الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
In most countries, including Egypt, the funds available are not adequate to cover the costs for all the required improvements, repairs and/ or maintenance projects of roads and highways networks. Further deterioration in highways should be expected in light of existing conditions and funding levels, since the required budgets for such maintenance are much higher than the available funding levels. Therefore agencies should seek more cost- effective preservation methods for highway networks. Accordingly developing a pavement maintenance management system framework in Egypt is of great significance; in order to maximize the overall pavement performance and minimize the overall costs of maintaining and preserving the Egyptian highways and roads network .Pavement Management System can be defined as a systematic approach that provides the engineering and economic analysis tools required by decision makers to make cost-effective selections of Maintenance, Rehabilitation, and Reconstruction (MR&R) strategies on a network basis. Pavement Management system framework includes pavement condition assessment, pavement prediction deterioration model, repair alternatives and strategies, improvement after repair models, pavement maintenance prioritization and repair fund allocation model for planning maintenance actions under different budget and/or performance optimization constraints. Pavement Condition Index (PCI) was deployed as a pavement performance indicator. Markov chain process was applied in this thesis to develop future pavement deterioration prediction model for highways in Egypt, and to forecast the future pavement performance. Transition Probability Matrices(TPM)were generated for two highways in Egypt as a case study; namely, the Alexandria-Cairo agricultural highway; representing the agricultural areas roads conditions in Egypt and the Alexandria-Matrouh north coast highway; representing the coastal roads conditions in Egypt. TPMs were developed based on data made available through the Central Administration for Road Maintenance, at the General Authority for Roads and Bridges and Land Transport (GARBLT). Pavement deterioration prediction models were developed for the two highways examined in the case study for a planning horizon of five time cycles each time cycle comprises two year, for the Alexandria-Cairo agricultural highway the pavement performance PCI state at the initial condition at the base year (2010) was 67.42 and predicted to reach 23.77 after five time cycles each time cycle represents a period from one and half year to two years. On the other hand for the Alexandria-Matrouh north coast highway PCI was 60.05 at the analysis base year (2012) and predicted to reach to 24.77 at the end of the planning horizon of five time cycles and this is due to the deterioration of the pavement with time without taking into consideration any maintenance action undertaken in the highway.Then the results of the models were validated using actual data beyond the planning horizon and the difference between the predicted data and validation data was insignificant at a 95% confidence level. Transition Probability Matrices (TPM) for four categorize of maintenance types(MR&R) were used as performance improvement and repair models. These categories were Routine Maintenance, Minor Rehabilitation, Major Rehabilitation, and Reconstruction according to the Egyptian code for roads maintenance part ten. Major maintenance TPM was developed based on data provided by the Central Administration for Road Maintenance, at the General Authority for Roads and Bridges and Land Transport (GARBLT) for the Alexandria-Cairo agricultural highway and the Alexandria-Matrouh north coast highway. The rest of maintenance types TPMs were identified and assumed according to other literature references and experts engineers judgment as the data set for TPMs generation not available in the GARBLT. The development of pavement management optimization model was important to manage maintenance of highways and roads networks in Egypt. In this thesis, a Pavement Maintenance Management Optimization Model (PMMOM) for highways in Egypt was developed using genetic algorithms optimization application, designed as an add-in for MS Excel™. The models used in PMMOM are developed using the available data at the General Authority for Road Bridges and Land Transport (GARBLT) in Egypt for two major highways, which are Alexandria-Cairo agricultural highway and Alexandria-Matrouh north coast highway, representing the agricultural roads and coastal roads conditions in Egypt, respectively. PMMOM was developed for a planning horizon of five time cycles. Seven budget ( assigned for pavement maintenance) and performance constraint scenarios were demonstrated in the Thesis. The optimization analysis resulting from PMMOM, as shown from the results of SC02 scenario (achieve maximum overall network performance without any budget constraints) , indicates that the maximum average predicted pavement performance which is the pavement conditions states of the highway of for the whole highways network, under unlimited budget conditions, can reach63 .79as an average over the planning horizon of five time cycles, with an overall cost of approximately 2634.4 million EGP over the analysis period. The PMMOM analysis results for the first scenario SC01 (Do-Nothing scenario) show that the maximum average overall network predicted pavement performance is 22.4 with minimum maintenance cost equals zero, which means that no maintenance action will take place for any of the pavement sectors throughout the planning horizon. The results show that the model is sensitive enough to reflect the differences of optimization analysis constraints on the analysis results, and can provide an effective tool for planning maintenance actions under different budget and/or performance optimization constraints.