Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety

This paper presents a multiobjective optimization of post-tensioned concrete road bridges in terms of cost, CO2 emissions, and overall safety factor. A computer tool links the optimization modulus with a set of modules for the finite-element analysis and limit states verification. This is applied for the case study of a three-span continuous post-tensioned box-girder road bridge, located in a coastal region. A multiobjective harmony search is used to automatically search a set of optimum structural solutions regarding the geometry, concrete strength, reinforcing and post-tensioned steel. Diversification strategies are combined with intensification strategies to improve solution quality. Results indicate that cost and CO2 emissions are close to each other for any safety range. A one-euro reduction, involves a 2.34 kg CO2 emissions reduction. Output identifies the best variables to improve safety and the critical limit states. This tool also provides bridge managers with a set of trade-off optimum solutions, which balance their preferences most closely, and meet the requirements previously defined.The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (BRIDLIFE Project: BIA2014-56574-R) and the Research and Development Support Program of Universitat Politecnica de Valencia (PAID-02-15).García Segura, T.; Yepes, V. (2016). Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety. Engineering Structures. 125:325-336. https://doi.org/10.1016/j.engstruct.2016.07.012S32533612

Multi-objective design of post-tensioned concrete road bridges using artificial neural networks

[EN] In order to minimize the total expected cost, bridges have to be designed for safety and durability. This paper considers the cost, the safety, and the corrosion initiation time to design post-tensioned concrete box-girder road bridges. The deck is modeled by finite elements based on problem variables such as the cross-section geometry, the concrete grade, and the reinforcing and post-tensioning steel. An integrated multi-objective harmony search with artificial neural networks (ANNs) is proposed to reduce the high computing time required for the finite-element analysis and the increment in conflicting objectives. ANNs are trained through the results of previous bridge performance evaluations. Then, ANNs are used to evaluate the constraints and provide a direction towards the Pareto front. Finally, exact methods actualize and improve the Pareto set. The results show that the harmony search parameters should be progressively changed in a diversification-intensification strategy. This methodology provides trade-off solutions that are the cheapest ones for the safety and durability levels considered. Therefore, it is possible to choose an alternative that can be easily adjusted to each need.The authors acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness, along with FEDER funding (BRIDLIFE Project: BIA2014-56574-R) and the Research and Development Support Program of Universitat Politecnica de Valencia (PAID-02-15).García-Segura, T.; Yepes, V.; Frangopol, D. (2017). Multi-objective design of post-tensioned concrete road bridges using artificial neural networks. Structural and Multidisciplinary Optimization. 56(1):139-150. doi:10.1007/s00158-017-1653-0S139150561Alberdi R, Khandelwal K (2015) Comparison of robustness of metaheuristic algorithms for steel frame optimization. Eng Struct 102:40–60. doi: 10.1016/j.engstruct.2015.08.012Beume N, Naujoks B, Emmerich M (2007) SMS-EMOA: Multiobjective selection based on dominated hypervolume. Eur J Oper Res 181:1653–1669. doi: 10.1016/j.ejor.2006.08.008Cai H, Aref AJ (2015) A genetic algorithm-based multi-objective optimization for hybrid fiber reinforced polymeric deck and cable system of cable-stayed bridges. Struct Multidiscip Optim 52:583–594. doi: 10.1007/s00158-015-1266-4Cao MS, Pan LX, Gao YF, Novák D, Ding ZC, Lehký D, Li XL (2015) Neural network ensemble-based parameter sensitivity analysis in civil engineering