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Barrel vaults are attractive space structures that cover large area without intermediate supports. In this paper, the charged

search system (CSS) optimization algorithm is employed for optimal design of barrel vaults. This method utilizes the governing

laws of Coulomb and Gauss from electrostatics and the Newtonian law of mechanics. The results demonstrate the efficiency of

the discrete CSS algorithm compared to other meta-heuristic algorithms.

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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.

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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.

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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. .

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In this research, the Charged System Search (CSS) and Enhanced Charged System Search (ECSS) algorithm are used to obtain the optimum design of irregular grillage systems with different spacing and various boundary conditions. The cross-sectional properties of the beams are selected as the design variables and the weight of structure is used as the objective function. The displacement limitations and permissible stress constraints are employed from LRFD-AISC and are considered in the formulation of the design problem. Furthermore, in obtaining the response of the grillage systems, the effect of warping is also taken into account. The comparison of the results shows that warping changes the beam spacing, and different boundary conditions have substantial effects on the optimum design of irregular grillage systems

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An important factor in the design and implementation of structural control strategies is the number and placement of actuators. By employing optimally-located actuators, the effectiveness of control system increases, while with an optimal number of actuators, an acceptable level of performance can be achieved with fewer actuators. The method proposed in this paper, simultaneously determines the number and location of actuators, installed in a building, in an optimal sense. In particular, a genetic algorithm which minimizes a suitably defined structural damage index is introduced and applied to a well-known nonlinear model of a 20-story benchmark building. It is shown in the paper that an equal damage protection, compared to the work of other researchers, can be achieved with fewer numbers of optimally placed actuators. This result can be important from economic point of view. However, the attempt to minimize one performance index has negative effect on the others. To cope with this problem to some extent, the proposed genetic methodology has been modified to be applied in a multi-objective optimization problem.

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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.

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In this paper, a bi-level decision making model is proposed for a vehicle routing problem with multiple decision-makers (VRPMD) in a fuzzy random environment. In our model, the objective of the leader is to minimize total costs by deciding the customer sets, while the follower is trying to minimize routing costs by choosing routes for each vehicle. Demand for each item has considerable uncertainty, so customer demand is considered a fuzzy random factor in this paper. After setting up the bi-level programming model for VRPMD, a bi-level global-local-neighbor particle swarm optimization with fuzzy random simulation (bglnPSO-frs) is developed to solve the bi-level fuzzy random model. Finally, the proposed model and method are applied to construction material transportation in the Yalong River Hydropower Base in China to illustrate its effectiveness.

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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.

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In comparison with other geomaterials, constitutive modeling of rockfill materials and its validation is more complicated. This is principally due to the existence of more intricate phenomena such as particle crushing, as well as laboratory test limitations. These issues have necessitated developing more complex constitutive models, with many parameters. Regardless of the type of model, the calibrations of the parameters in such models are considered as one of the most important and challenging steps in the application of the model. Therefore, the need for comprehensive and rapid methods for evaluation of optimum parameters of the models is deemed necessary. In this paper, a Neuro-Fuzzy model in conjunction with Particle Swarm Optimization (PSO) is used for calibration of the twelve parameters of Hierarchical Single Surface (HISS) constitutive model based on the Disturbed State Concept (DSC). The Neuro-fuzzy system is used to provide a high-degree nonlinear regression model between the deviatoric stress and volumetric strain versus axial strain that has been obtained from consolidated drained large scale tri-axial tests on rockfill materials. The model parameters are determined in an iterative optimized loop with PSO and ANFIS such that the equations of DSC/HISS are simultaneously satisfied. Material data used in this study are gathered from the results of large tri-axial tests for two rockfill dams in Iran. It is shown that the proposed method has higher accuracy and more importantly its robustness is exhibited through test predictions. The achieved improvement is substantiated in a comparison with the more widely used "Least-Square" method.

