TY - JOUR

T1 - A network flow model for clustering segments and minimizing total maintenance and rehabilitation cost

AU - Wang, I. Lin

AU - Tsai, Yi Chang James

AU - Li, Feng

N1 - Funding Information:
The authors would like to thank the Georgia Department of Transportation for providing the data to support our study. I-Lin Wang was partially supported by the National Science Council of Taiwan under Grant NSC98-2410-H-006-015-MY2.

PY - 2011/5

Y1 - 2011/5

N2 - Because of shrinking budgets, transportation agencies are facing severe challenges in the preservation of deteriorating pavements. There is an urgent need to develop a methodology that minimizes maintenance and rehabilitation (M&R) cost. To minimize total network M&R cost of clustering pavement segments, we propose an integer programming model similar to an uncapacitated facility location problem (UFLP) that clusters pavement segments contiguously. Based on the properties of contiguous clustered pavement segments, we have transformed the clustering problem into an equivalent network flow problem in which each possible clustering corresponds to a path in the proposed acyclic network model. Our proposed shortest-path algorithm gives an optimal clustering of segments that can be calculated in a time polynomial to the number of segments. Computational experiments indicate our proposed network model and algorithm can efficiently deal with real-world spatial clustering problems.

AB - Because of shrinking budgets, transportation agencies are facing severe challenges in the preservation of deteriorating pavements. There is an urgent need to develop a methodology that minimizes maintenance and rehabilitation (M&R) cost. To minimize total network M&R cost of clustering pavement segments, we propose an integer programming model similar to an uncapacitated facility location problem (UFLP) that clusters pavement segments contiguously. Based on the properties of contiguous clustered pavement segments, we have transformed the clustering problem into an equivalent network flow problem in which each possible clustering corresponds to a path in the proposed acyclic network model. Our proposed shortest-path algorithm gives an optimal clustering of segments that can be calculated in a time polynomial to the number of segments. Computational experiments indicate our proposed network model and algorithm can efficiently deal with real-world spatial clustering problems.

UR - http://www.scopus.com/inward/record.url?scp=79952627856&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79952627856&partnerID=8YFLogxK

U2 - 10.1016/j.cie.2011.01.001

DO - 10.1016/j.cie.2011.01.001

M3 - Article

AN - SCOPUS:79952627856

VL - 60

SP - 593

EP - 601

JO - Computers and Industrial Engineering

JF - Computers and Industrial Engineering

SN - 0360-8352

IS - 4

ER -