MAINTENANCE BUDGET ALLOCATION MODEL USING MULTI OBJECTIVE PROGRAMMING

للكاتبين

M. Basher Hassoun, Essam Sharaf, A.A.Gadallah, Gamal Saleh Darwish

Ministry of Transportation Damascus Syria

Gulf Engineering House, Rriyadh Saudi Arabia

public works Department y, Faculty of Engineering , Cairo Universit

ABSTRACT:

Because the length of the road network gradually increases, planning for network expenditure

becomes very important to support the economy of a country. The problem of highway

maintenance to keep the network in a serviceable condition becomes an important issue. One

of the most important activities of pavement maintenance management systems (PMMS) is to

establish priorities and funding programs of maintenance for a road network to obtain the

most cost-effective utilization of limited funds. So, the question of what is an optimal

allocation of total available funds to maintenance and rehabilitation is very important

especially if it is extended to include the specific links to be maintained within each activity

type. The scope of the paper focuses on development of optimization model for optimal funds

allocation for highway maintenance activities using Goal and Linear programming for

handling multi-objective optimization problems [Hassoun 1999]. The developed model is

very powerful and flexible tool for pavement engineers and decision-makers and can be

effectively used in the planning and budget estimation activities. The methodology of the

model enables the decision-makers to address issues, such as under and over achievement

among system objectives, highway classes, and activity types. The model is capable of

analyzing the impact of different policy on the needs and performance of highway systems.

The output of the model is in the form of optimum set of suggested projects to be performed

to reach the required improvement in each objective as assigned in the priority levels. The

model can address the environmental aspects as separate objective. The inclusion of such an

objective can lead to a tremendous amount of pollution decrease.

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