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Showing 20 results for Hybrid

Mohammad T. Dastorani, Nigel G. Wright,
Volume 2, Issue 3 (9-2004)
Abstract

In this study, an artificial neural networks (ANN) was used to optimise the results obtained from a hydrodynamic model of river flow prediction. The study area is Reynolds Creek Experimental Watershed in southwest Idaho, USA. First a hydrodynamic model was constructed to predict flow at the outlet using time series data from upstream gauging sites as boundary conditions. The model, then was replaced with an ANN model using the same inputs. Finally a hybrid model was employed in which the error of the hydrodynamic model is predicted using an ANN model to optimise the outputs. Simulations were carried out for two different conditions (with and without data from a recently suspended gauging site) to evaluate the effect of this suspension in hydrodynamic, ANN and the hybrid model. Using ANN in this way, the error produced by the hydrodynamic model was predicted and thereby, the results of the model were improved.
H. Oucief, M.f. Habita, B. Redjel,
Volume 4, Issue 2 (6-2006)
Abstract

In most cases, fiber reinforced self-compacting concrete (FRSCC) contains only one type of fiber. The use of two or more types of fibers in a suitable combination may potentially not only improve the overal properties of self-compacting concrete, but may also result in performance synergie. The combining of fibers, often called hybridization, is investigated in this paper for a cimentetious matrix. Control, single, two fibers hybrid composites were cast using different fiber type steel and polypropylene with different sizes. Flexural toughness tests were performed and results were extensively analysed to identify synergy, if any, associated with various fiber combinations. Based on various analysis schemes, the paper identifies fiber combinations that demonstrate maximum synergy in terms of flexural toughness.
Abbas Afshar, S. Ali Zahraei, M. A. Marino,
Volume 6, Issue 1 (3-2008)
Abstract

In a large scale cyclic storage system ,as the number of rule parameters and/or number of operating period increase, general purpose gradient-based NLP solvers and/or genetic algorithms may loose their merits in finding optimally feasible solution to the problem. In these cases hybrid GA which decomposes the main problem into two manageable sub-problems with an iterative scheme between GA and LP solvers may be considered as a sound alternative This research develops a hybrid GA-LP algorithm to optimally design and operate a nonlinear, non-convex, and large scale lumped cyclic storage system. For optimal operation of the system a set of operating rules are derived for joint utilization of surface and groundwater storage capacities to meet a predefined demand with minimal construction and operation cost over a 20 seasonal planning period. Performance of the proposed model is compared with a non-cyclic storage system. The management model minimizes the present value of the design and operation cost of the cyclic and non-cyclic systems under specified and governing constraints, employing the developed GA-LP hybrid model. Results show that cyclic storage dominates non-cyclic storage system both in cost and operation flexibility.
Shahriar Afandizadeh, Jalil Kianfar,
Volume 7, Issue 1 (3-2009)
Abstract

This paper presents a hybrid approach to developing a short-term traffic flow prediction model. In this

approach a primary model is synthesized based on Neural Networks and then the model structure is optimized through

Genetic Algorithm. The proposed approach is applied to a rural highway, Ghazvin-Rasht Road in Iran. The obtained

results are acceptable and indicate that the proposed approach can improve model accuracy while reducing model

structure complexity. Minimum achieved prediction r2 is 0.73 and number of connection links at least reduced 20%

as a result of optimization.


A. Kaveh, H. Nasr Esfahani,
Volume 10, Issue 1 (3-2012)
Abstract

In this paper the conditional location problem is discussed. Conditional location problems have a wide range of applications

in location science. A new meta-heuristic algorithm for solving conditional p-median problems is proposed and results are

compared to those of the previous studies. This algorithm produces much better results than the previous formulations.


Zh. Zhang, J. Xu,
Volume 11, Issue 1 (3-2013)
Abstract

To improve the construction efficiency of the Longtan Hydropower Project, this paper studies the multi-mode resourceconstrained project scheduling problem in its Drilling Grouting Construction Project. A multiple objective decision making model with bi-random coefficients is first proposed for this practical problem to cope with hybrid uncertain environment where twofold randomness exists. Subsequently, to deal with the uncertainties, the chance constraint operator is introduced and the equivalent crisp model is derived. Furthermore, the particular nature of our model motivates us to develop particle swarm ptimization algorithm for the equivalent crisp model. Finally, the results generated by computer highlight the performances of the proposed model and algorithm in solving large-scale practical problems.
C. Torres-Machi, V. Yepes, J. Alcala, E. Pellicer,
Volume 11, Issue 2 (6-2013)
Abstract

