Road‐Maintenance Planning Using Genetic Algorithms. II: Analysis

Abstract

This paper analyzes the road‐maintenance planning problem at network level using a genetic‐algorithm program, PAVENET, which is a computer model developed to serve as an analytical tool for pavement maintenance engineers. The effects on road‐maintenance programs of the following parameters are analyzed: (1) Network parameters, such as the age structure of pavements; (2) maintenance‐policy parameters, such as the choice of warning levels; and (3) resource parameters, such as the level of budget available. Examples are presented to illustrate how the pavement age structure of a road network affects road‐maintenance planning, and how the PAVENET program can be used to formulate a maintenance strategy to regulate long‐term maintenance demand. Also illustrated are the adverse long‐term effects of poor budget planning in the initial years. Analyses are presented to demonstrate the application of the PAVENET program to the selection of maintenance warning levels. Finally, examples are given to study the effect of the type of pavement and distress function on maintenance planning.