Effective Network Level Optimization for Bridges Maintenance

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.

Minimizing the impact of vacating instream storage of a multi-reservoir system: a tradeoff study of water supply and empty flushing

Reservoir operator does not favor storage above a certain level in situations such as the pre-release operation prior to a flood, scheduled engineering constructions or mechanical excavations of sediments in the impoundments, drawdown and empty flushing, etc. This paper selects the last of which as the case study, and a method is presented to promote the feasibility of emptying reservoir storage. The impact of emptying reservoir on water supply is minimized through appropriate joint operation in a multi-reservoir system, where drawdown and empty flushing is carried out in a primary reservoir and the other reservoirs provide backup water for supply. This method prioritizes allocating the storage in the primary reservoir for water supply during specific periods prior to its empty. If the storage of every reservoir achieves its predefined conditions, drawdown of the primary reservoir is activated and followed by empty flushing. Previously preserved storage in the other reservoirs ensures adequate water supply during the periods of emptying the primary reservoir. Flushing of the primary reservoir is continued until either the accumulative released water exceeds the specified volume, storage in the backup reservoirs drops below the pre-defined threshold, or the inflow to the primary reservoir recedes from the flood peak to be below the releasing capacity of outlets. This behavior is simulated and linked with a nonlinear optimization algorithm to calibrate the optimal parameters defining the activation and termination of empty flushing. The optimized strategy limits the incremental water shortage within the acceptable threshold and maximizes the expected benefits of emptying reservoir.

Reliable Intervals Method in Decision-Based Support Models for Group Decision-Making

In this paper, a methodology to derive reliable intervals for multiplicative preference relations (or pairwise comparison matrices) satisfying consistency and consensus indexes is introduced. Our approach is proposed via a combination of numerical algorithms and a nonlinear optimization algorithm. A synthesis of reliable intervals is achieved, where group decision makers show evidence of these intervals to express flexibility in the manner of their preferences, while accomplishing some a priori decision targets, rules and advice given by their current framework. The algorithms are applied to some examples in order to illustrate our results and compare them with other methodologies.

Assessment of optimal empty flushing strategies in a multi-reservoir system

Empty flushing is the most effective approach to evacuate the deposited sediments in the reservoir. However, emptying reservoir essentially conflicts with its water supply operation, thus a feasible strategy of empty flushing should prevent significant increase of water shortage risks. This paper presents a framework of performing empty flushing in a multi-reservoir system, where flushing is carried out in a primary reservoir and the other reservoirs provide backup storage for stable water supply during flushing. A network flow programming-based model is employed to simulate daily joint operation of reservoirs. During the simulation, if the storage of each reservoir achieves the predefined conditions, drawdown and empty flushing of the primary reservoir is activated. During the flushing, if the storage of any reservoir reaches the pre-defined thresholds, then the flushing operation is halted and the simulation switches back to the regular joint operation mode. This simulation model is linked with a nonlinear optimization algorithm to calibrate the optimal parameters. The optimized strategy yields a maximum amount of flushed sediments, while the incremental water shortage is controlled within the acceptable threshold.