International Journal of Optimization in Civil Engineering
Volume:7 Issue: 3, Summer 2017

Semi-active base isolation system has been proposed mainly to mitigate the base drift of isolated structures while in most cases, its application causes the maximum acceleration of superstructure to be increased. In this paper, designing optimal semi-active base isolation system composed of linear base isolation system with low damping and magneto-rheological (MR) damper has been studied for controlling superstructure acceleration and base drift separately and simultaneously. A multi-objective optimization problem has been defined for optimal design of semi-active base isolation system which considers a linear combination of maximum acceleration and base drift as objective function where Genetic algorithm (GA) has been used to solve the optimization problem. H2/Linear Quadratic Gaussian (LQG) and clipped-optimal control algorithms have been used to determine the desired control force and the voltage of MR damper in each time step. For numerical simulation, a four-story base isolated shear frame has been considered and for different values of weighting parameter in objective function, optimal semi-active base isolation system has been designed under various design earthquakes. The results show that by using base isolation system and supplemental MR damper, the superstructure acceleration and base drift can be suppressed significantly. Also, it has been concluded that by selecting proper values for maximum acceleration and base drift related weighting parameters in objective function, it is possible to mitigate the maximum acceleration and base drift simultaneously. Furthermore, semiactive control system has worked successfully under testing earthquakes regarding design criteria.

In this paper, a systematic approach is presented for optimal design of tunnel support lining using two-dimensional finite element analysis models of soil-structure interaction developed in ABAQUS software and the Modified Colliding Bodies Optimization (MCBO) algorithm implemented in MATLAB environment. This approach is then employed to study the influence of variable geometrical and geo-mechanical parameters on the optimal design of a class of practical access tunnels.

In this paper, MATLAB code for a recently developed meta-heuristic methodology, the vibrating particles system (VPS) algorithm, is presented. The VPS is a population-based algorithm which simulates a free vibration of single degree of freedom systems with viscous damping. The particles gradually approach to their equilibrium positions that are achieved from current population and historically best position. Two truss towers with 942 and 2386 elements are examined for the validity of the present algorithm; however, the performance VPS has already been proven through truss and frame design optimization problems.

This study investigates the prediction model of compressive strength of self–compacting concrete (SCC) by utilizing soft computing techniques. The techniques consist of adaptive neuro–based fuzzy inference system (ANFIS), artificial neural network (ANN) and the hybrid of particle swarm optimization with passive congregation (PSOPC) and ANFIS called PSOPC–ANFIS. Their performances are comparatively evaluated in order to find the best prediction model. In this study, SCC mixtures containing different percentage of nano SiO2 (NS), nano–TiO2 (NT), nano–Al2O3 (NA), also binary and ternary combining of these nanoparticles are selected. The results indicate that the PSOPC–ANFIS approach in comparison with the ANFIS and ANN techniques obtains an improvement in term of generalization and predictive accuracy. Although, the ANFIS and ANN techniques are a suitable model for this purpose, PSO integrated with the ANFIS is a flexible and accurate method due tothe stronger global search ability of the PSOPC algorithm.

Today’s, a common problem in cities is increasing delay and reducing the speed of traffic. On the other wise increasing costs of acquisition in urban area are not allow new routes and highways. Also construction of new highway or street such as Imam Ali highway and Sadr highway in Tehran lead to develop new applications (such as BRT lane ,…) And become quickly saturate and less efficient. Therefore traffic Management could be more effective in controlling traffic with lower costs. Variable message sign is one of these management solutions. For this purpose, two parallel streets ENGHELAB and JOMHORI are selected to study. The result of this research show that implementation of this variable message sign when accident occur and abstraction the road and using strategy of change way can reduce 100 sec/km of delay time and reduce fuel consumption to 400 lit/hr that it means saving about 667 thousand dollar in fuel consumption and delay time.

Tower cranes are major and expensive equipment that are extensively used at building construction projects and harbors for lifting heavy objects to demand points. The tower crane locating problem to position a tower crane and supply points in a building construction site for supplying all requests in minimum time, has been raised from more than twenty years ago. This problem has already been solved by linear programming, but meta-heuristic methods spend less time to solving the problem. Hence, in this paper three newly developed meta-heuristic algorithms called CBO, ECBO, and VPS have been used to solve the tower crane locating problem. Three scenarios are studied to show the applicability and performance of these meta-heuristics.

A new meta-heuristic method, based on Neuronal Communication (NC), is introduced in this article. The neuronal communication illustrates how data is exchanged between neurons in neural system. Actually, this pattern works efficiently in the nature. The present paper shows it is the same to find the global minimum. In addition, since few numbers of neurons participate in each step of the method, the cost of calculation is less than the other comparable meta-heuristic methods. Besides, gradient calculation and a continuous domain are not necessary for the process of the algorithm. In this article, some new weighting functions are introduced to improve the convergence of the algorithm. In the end, various benchmark functions and engineering problems are examined and the results are illustrated to show the capability, efficiency of the method. It is valuable to note that the average number of iterations for fifty independent runs of functions have been decreased by using Neuronal Communication algorithm in comparison to a majority of methods.

Optimal design of cantilever reinforced concrete retaining wall can lead considerable cost saving if its involvement in hill road formation and railway line formation is significant. A study of weight reduction optimization of reinforced cantilever retaining wall subjected to a sloped backfill using Differential Evolution Algorithm (DEA) is carried out in the present research. The retaining wall carrying a sloped backfill is investigated manually and the problem is solved using the algorithm and results were compared. The Indian Standard design philosophy is followed throughout the research. The design variables, constraint equations were determined and optimized with DEA. The single objective constrained optimization problem deals with seven design variables of cantilever retaining wall in which four design variables constitutes to geometric dimensions and remaining three variables constitutes to the reinforcement steel area. Ten different constraints are considered and each of it deals with ten failure modes of retaining wall. Further, a sensitivity analysis is carried out by varying the parameters namely, height of the stem and thickness of stem at top, both of it being a constant design variable in the normal optimization problem. Results show that about 15% weight reduction is achieved while comparing with manual solution.

The present study sets out to integrate the performance-based seismic design approach with the connection topology optimization method. Performance-based connection topology optimization concept aims to simultaneously optimize the size of members and the type of connections with respect to the framework of performance-based seismic design. This new optimization concept is carried out for unbraced and X-braced steel frames in order to assess its efficiency. The cross-sectional area of components and the type of beam-to-column connections are regarded as design variables. The objective function is formulated in terms of the material costs and the cost of rigid connections. The nonlinear pushover analysis is adopted to acquire the response of the structure at various performance levels. In order to cope with the optimization problem, CBO algorithm is employed. The achieved results demonstrate that incorporating the optimal arrangement of beam-to-column connections into the optimum performance-based design procedure of either unbraced or X-braced steel frame could lead to a design that significantly reduces the overall cost of the structure and offers a predictable and reliable performance for the structure subjected to hazard levels.

For any agency dealing with the design of the water distribution network, an economic design will be an objective. In this research, Central Force Optimization (CFO) and Differential Evolution (DE) algorithm were used to optimize Ismail Abad water Distribution network. Optimization of the network has been evaluated by developing an optimization model based on CFO and DE algorithm in MATLAB and the dynamic connection with EPANET software for network hydraulic calculation. Conclusions show CFO runtime is less than DE. While optimization of CFO (737,924 $) and DE (737,920 $) are %1.61 and %1.57 more than the absolute optimum that determined by the MILP method (726,463 $), respectively.