systems. Neural Comput Appl 1–8. doi: 10.1007/s00521-015-2132-4Chatterjee S, Sarkar S, Hore S, Dey N, Ashour AS, Balas VE (2016) Particle swarm optimization trained neural network for structural failure prediction of multistoried RC buildings. Neural Comput Appl. 1–12. doi: 10.1007/s00521-016-2190-2Coello CAC (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Methods Appl Mech Eng 191:1245–1287. doi: 10.1016/S0045-7825(01)00323-1Coello CAC, Lamont GB, Veldhuizen DA Van (2006) Evolutionary algorithms for solving multi-objective problems. Springer-Verlag New York, IncComputers and Structures Inc. (2015) Introduction to CSiBridge. Integrated 3D bridge analysis, design and rating. Berkeley, California, USADeb K (2011) Multi-objective optimisation using evolutionary algorithms: an introduction. In: Wang L, Ng AHC, Deb K (eds) Multi-objective evolutionary optimisation for product design and manufacturing. Springer, London, pp 3–34Deb K, Nain PKS (2007) An evolutionary multi-objective adaptive meta-modeling procedure using artificial neural networks. In: Yang S, Ong Y-S, Jin Y (eds) Evolutionary computation in dynamic and uncertain environments. Springer, Berlin, pp 297–322Dong Y, Frangopol DM, Saydam D (2013) Time-variant sustainability assessment of seismically vulnerable bridges subjected to multiple hazards. Earthq Eng Struct Dyn 42:1451–1467. doi: 10.1002/eqe.2281Emmerich M, Naujoks B (2004) Metamodel assisted multiobjective optimisation strategies and their application in airfoil design. In: Parmee IC (ed) Adaptive computing in design and manufacture VI. Springer, London, pp 249–260European Committee for Standardisation (2003) EN 1991–2:2003. Eurocode 1: Actions on structures-Part 2: Traffic loads bridgesEuropean Committee for Standardisation (2005) EN1992-2:2005. Eurocode 2: Design of concrete structures- Part 2: Concrete Bridge-Design and detailing rules. BrusselsFomento M (2008) EHE-08: code on structural concrete. Ministerio de Fomento, MadridFomento M (2011) IAP-11: code on the actions for the design of road bridges. Ministerio de Fomento, MadridGarcía-Segura T, Yepes V (2016) Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety. Eng Struct 125:325–336. doi: 10.1016/j.engstruct.2016.07.012García-Segura T, Yepes V, Alcalá J (2014a) Life cycle greenhouse gas emissions of blended cement concrete including carbonation and durability. Int J Life Cycle Assess 19:3–12. doi: 10.1007/s11367-013-0614-0García-Segura T, Yepes V, Martí JV, Alcalá J (2014b) Optimization of concrete I-beams using a new hybrid glowworm swarm algorithm. Lat Am J Solids Struct 11:1190–1205. doi: 10.1590/S1679-78252014000700007García-Segura T, Yepes V, Alcalá J, Pérez-López E (2015) Hybrid harmony search for sustainable design of post-tensioned concrete box-girder pedestrian bridges. Eng Struct 92:112–122. doi: 10.1016/j.engstruct.2015.03.015Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. Simulation 76:60–68Giannakoglou KC (2002) Design of optimal aerodynamic shapes using stochastic optimization methods and computational intelligence. Prog Aerosp Sci 38:43–76. doi: 10.1016/S0376-0421(01)00019-7Hare W, Nutini J, Tesfamariam S (2013) A survey of non-gradient optimization methods in structural engineering. Adv Eng Softw 59:19–28. doi: 10.1016/j.advengsoft.2013.03.001Martí JV, Yepes V, González-Vidosa F (2015) Memetic algorithm approach to designing precast-prestressed concrete road bridges with steel fiber reinforcement. J Struct Eng 141:4014114. doi: 10.1061/(ASCE)ST.1943-541X.0001058Martí JV, García-Segura T, Yepes V (2016) Structural design of precast-prestressed concrete U-beam road bridges based on embodied energy. J Clean Prod 120:231–240. doi: 10.1016/j.jclepro.2016.02.024Martinez-Martin FJ, Gonzalez-Vidosa F, Hospitaler A, Yepes V (2012) Multi-objective optimization design of bridge piers with hybrid heuristic algorithms. J Zhejiang Univ Sci A 13:420–432. doi: 10.1631/jzus.A1100304Martini K (2011) Harmony search method for multimodal size, shape, and topology optimization of structural frameworks. J Struct