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In this paper, the problem of simultaneous shape and size optimization of single-layer barrel vault frames which contains both of discrete and continuous variables is addressed. In this method, the improved magnetic charged system search (IMCSS) is utilized as the optimization algorithm and the open application programming interface (OAPI) plays the role of interfacing analysis software with the programming language. A comparison between the results of the present method and some existing algorithms confirms the high ability of this approach in simultaneous shape and size optimization of the practical and large-scale spatial structures.

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Stabilization of earth slopes with various proposed methods is one of the important concerns of geotechnical engineering. In this practice, despite numerous developments, design conservativeness and high costs of stabilization are the issues yet to be addressed. This paper not only deals with pile location optimization but also studies the effects of the pile length by using line segments slip surface (non-circular). Taking into account the line segments slip surface in stabilization of earth slopes is a new topic which has been addressed in this paper. The line segments slip surface is actual slip surface and for determining the pile location it can lead to the actual length of the pile. The line segments critical slip surface is obtained by using the Alternating Variable Local Gradient (AVLG) optimization method. AVLG is an approach in optimization process and it is based on the Univariate method. The line segments form the initial and critical slip surface. Pile improper installation and inadequate length not only fails to increase the factor of safety, but also reduces it. The analyses are performed using the limit equilibrium (LE) method. Results of these analyses are acceptable and are properly consistent with the results obtained by other researchers.

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Incremental launching is a widespread bridge erection technique which may offer many advantages for bridge designers. Since internal forces of deck vary perpetually during construction stages, simulation and modeling of the bridge behavior, for each step of launching, are tedious and time consuming tasks. The problem becomes much more complicated in construction progression. Considering other load cases such as support settlements or temperature effects makes the problem more intricate. Therefore, modeling of construction stages entails a reliable, simple, economical and fast algorithmic solution. In this paper, a new Finite Element (FE) model for study on static behavior of bridges during launching is presented. Also a simple method is introduced to normalize all quantities in the problem. The new FE model eliminates many limitations of some previous models. To exemplify, the present model is capable to simulate all the stages of launching, yet some conventional models of launching are insufficient for them. The problem roots from the main assumptions considered to develop these models. Nevertheless, by using the results of the present FE model, some solutions are presented to improve accuracy of the conventional models for the initial stages. It is shown that first span of the bridge plays a very important role for initial stages it was eliminated in most researches. Also a new simple model is developed named as "semi infinite beam" model. By using the developed model with a simple optimization approach, some optimal values for launching nose specifications are obtained. The study may be suitable for practical usages and also useful for optimizing the nose-deck system of incrementally launched bridges.

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This paper presents a novel approach to solve the double-track railway rescheduling problem, when an incident occurs into one of the block sections of the railway. The approach restricts the effects of an incident to a specific time, based on which the trains are divided into rescheduled and unchanged ones, so that the latter retain their original time-table after the incident. The main contribution of this approach is the simultaneous consideration of three rescheduling policies: cancelling, delaying and re-ordering. A mixed-integer optimization model is developed to find optimal conflict-free time-table compatible with the proposed approach. The objective function minimizes two cost parts: the cost of deviation from the primary time-table and the cost of train cancellation. The model is solved by CPLEX 11 software which automatically generates the optimal solution of a problem. Also, a meta-heuristic solution method based on simulated annealing algorithm is proposed for tackling the large-scale problems. The results of an experimental analysis on two double-track railways of the Iranian network show an appropriate capability of the model and solution method for handling the simultaneous train rescheduling. The results indicate that the proposed solution method can provide good solutions in much shorter time, compared with the time taken to solve the mathematical model by CPLEX software.

