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Pavement Maintenance Scheduling using Genetic Algorithms

Volume 11, Number 2, March 2015 - Paper 3 - pp. 135-152

C. YANG, R. REMENYTE-PRESCOTT and J. D. ANDREWS

Nottingham Transportation Engineering Centre, University of Nottingham, Nottingham, NG7 2RD, UK

(Received on May 09, 2014, revised on September 04, and September 26, 2014)

Abstract:

This paper presents a new pavement management system (PMS) to achieve the optimal pavement maintenance and rehabilitation (M&R) strategy for a highway network using genetic algorithms (GAs). Optimal M&R strategy is a set of pavement activities that both minimise the maintenance cost of a highway network and maximise the pavement condition of the road sections on the network during a certain planning period. NSGA-II, a multi-objective GA, is employed to perform pavement maintenance optimisation because of its robust search capabilities and constraint handling method that deal with the multi-objective and multi-constrained optimisation problems. In the proposed approach, both deterministic and probabilistic pavement age gain models are utilised for evaluating the evolution of pavement condition over time because of their simplicity of application. The proposed PMS is applied to a case study network that consists of different kinds of road sections. The results obtained indicate that the model is a valuable toolbox for pavement engineers.

 

References: 32

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