Eng 137:1332–1339. doi: 10.1061/(ASCE)ST.1943-541X.0000378Marti-Vargas JR, Ferri FJ, Yepes V (2013) Prediction of the transfer length of prestressing strands with neural networks. Comput Concr 12:187–209. doi: 10.12989/cac.2013.12.2.187McGee R (1999) Modeling of durability performance of Tasmanian bridges. In: Melchers R, M.G S (eds) Applications of statistics and probability: civil engineering, reliability and risk analysis. A.A. Balkema, Rotterdam, pp 297–306Papadakis VG, Roumeliotis AP, Fardis MN, Vagenas CG (1996) Mathematical modelling of chloride effect on concrete du-rability and protection measures. In: Dhir RK, Jones MR (eds) Concrete repair, rehabilitation and protection. E&FN Spon, London, pp 165–174Paya I, Yepes V, González-Vidosa F, Hospitaler A (2008) Multiobjective optimization of reinforced concrete building frames by simulated annealing. Comput Civ Infrastruct Eng 23:596–610. doi: 10.1111/j.1467-8667.2008.00561.xProtopapadakis E, Schauer M, Pierri E et al (2016) A genetically optimized neural classifier applied to numerical pile integrity tests considering concrete piles. Comput Struct 162:68–79. doi: 10.1016/j.compstruc.2015.08.005Quaglia CP, Yu N, Thrall AP, Paolucci S (2014) Balancing energy efficiency and structural performance through multi-objective shape optimization: Case study of a rapidly deployable origami-inspired shelter. Energ Build 82:733–745. doi: 10.1016/j.enbuild.2014.07.063Ricart J, Hüttemann G, Lima J, Barán B (2011) Multiobjective harmony search algorithm proposals. Electron Notes Theor Comput Sci 281:51–67. doi: 10.1016/j.entcs.2011.11.025Sanad A, Saka MP (2001) Prediction of ultimate shear strength of reinforced-concrete deep beams using neural networks. J Struct Eng 127:818–828. doi: 10.1061/(ASCE)0733-9445(2001)127:7(818)Sarma KC, Adeli H (1998) Cost optimization of concrete structures. J Struct Eng 124:570–578. doi: 10.1061/(ASCE)0733-9445(1998)124:5(570)Shi X (2016) Experimental and modeling studies on installation of arc sprayed Zn anodes for protection of reinforced concrete structures. Front Struct Civ Eng 10:1–11. doi: 10.1007/s11709-016-0312-7Sreehari VM, Maiti DK (2016) Buckling load enhancement of damaged composite plates under hygrothermal environment using unified particle swarm optimization. Struct Multidiscip Optim 1–11. doi: 10.1007/s00158-016-1498-yTorres-Machi C, Chamorro A, Pellicer E et al (2015) Sustainable pavement management: Integrating economic, technical, and environmental aspects in decision making. Transp Res Rec J Transp Res Board 2523:56–63. doi: 10.3141/2523-07Vu KAT, Stewart MG (2000) Structural reliability of concrete bridges including improved chloride-induced corrosion models. Struct Saf 22:313–333. doi: 10.1016/S0167-4730(00)00018-7Xu H, Gao XZ, Wang T, Xue K (2010) Harmony search optimization algorithm: application to a reconfigurable mobile robot prototype. In: Geem ZW (ed) Recent advances in harmony search algorithm. Springer, Berlin, pp 11–22Yepes V, García-Segura T, Moreno-Jiménez JM (2015a) A cognitive approach for the multi-objective optimization of RC structural problems. Arch Civ Mech Eng 15:1024–1036. doi: 10.1016/j.acme.2015.05.001Yepes V, Martí JV, García-Segura T (2015b) Cost and CO2 emission optimization of precast–prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm. Autom Constr 49:123–134. doi: 10.1016/j.autcon.2014.10.013Zavala GR, Nebro AJ, Luna F, Coello Coello CA (2013) A survey of multi-objective metaheuristics applied to structural optimization. Struct Multidiscip Optim 49:537–558. doi: 10.1007/s00158-013-0996-4Zavrtanik N, Prosen J, Tušar M, Turk G (2016) The use of artificial neural networks for modeling air void content in aggregate mixture. Autom Constr 63:155–161. doi: 10.1016/j.autcon.2015.12.009Zitzler E, Thiele L (1998) Multiobjective optimization using evolutionary algorithms - a comparative case study. In: Eiben AE, Bäck T, Schoenauer M, Schwefel H-P (eds) Conference on parallel problem solving from nature- PPSN V. Springer Berlin Heidelberg, Amsterdam, The Netherlands, pp 292–30