This paper describes a methodology in designing high-performance concrete for simply supported beams, using a hybrid optimization strategy based on a variable neighborhood search threshold acceptance algorithm. Three strategies have been applied to discrete optimization of reinforced concrete beams: Variable Neighborhood Descent (VND), Reduced Neighborhood Search (RNS) and Basic Variable Neighborhood Search (BVNS). The problem includes 14 variables: two geometrical one material type one mix design and 10 variables for the reinforcement setups. The algorithms are applied to two objective functions: the economic cost and the embedded CO2 emissions. Firstly, this paper presents the application of these three different optimization strategies, which are evaluated by fitting the set of solutions obtained to a three-parameter Weibull distribution function. The Variable Neighborhood Descent with Threshold Accepting acceptance strategy algorithm (VND-TA) results as the most reliable method. Finally, the study presents a parametric study of the span length from 10 to 20 m in which it can be concluded that economic and ecological beams show a good parabolic correlation with the span length.
R. Kamyab Moghadas, E. Salajegheh,
Volume 11, Issue 2 (6-2013)
Abstract

The present paper focuses on size optimization of scallop domes subjected to static loading. As this type of space structures includes a large number of the structural elements, optimum design of such structures results in efficient structural configurations. In this paper, an efficient optimization algorithm is proposed by hybridizing particle swarm optimization (PSO) algorithm and cellular automata (CA) computational strategy, denoted as enhanced particle swarm optimization (EPSO) algorithm. In the EPSO, the particles are distributed on a small dimensioned grid and the artificial evolution is evolved by a new velocity updating equation. In the new equation, the difference between the design variable vector of each site and an average vector of its neighboring sites is added to the basic velocity updating equation. This new term decreases the probability of premature convergence and therefore increases the chance of finding the global optimum or near global optima. The optimization task is achieved by taking into account linear and nonlinear responses of the structure. In the optimization process considering nonlinear behaviour, the geometrical and material nonlinearity effects are included. The numerical results demonstrate that the optimization process considering nonlinear behaviour results in more efficient structures compared with the optimization process considering linear behaviour. .
M. H. Sebt, M. H. Fazel Zarandi, Y. Alipouri,
Volume 11, Issue 3 (9-2013)
Abstract

Resource-Constrained Project Scheduling Problem (RCPSP) is one of the most popular problems in the scheduling phase of any project. This paper tackles the RCPSP in which activity durations can vary within their certain ranges such as RCPSP with variable activity durations. In this paper, we have attempted to find the most suitable hybridization of GA variants to solve the mentioned problem. For this reason, three GA variants (Standard GA, Stud GA and Jumping Gene) were utilized for first GA, and two GA variants (Standard GA, Stud GA) for the second one, and their hybridizations were compared. For this purpose, several comparisons of the following hybridizations of GAs are performed: Standard-Standard GA, Standard-Stud GA, Stud-Standard GA, Stud-Stud GA, Jumping Gene-Standard GA, and Jumping Gene-Stud GA. Simulation results show that implementing Stud-Stud GA hybridization to solve this problem will cause convergence on the minimum project makespan, faster and more accurate than other hybrids. The robustness of the Stud GA in solving the well-known benchmarking RCPSP problems with deterministic activity durations is also analyzed.
S. Soudmand, M. Ghatee, S. M. Hashemi,
Volume 11, Issue 4 (12-2013)
Abstract

This paper proposes a new hybrid method namely SA-IP including simulated annealing and interior point algorithms to find the optimal toll prices based on level of service (LOS) in order to maximize the mobility in urban network. By considering six fuzzy LOS for flows, the tolls of congested links can be derived by a bi-level fuzzy programming problem. The objective function of the upper level problem is to minimize the difference between current LOS and desired LOS of links. In this level, to find optimal toll, a simulated annealing algorithm is used. The lower level problem is a fuzzy flow estimator model with fuzzy link costs. Applying a famous defuzzification function, a real-valued multi-commodity flow problem can be obtained. Then a polynomial time interior point algorithm is proposed to find the optimal solution regarding to the estimated flows. In pricing process, by imposing cost on some links with LOS F or E, users incline to use other links with better LOS and less cost. During the iteration of SA algorithm, the LOS of a lot of links gradually closes to their desired values and so the algorithm decreases the number of links with LOS worse than desirable LOS. Sioux Falls network is considered to illustrate the performance of SA-IP method on congestion pricing based on different LOS. In this pilot, after toll pricing, the number of links with LOS D, E and F are reduced and LOS of a great number of links becomes C. Also the value of objective function improves 65.97% after toll pricing process. It is shown optimal toll for considerable network is 5 dollar and by imposing higher toll, objective function will be worse.
A. Kaveh, A. Nasrolahi,
Volume 12, Issue 1 (3-2014)
Abstract

