Glen Cancian
ABSTRACT
All road authorities are required to make sound maintenance investment decisions to maximise value from available budgets. As an indication of the complexity of this task, the schedule of pavement maintenance and rehabilitation for a small pavement network consisting of 200 segments, with four treatment alternatives over a planning period of five years has (2004)5 = 1.05 * 1046 possible alternatives. This study investigates the number and quality of solutions obtained by adding additional computing resources to a budget constrained implementation of a Parallel Genetic Algorithm based pavement management treatment scheduling system.
- Fwa, T.F. and Farhan, J., 2012. Optimal multiasset maintenance budget allocation in highway asset management. Journal of Transportation Engineering, 138(10), pp.1179--1187.Google Scholar
Cross Ref
- Kulkarni, R.B. and Miller, R.W., 2003. Pavement management systems: Past, present, and future. Transportation Research Record, 1853(1), pp. 65--71.Google ScholarCross Ref
- Chang, C. and Smith, R.E., 2004, October. The effects of pavement maintenance and rehabilitation strategies on the value of roadway infrastructure. In 6th International Conference on Managing Pavements: The Lessons, The Challenges, The Way Ahead. Queensland Department of Main Roads. Brisbane Queensland, AustraliaGoogle Scholar
- Gao, L. and Zhang, Z., 2008. Robust optimization for managing pavement maintenance and rehabilitation. Transportation research record, 2084(1), pp.55--61.Google Scholar
Index Terms
- Impact of additional hardware resources on a parallel genetic algorithm
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