On the role of metaheuristic optimization in bioinformatics

Metaheuristic algorithms are employed to solve complex and large-scale optimization problems in many different fields, from transportation and smart cities to finance. This paper discusses how metaheuristic algorithms are being applied to solve different optimization problems in the area of bioinformatics. While the text provides references to many optimization problems in the area, it focuses on those that have attracted more interest from the optimization community. Among the problems analyzed, the paper discusses in more detail the molecular docking problem, the protein structure prediction, phylogenetic inference, and different string problems. In addition, references to other relevant optimization problems are also given, including those related to medical imaging or gene selection for classification. From the previous analysis, the paper generates insights on research opportunities for the Operations Research and Computer Science communities in the field of bioinformatics

A Multi-Agent Architecture for the Design of Hierarchical Interval Type-2 Beta Fuzzy System

This paper presents a new methodology for building and evolving hierarchical fuzzy systems. For the system design, a tree-based encoding method is adopted to hierarchically link low dimensional fuzzy systems. Such tree structural representation has by nature a flexible design offering more adjustable and modifiable structures. The proposed hierarchical structure employs a type-2 beta fuzzy system to cope with the faced uncertainties, and the resulting system is called the Hierarchical Interval Type-2 Beta Fuzzy System (HT2BFS). For the system optimization, two main tasks of structure learning and parameter tuning are applied. The structure learning phase aims to evolve and learn the structures of a population of HT2BFS in a multiobjective context taking into account the optimization of both the accuracy and the interpretability metrics. The parameter tuning phase is applied to refine and adjust the parameters of the system. To accomplish these two tasks in the most optimal and faster way, we further employ a multi-agent architecture to provide both a distributed and a cooperative management of the optimization tasks. Agents are divided into two different types based on their functions: a structure agent and a parameter agent. The main function of the structure agent is to perform a multi-objective evolutionary structure learning step by means of the Multi-Objective Immune Programming algorithm (MOIP). The parameter agents have the function of managing different hierarchical structures simultaneously to refine their parameters by means of the Hybrid Harmony Search algorithm (HHS). In this architecture, agents use cooperation and communication concepts to create high-performance HT2BFSs. The performance of the proposed system is evaluated by several comparisons with various state of art approaches on noise-free and noisy time series prediction data sets and regression problems. The results clearly demonstrate a great improvement in the accuracy rate, the convergence speed and the number of used rules as compared with other existing approaches

Soft Computing Techiniques for the Protein Folding Problem on High Performance Computing Architectures

The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.This work is jointly supported by the FundaciónSéneca (Agencia Regional de Ciencia y Tecnología, Región de Murcia) under grants 15290/PI/2010 and 18946/JLI/13, by the Spanish MEC and European Commission FEDER under grant with reference TEC2012-37945-C02-02 and TIN2012-31345, by the Nils Coordinated Mobility under grant 012-ABEL-CM-2014A, in part financed by the European Regional Development Fund (ERDF). We also thank NVIDIA for hardware donation within UCAM GPU educational and research centers.Ingeniería, Industria y Construcció

Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems

[EN] This document is intended to be a presentation of the Special Issue "Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems". The final aim of this Special Issue is to propose a suitable framework supporting insightful hydraulic mechanisms to aid the decision-making processes of water utility managers and practitioners. Its 18 peer-reviewed articles present as varied topics as: water distribution system design, optimization of network performance assessment, monitoring and diagnosis of pressure pipe systems, optimal water quality management, and modelling and forecasting water demand. Overall, these articles explore new research avenues on urban hydraulics and hydroinformatics, showing to be of great value for both Academia and those water utility stakeholders.Herrera Fernández, AM.; Meniconi, S.; Alvisi, S.; Izquierdo Sebastián, J. (2018). Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems. Water. 10(4):1-7. https://doi.org/10.3390/w10040440S1710

A Global Optimisation Toolbox for Massively Parallel Engineering Optimisation

A software platform for global optimisation, called PaGMO, has been developed within the Advanced Concepts Team (ACT) at the European Space Agency, and was recently released as an open-source project. PaGMO is built to tackle high-dimensional global optimisation problems, and it has been successfully used to find solutions to real-life engineering problems among which the preliminary design of interplanetary spacecraft trajectories - both chemical (including multiple flybys and deep-space maneuvers) and low-thrust (limited, at the moment, to single phase trajectories), the inverse design of nano-structured radiators and the design of non-reactive controllers for planetary rovers. Featuring an arsenal of global and local optimisation algorithms (including genetic algorithms, differential evolution, simulated annealing, particle swarm optimisation, compass search, improved harmony search, and various interfaces to libraries for local optimisation such as SNOPT, IPOPT, GSL and NLopt), PaGMO is at its core a C++ library which employs an object-oriented architecture providing a clean and easily-extensible optimisation framework. Adoption of multi-threaded programming ensures the efficient exploitation of modern multi-core architectures and allows for a straightforward implementation of the island model paradigm, in which multiple populations of candidate solutions asynchronously exchange information in order to speed-up and improve the optimisation process. In addition to the C++ interface, PaGMO's capabilities are exposed to the high-level language Python, so that it is possible to easily use PaGMO in an interactive session and take advantage of the numerous scientific Python libraries available.Comment: To be presented at 'ICATT 2010: International Conference on Astrodynamics Tools and Techniques