In this paper, a new enhanced version of the Particle Swarm Optimization (PSO) is presented. An important modification is made by adding probabilistic functions into PSO, and it is named Probabilistic Particle Swarm Optimization (PPSO). Since the variation of the velocity of particles in PSO constitutes its search engine, it should provide two phases of optimization process which are: exploration and exploitation. However, this aim is unachievable due to the lack of balanced particles’ velocity formula in the PSO. The main feature presented in the study is the introduction of a probabilistic scheme for updating the velocity of each particle. The Probabilistic Particle Swarm Optimization (PPSO) formulation thus developed allows us to find the best sequence of the exploration and exploitation phases entailed by the optimization search process. The validity of the present approach is demonstrated by solving three classical sizing optimization problems of spatial truss structures.
M. Afzalirad, M. Kamalian, M. K. Jafari, A. Sohrabi-Bidar,
Volume 12, Issue 1 (1-2014)
Abstract

In this paper, an advanced formulation of time-domain, two-dimensional Boundary Element Method (BEM) with material damping is presented. Full space two-dimensional visco-elastodynamic time-convoluted kernels are proposed in order to incorporate proportional damping. This approach is applied to carry out site response analysis of viscoelastic topographic structures subjected to SV and P incident waves. Seismic responses of horizontally layered site, semi-circular canyons, slope topography and ridge sections subjected to these incident waves are analyzed in order to demonstrate the accuracy of the kernels and the applicability of the presented viscoelastic boundary element algorithm. The results show an excellent agreement with recent published results obtained in frequency domain. Also, the effects of different material damping ratios on site response are investigated.
H. Shahnazari, M. A. Shahin, M. A. Tutunchian,
Volume 12, Issue 1 (1-2014)
Abstract

Due to the heterogeneous nature of granular soils and the involvement of many effective parameters in the geotechnical behavior of soil-foundation systems, the accurate prediction of shallow foundation settlements on cohesionless soils is a complex engineering problem. In this study, three new evolutionary-based techniques, including evolutionary polynomial regression (EPR), classical genetic programming (GP), and gene expression programming (GEP), are utilized to obtain more accurate predictive settlement models. The models are developed using a large databank of standard penetration test (SPT)-based case histories. The values obtained from the new models are compared with those of the most precise models that have been previously proposed by researchers. The results show that the new EPR and GP-based models are able to predict the foundation settlement on cohesionless soils under the described conditions with R2 values higher than 87%. The artificial neural networks (ANNs) and genetic programming (GP)-based models obtained from the literature, have R2 values of about 85% and 83%, respectively which are higher than 80% for the GEP-based model. A subsequent comprehensive parametric study is further carried out to evaluate the sensitivity of the foundation settlement to the effective input parameters. The comparison results prove that the new EPR and GP-based models are the most accurate models. In this study, the feasibility of the EPR, GP and GEP approaches in finding solutions for highly nonlinear problems such as settlement of shallow foundations on granular soils is also clearly illustrated. The developed models are quite simple and straightforward and can be used reliably for routine design practice.
Mohsen Shahrouzi, Amir Abbas Rahemi,
Volume 12, Issue 2 (6-2014)
Abstract

Well-known seismic design codes have offered an alternative equivalent static procedure for practical purposes instead of verifying design trials with complicated step-y-step dynamic analyses. Such a pattern of base-shear distribution over the building height will enforce its special stiffness and strength distribution which is not necessarily best suited for seismic design. The present study, utilizes a hybrid optimization procedure to seek for the best stiffness distribution in moment-resistant building frames. Both continuous loading pattern and discrete sizing variables are treated as optimization design variables. The continuous part is sampled by Harmony Search algorithm while a variant of Ant Colony Optimization is utilized for the discrete part. Further search intensification is provided by Branch and Bound technique. In order to verify the design candidates, static, modal and time-history analyses are applied regarding the code-specific design spectra. Treating a number of building moment-frame examples, such a hyper optimization resulted in new lateral loading patterns different from that used in common code practice. It was verified that designing the moment frames due to the proposed loading pattern can result in more uniform story drifts. In addition, locations of the first failure of columns were transmitted to the upper/less-critical stories of the frame. This achievement is important to avoid progressive collapse under earthquake excitation.
A. Kaveh, H. Safari,
Volume 12, Issue 3 (9-2014)
Abstract

The paper presents a hybrid-enhanced algorithm based on CSS for discrete problems whit the focus on traveling salesman problem. The CSS algorithm based on some principles from physics and mechanics, utilize the governing Coulomb law from electrostatics and Newtonian laws of mechanics. However, the CSS is more suitable for continuous problems compared with discrete problems. In this paper, we have tried to resolve this defect of CSS algorithm with the help of local search methods and nearest neighbor for discrete problems whit the focus on traveling salesman problem (TSP). To prove the efficiency of the proposed algorithm, results compared with the results of benchmark problems. Then, the proposed algorithm is used to solve the TSP, using as a method for solving the single row facility layout problem (SRFLP). To prove the efficiency, the results are compared with the results of benchmark problems reported in the recent literatures.
Dr E. Shakeri, M. Dadpour, H. Abbasian Jahromi,
Volume 13, Issue 1 (3-2015)
Abstract

