traffic equipment’s rush-repairs in battlefield.

• Periodical: Advanced Materials Research (Volumes 605-607)
• Pages: 49-52
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.605-607.49
• Online since: December 2012
• Authors: Geng Sheng Wu, Qi Yi Zhang
• Keywords: Genetic Algorithm (GA), Rush-Repair, Traffic Equipment

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