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Network‐Level Road Pavement Maintenance and Rehabilitation Scheduling for Optimal Performance Improvement and Budget Utilization
Author(s) -
Gao Lu,
Xie Chi,
Zhang Zhanmin,
Waller S. Travis
Publication year - 2012
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.2011.00733.x
Subject(s) - pavement management , weighting , parametric statistics , computer science , job shop scheduling , scheduling (production processes) , mathematical optimization , pareto principle , budget constraint , ranking (information retrieval) , set (abstract data type) , operations research , engineering , transport engineering , mathematics , schedule , artificial intelligence , medicine , statistics , neoclassical economics , economics , radiology , programming language , operating system
This article discusses how to efficiently and completely solve a bi‐objective pavement maintenance and rehabilitation‐scheduling problem, which aims at optimizing two objectives of pavement condition improvement and budget utilization in a simultaneous manner. This problem may be addressed by the weighting method, constraint method, ranking method, and various metaheuristic methods. However, none of these methods can guarantee the complete Pareto‐optimal solution set, which would potentially lead to suboptimal decisions. In this article, a parametric method is suggested to solve the bi‐objective pavement maintenance and rehabilitation‐scheduling problem. The effectiveness and efficiency of the parametric method is investigated and demonstrated through a case study using the real‐world data set from the Dallas District's Pavement Management Information System. A performance comparison between the widely used weighting method and the parametric method clearly justifies the computational advantages of the parametric method.