Employer Organizations have increasingly interested in outsourcing their projects in the form of public-private partnership (PPP) due to various reasons such as compromising the resource limitations, entering new technologies to the organization and reducing risk. Choosing the private sector as one of the most basic steps in the formation of PPP is of great importance. The present study aims to introduce a hybrid model to evaluate and choose the private sector as one of the parties in PPP using a combination of SWOT-AHP analysis, as one of the most powerful tools in identifying the problem environment, and Fuzzy ELECTRE analysis to evaluate the existing candidates to participate in the partnership using the criteria resulted from SWOT analysis. In first step, criteria set by an organization, as a case, to choose appropriate private sector were identified using SWOT method during various meetings with qualified experts. Then, the best choice was selected using ELECTRE method. Finally, obtained results were compared with the PROMETHE method. The results showed the effectiveness of our proposed method to select private partnerships especially positive and negative inter-organizational and outer-organizational factors significantly influence the private sector selection.
Mohsen Gerami, Ali Kheyroddin, Abbas Sivandi-Pour,
Volume 14, Issue 1 (1-2016)
Abstract

Steel-concrete hybrid systems are used in buildings, in which a steel structure has been placed on a concrete structure to make a lighter structure and have a faster construction. Dynamic analysis of hybrid structures is usually a complex procedure due to various dynamic characteristics of each part, i.e. stiffness, mass and especially damping. Dynamic response of hybrid structures has some complications. One of the reasons is the different stiffness of the two parts of structure and another reason is non-uniform distribution of materials and their different features such as damping in main modes of vibration. The available software is not able to calculate damping matrices and analyze these structures because the damping matrix of these irregular structures is non-classical. Also an equivalent damping should be devoted to the whole structure and using the available software. In the hybrid structures, one or more transitional stories are used for better transition of lateral and gravity forces. In this study, an equation has been proposed to determining the equivalent uniform damping ratio for hybrid steel-concrete buildings with transitional storey(s). In the proposed method, hybrid buildings are considered to have three structural systems, reinforced concrete, transitional storey and steel. Equivalent uniform damping ratio is derived by means of a semi-empirical error minimization procedure.


Amin Jamili,
Volume 15, Issue 1 (1-2017)
Abstract

A robust periodic train-scheduling problem under perturbation is discussed in this paper. The intention is to develop a robustness index and propose a mathematical model which is robust against perturbations. Some practical assumptions, as well as the acceleration and deceleration times along with periodic scheduling in addition to a practical new robustness index are considered. The aim is to obtain timetables with minimum travelling time that are robust against minor perturbations while the unnecessary stops are minimized. Generally, the spread of delays in the railway system is called delay propagation. We show that in addition to this phenomenon, there exists a more complicated case in periodic type of scheduling that is the fact of delay propagation from one period to the next. In fact, if the delays of a period are not absorbed by the next one, the size of delays may converge to infinity. We name this as delay intensification. Furthermore, we develop a hybrid heuristic algorithm which is able to find near optimal schedules in a limited amount of time and can absorb perturbations. To validate the algorithm, a new lower bound is introduced.


Jiuping Xu, Qiurui Liu, Zhonghua Yang,
Volume 15, Issue 1 (1-2017)
Abstract

To fully explain hydropower unit operational problems, an optimal multi-objective dynamic scheduling model is presented which seeks to improve the efficiency of reservation regulation management. To reflect the actual hydropower engineering project environment, fuzzy random uncertainty and an integrated consideration of the natural resource constraints, such as load balance, system power balance, generation limits, turbine capacity, water head, discharge capacities, reservoir storage volumes, and water spillages, were included in the model. The aim of this research was to concurrently minimize discharges and maximize economic benefit. Subsequently, a new hybrid dynamic-programming based multi-start multi-objective simulated annealing algorithm was developed to solve the hydro unit operational problem. The proposed model and intelligent algorithm were then applied to the Xiaolongmen Hydraulic and Hydropower Station in China. The computational unit commitment schedule results demonstrated the practicality and efficiency of this optimization method.


Ali Kaveh, M. Ghobadi,
Volume 15, Issue 1 (1-2017)
Abstract

This study proposes an efficient method for allocating the blood centers to hospitals based on the concept of graph partitioning (p-median methodology) and meta- heuristic optimization algorithms. For this purpose a weighted graph is first constructed for the network denoted by G0. A coarsening process is then performed to match the edges in n stages. Following the coarsening phase, the enhanced colliding bodies (ECBO) algorithm is applied to decompose the graph into a number of sub domains by use of p-median methodology. In our problem p is the number of blood centers which hospitals are intended to allocate. The results indicate that the proposed algorithm performs quite satisfactory from computational time and optimum points of view.



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