www.ijecs.in International Journal Of Engineering And Computer Science Volume 9 Issue 09 September 2020, Page No. 25161-25174 ISSN: 2319-7242 DOI: 10.18535/ijecs/v9i09.4525 Sofiane HADJI, IJECS Volume 09 Issue 09 September, 2020 Page No. 25161-25174 Page 25161 Effective Network Level Optimization for Bridges Maintenance Sofiane HADJI Scientific Director, SIXENSE Engineering (Vinci Group), 22-24 Rue Lavoisier - 92000 Nanterre, France Abstract: The objective of this paper is to present an effective new methodology to optimize the maintenance costs of bridges stock. Optimization takes place at the network level and not in a project level (bridge by bridge). The dynamics of passage between bridges condition state (from 1 to 5) is achieved by the Markov chains probabilistic method. The Markov transition matrix is determined either by ratios of total areas and areas degraded annually, or by the resolution of an optimization problem. In the latter case, the nonlinear optimization algorithm SQP (Sequanciel Quadratic Programming) is developed. A bridge maintenance matrix is introduced in the calculation of the repair cost. The originality of our approach is to parameterize this matrix by introducing the different optimization variables of the problem. Finally, the cost function to be optimized annually is calculated and optimized by a genetic algorithm. This cost function represents the cost of maintaining the entire asset. Keywords: Markov chain simulation; Genetic SQP optimization; Bridge deterioration modeling; Transition probability matrix, Maintenance matrix, Network level. 1. Introduction An efficient maintained transportation system is a fundamental factor for the economic and social developments. For managing highway bridges, decision makers require efficient and practical decision making techniques. In a context of limited bridge management budget, it is important to determine the most effective breakdown of financial resources over the different structures of a bridge network. Infrastructure management systems have been developed to apply the life-cycle costing approach to optimize maintenance decisions at both network and project levels and achieving network/project performance requirements under financial constraints [12, 13]. A strong interest was expressed within the managers for an objective analysis at the network level [6, 7] of the compromises between performance and financing. In fact, an approach at the network level initially allows us to directly have the different financial investments ratios without worrying about repairs for each bridge (project level). Once the right financial ratios have been optimized, one can scheduling maintenance for each bridge over the simulation duration [4, 5]. The objective of this article is to provide infrastructure managers with a simple and effective decision-making tool capable of optimizing bridges maintenance at the macro level. The formulation is based on the probabilities of Markov chains, maintenance matrix, SQP and genetic optimization methods. The originality of our approach relates to the search for the optimum through the bridge maintenance matrix which is not predefined. The construction of this tool requires the development of the following elements:  Network condition rating system  Deterioration models for prediction of bridge aging based on the condition ratings  Cost model  Maintenance model  Appropriate maintenance cost function and its optimization 2. Condition rating The IQOA scoring system in France (quality assessment of engineering structures) was developed to give each year a global assessment of the state of the bridge stock managed by the French Highway Agency or by private agencies. The bridge stock is assessed every 3 years (i.e., by applying IQOA inspections annually on 1/3 of the total number of assets). The IQOA scoring (table 1) contain five level score 1 (the best state) to 5