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contributor authorMohamed Elmasry; Tarek Zayed; Alaa Hawari
date accessioned2019-03-10T12:01:20Z
date available2019-03-10T12:01:20Z
date issued2019
identifier other%28ASCE%29CO.1943-7862.0001599.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4254663
description abstractInspection activities play an important role in the operation and maintenance (O&M) strategy in municipalities. Efficient O&M strategies can help in making informed decisions based on the actual condition of pipelines collected from inspection activities. Municipalities are in dire need of optimizing inspection activities due to the competitive needs for the large number of deteriorated sewer pipelines and limited budget allocated for inspections. This paper presents an optimization model for inspection of deteriorated sewer pipelines using multiobjective optimization technique for which time, cost, and number of inspected sections are optimized using mixed integer linear programming (MILP). The general algebraic modeling system (GAMS) is used to reduce the computational complexity of the proposed optimization model. A case study for an existing sewage network in the city of Doha, Qatar, is used to demonstrate the capabilities of the optimization model. The results obtained from implementing the optimization model showed an enhancement of 25.7, 44.4, and 6.5% for time, cost, and number of sections inspected when compared with the results for the same model using the genetic algorithm (GA). Additionally, a cost-saving of 68% could be achieved if the proposed optimization model was deployed instead of the current inspection practices carried out by the municipalities in Doha, Qatar. It is expected that the proposed model could be used to reduce both the cost and time of inspection, especially in cases of limited budget and work forces.
publisherAmerican Society of Civil Engineers
titleMulti-Objective Optimization Model for Inspection Scheduling of Sewer Pipelines
typeJournal Paper
journal volume145
journal issue2
journal titleJournal of Construction Engineering and Management
identifier doi10.1061/(ASCE)CO.1943-7862.0001599
page04018129
treeJournal of Construction Engineering and Management:;2019:;Volume ( 145 ):;issue: 002
contenttypeFulltext


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