Optimization techniques are commonly used as aids in making road maintenance management decisions and the present paper demonstrates the applicability of genetic algorithms as an optimization tool. Genetic algorithms are search algorithms that efficiently exploit historical information to locate search points with improved performance. The theoretical basis and operations of genetic algorithms are presented and a computer model formulated on genetic algorithm operating principles. The model, known as PAVENET, is described in detail. Analyses are conducted to illustrate the characteristics of important operating parameters of PAVENET, which include: 1) parent pool size, 2) mutation rate in offspring generation, and 3) ranking system for offspring selection. A sample problem provides a look at the convergence process as analyzed by the PAVENET program; recommendations on the choice of operating parameters are made.


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  • Accession Number: 00669215
  • Record Type: Publication
  • Files: TRIS, ATRI
  • Created Date: Oct 31 1994 12:00AM