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Heuristics in optimal detailed design of precast road bridges

Yepes V., Martí J. V., García-Segura T., González-Vidosa F.

Archives of Civil and Mechanical Engineering

2017

Vol. 17, no. 4

738--749

This paper deals with the cost optimization of road bridges consisting of concrete slabs prepared in situ and two precast-prestressed U-shaped beams of self-compacting concrete. It shows the efficiency of four heuristic algorithms applied to a problem of 59 discrete variables. The four algorithms are the Descent Local Search (DLS), a threshold accepting algorithm with mutation operation (TAMO), the Genetic Algorithm (GA), and the Memetic Algorithm (MA). The heuristic optimization algorithms are applied to a bridge with a span length of 35 m and a width of 12 m. A performance analysis is run for the different heuristics, based on a study of Pareto optimal solutions between execution time and efficiency. The best results were obtained with TAMO for a minimum cost of 104 184€. Among the key findings of the study, the practical use of these heuristics in real cases stands out. Furthermore, the knowledge gained from the investigation of the algorithms allows a range of values for the design optimization of such structures and pre-dimensioning of the variables to be recommended.

A cognitive approach for the multi-objective optimization of RC structural problems

Yepes V., García-Segura T., Moreno-Jiménez J. M.

Archives of Civil and Mechanical Engineering

2015

Vol. 15, no. 4

1024--1036

This paper proposes a cognitive approach for analyzing and reducing the Pareto optimal set for multi-objective optimization (MOO) of structural problems by means of jointly incorporating subjective and objective aspects. The approach provides improved knowledge on the decision-making process and makes it possible for the actors involved in the resolution process and its integrated systems to learn from the experience. The methodology consists of four steps: (i) the construction of the Pareto set using MOO models; (ii) the filtering of the Pareto set by compromise programming methods; (iii) the selection of the preferred solutions, utilizing the relative importance of criteria and the Analytic Hierarchy Process (AHP); (iv) the extraction of the relevant knowledge derived from the resolution process. A case study on the reinforced concrete (RC) I-beam has been included to illustrate the methodology. The compromise solutions are obtained through the objectives of economic feasibility, structural safety, and environmental sustainability criteria. The approach further identifies the patterns of behavior and critical points of the resolution process which reflect the relevant knowledge derived from the cognitive perspective. Results indicated that the solutions selected increased the number of years of service life. The procedure produced durable and ecological structures without price trade-offs.