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Resource allocation project scheduling problem (RCPSP) has been one of the challenging subjects amongst researchers in the last decades. Most of the researches in this scope have used deterministic variables, however in a real project activities are exposed to risks and uncertainties that cause to delay in project’s duration. There are some researchers that have considered the risks for scheduling, however, new metahuristics are available to solve this problem for finding better solution with less computational time. In this paper, two new metahuristic algorithms are applied for solving fuzzy resource allocation project scheduling problem (FRCPSP) known as charged system search (CSS) and colliding body optimization (CBO). The results show that both of these algorithms find reasonable solutions, however CBO finds the results in a less computational time having a better quality. A case study is conducted to evaluate the performance and applicability of the proposed algorithms.

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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.

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Tuned mass dampers are common solutions for passive control of bridge responses against dynamic loads. The present work concerns non-uniform support excitation of earthquakes as the dynamic loading source and studies TMD performance in controlling consequent vertical response of simply supported steel bridges. Charged system search as a recent meta-heuristic is successfully utilized to optimize TMD parameters whereas the dynamic response is evaluated via rigorous step-by-step time-history finite element analysis. As another issue, superiority of multiple TMD’s over single TMD is investigated for the present problem after unifying their parameters via optimization. Treating a bridge model as the case study under a number of real-world recorded earthquakes, the error of uniform support excitation under such a non-uniform case is evaluated. Superior efficiency of the utilized charged system search over popular genetic algorithm is observed for this problem. The results also revealed that how advantageous is the application of optimally designed multiple TMD in controlling dynamic vibration modes of such a distributed mass structure

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This paper has applied operation research to solid waste disposal by which two objective functions are optimized to minimize the expected operational costs (maximize revenues) and the expected net carbon dioxide equivalent (CDE) emissions. Types and uncertain amounts of solid wastes as well as costs of electricity were factored into the selection decision of solid waste disposal, i.e. landfill, incineration, composting and recycling. An optimization model was applied to the solid waste disposal of Bangkok, Thailand. In addition, a multi-objective optimization technique was proposed for a tradeoff decision-making between minimum operational costs and CDE emissions. Composting and landfill are effective alternatives for Bangkok’s solid waste disposal system. The operational costs and net CDE emissions are highly correlated with the quantity of solid waste. Policy-makers and plant operators could adopt the proposed optimization model under uncertainty in the selection of an optimal solid waste disposal.

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This paper outlines the effects of curing conditions on the strength and hydration products of lime activated slag cement. The slag cement was prepared by activating the ground granulated blast furnace slag with lime and plaster of Paris. The curing of mortar specimens was done at temperatures of 27⁰, 45⁰,60⁰,75⁰C and the compressive strength of specimens were determined after curing periods of 3,7, 28, 56 and 90days. The curing temperature is found to influence both the early and later age strengths. For the present test conditions the highest 90days compressive strength was found to be 47.63MPa for the specimen cured at temperature of 60⁰C. Further, the developed strength in mortar specimens were correlated with the hydration products and microstructure using X-ray diffraction and scanning electron microscope results. Generalized reduced gradient technique is adopted to find the optimum curing temperature for the given raw material composition and this is found to vary marginally on curing period. 

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The reinforced concrete bifurcation in hydropower station is consistently under high internal water pressure, and its diameter is usually larger than common duct junctions. In order to diminish or to decrease the heavy plastic zone and stress concentration, structure rounding is commonly used on bifurcation. This will bring some changes to the flow characteristic of bifurcation, and it is an interesting attempt to figure out the influence of structure rounding optimization. The Realizable k-ε model was employed in Computational Fluid Dynamics numerical simulation. The water pressure distribution was compared quantitatively at several certain sections. Furthermore, uneven pressure is analyzed by relative standard deviation. Hydraulic characteristics are discussed as well, including flow pattern, excavation volume and head loss in different working conditions. The results indicate that the pressure of pipe wall is uneven, and the maximum and minimum pressure value has a differential of 0.3% - 1.2% compared to relative static water pressure. The pressure unevenness will increase after structure rounding, and it has a positive correlation with structure rounding radius. At the same time, it is more reasonable for structure rounding in obtuse angle region than that in acute angle region, on account of well-distributed flow conditions and better economic benefit.