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G. Cancian¹, G. Chai¹ and W. Pullan²

¹School of Engineering, Griffith University Gold Coast Campus, Parklands, Queensland, Australia
²School of Information Communication Technology, Griffith University Gold Coast Campus, Parklands, Queensland, Australia

doi:10.4203/ccp.109.31

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G. Cancian, G. Chai, W. Pullan, "Budget Constrained Pavement Maintenance Scheduling using a Parallel Genetic Algorithm", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 31, 2015. doi:10.4203/ccp.109.31

Keywords: pavement management systems, maintenance selection, rehabilitation treatment selection, optimisation, genetic algorithms, parallel genetic algorithms.

Summary

Road authorities around the world are presently shifting their focus from the construction of new assets to the maintenance of existing pavement networks. These road authorities are often challenged by a common requirement to produce a cost effective schedule of programmed maintenance and rehabilitation treatments within an increasingly limited budget. To this end, the majority of road authorities employee a pavement management system to 'assist in the funding allocation process' and to help asset managers 'select the best preservation program, decide which preservation treatment to use, and where and when to apply it to maximise the use of available resources'. This paper presents a budget constrained implementation of a parallel genetic algorithm (PGA) based pavement management treatment scheduling system along with results from computational experiments generated using a road network of 1,335 road segments. Incremented annual budget constraints are evaluated in addition to the effect of increasing the number of slave processors in the parallel implementation. The resulting PGA produced an optimised pavement maintenance and rehabilitation program of works that satisfies an annual budget constraint.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 109 PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping Paper 31 Budget Constrained Pavement Maintenance Scheduling using a Parallel Genetic Algorithm G. Cancian¹, G. Chai¹ and W. Pullan² ¹School of Engineering, Griffith University Gold Coast Campus, Parklands, Queensland, Australia ²School of Information Communication Technology, Griffith University Gold Coast Campus, Parklands, Queensland, Australia doi:10.4203/ccp.109.31 purchase the full-text of this paper Full Bibliographic Reference for this paper G. Cancian, G. Chai, W. Pullan, "Budget Constrained Pavement Maintenance Scheduling using a Parallel Genetic Algorithm", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 31, 2015. doi:10.4203/ccp.109.31 Keywords: pavement management systems, maintenance selection, rehabilitation treatment selection, optimisation, genetic algorithms, parallel genetic algorithms. Summary Road authorities around the world are presently shifting their focus from the construction of new assets to the maintenance of existing pavement networks. These road authorities are often challenged by a common requirement to produce a cost effective schedule of programmed maintenance and rehabilitation treatments within an increasingly limited budget. To this end, the majority of road authorities employee a pavement management system to 'assist in the funding allocation process' and to help asset managers 'select the best preservation program, decide which preservation treatment to use, and where and when to apply it to maximise the use of available resources'. This paper presents a budget constrained implementation of a parallel genetic algorithm (PGA) based pavement management treatment scheduling system along with results from computational experiments generated using a road network of 1,335 road segments. Incremented annual budget constraints are evaluated in addition to the effect of increasing the number of slave processors in the parallel implementation. The resulting PGA produced an optimised pavement maintenance and rehabilitation program of works that satisfies an annual budget constraint. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £50 +P&P)
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