International Journal of Optimization in Civil Engineering
Volume:5 Issue: 3, Summer 2015

The shape optimization of gravity dam is posed as an optimization problem with goals of minimum value of concrete, stresses and maximum safety against overturning and sliding need to be achieved. Optimally designed structure generally saves large investments especially for a large structure. The size of hydraulic structures is usually huge and thus requires a huge investment. If the optimization techniques are employed in the design stage, the project investment can be effectively minimized. There are many optimization techniques were used to optimize the gravity dam. In the present work, optimization of gravity dam is carried out using the differential evolution technique. Differential evolution is an evolutionary algorithm which process iteratively to locate best solution in the large search space. Searching of optimal solution to a problem is carried out by the process of mutation, cross over and reproduction from the initial developed candidate solutions. After undergoing a number of iterations, it is possible to get the minimum cross sectional area of dam which can satisfy various constraints and thus the reduction in volume of concrete can be achieved. From the results obtained, it is found that differential evolution is one of the efficient techniques for solving such a problem over continuous space. The success of differential evolution in solving a specific problem critically depends on appropriately choosing trial vector generation strategies and their associated control parameter value. The optimum solution obtained is compared with analytical method and it is found that there is 20.44 % of reduction in the requirement of concrete is envisaged.

Displacements induced by earthquake can be very large and result in severe damage to earth and earth supported structures including embankment dams, road embankments, excavations and retaining walls. It is important, therefore, to be able to predict such displacements. In this paper, a new approach to prediction of earthquake induced displacements of slopes (EIDS) using hybrid support vector regression (SVR) with particle swarm optimization (PSO) is presented. The PSO is combined with the SVR for determining the optimal value of its user-defined parameters. The optimization implementation by the PSO significantly improves the generalization ability of the SVR. In this research, the input data for the EIDS prediction consist of values of geometrical and geotechnical input parameters. As an output, the model estimates the EIDS that can be modeled as a function approximation problem. A dataset that includes 45 data points was applied in current study, while 36 data points (80%) were used for constructing the model and the remainder data points (9 data points) were used for assessment of degree of accuracy and robustness. The results obtained show that the SVR-PSO model can be used successfully for prediction of the EIDS.

The main functional purpose of a water distribution network is to transport water from a source to several domestic and industrial units while at the same time satisfying various requirements on hydraulic response. All the water distribution networks perform two basic operations: firstly the water network needs to deliver adequate amounts of water to meet specific requirements, and secondly the water network needs to be reliable; therefore, the required amount of water needs to be continuously available 24 hours a day and 365 days per year. Due to the inevitable failures of some components such as pump stations, reservoirs and/or pipelines in a large-scale water distribution network, in designing a reliable network, the topological structure with low vulnerability must be achieved. Consequently, the study of connectivity, which is the key graph-theoretical notion, becomes crucial. This paper highlights some fundamental concepts from graph theory for vulnerability assessment of water distribution networks, addresses the mathematical properties of the link and node-deletion problems, and outlines some well-established results on the deterministic measures to assess the fault tolerance of networks.

Castellated beams are generally provided with hexagonal and circular openings in the web portion. However, in view of structural applications, appropriate size and shape of openings in web are always a major issue of concern. Research work carried out in optimizing sizes of castellated beam with hexagonal openings have reported that castellated beams fail mainly by local failure modes and stress concentrations at opening edges. Castellated beams with sinusoidal openings offer better performance due to its increased area for stress distribution in addition to curved edges that causes smooth stress distribution. Few researchers have studied flexural behaviour of castellated beams with sinusoidal openings; however, optimization for size of such openings has not been reported so far. The paper focuses on parametric study of castellated beam with sinusoidal openings for optimization of opening size. Finite element analysis (FEA) is carried out by Abaqus software and also by Eurocode for different opening sizes and results obtained is experimentally validated. Results show that, castellated beam with sinusoidal opening of size 0.55times the overall depth of beam gives better strength.

Location and types of sensors may be integrated for simultaneous achievement of water security goals and other water utility objectives, such as regulatory monitoring requirements. Complying with the recent recommendations on dual benefits of sensors, this study addresses the optimal location of these types of sensors in a multipurpose approach. The study presents two mathematical models for optimum location of sensors as static double use benefit model (SDUBM) and dynamic double use benefit model (DDUBM) which provides tradeoffs between maximum monitored volume of water known as “demand coverage” and minimum consumption of contaminated water. In the proposed modeling scheme, sensors are located to maximize dual use benefits of achieving water security goals and accomplishing regulatory monitoring requirements. The validity of the model is tested using two extensively tested example problems with multi-objective ant colony optimization (ACO) algorithm. The Pareto front for different number of sensors are presented and discussed.

The main object of this research is to optimize an end-filled castellated beam. In order to support high shear forces close to the connections, sometimes it becomes necessary to fill certain holes in web opening beam. This is done by inserting steel plates and welding from both sides. Optimization of these beams is carried out using three meta-heuristic methods involves CSS, CBO, and CBO-PSO algorithms. To compare the performance of these algorithms, the minimum cost of the beam is taken as the design objective function. Also, in this study, two common types of laterally supported castellated beams are considered as design problems: beams with hexagonal openings and beams with circular openings. A number of design examples are considered to solve in this case. Comparison of the optimal solution of these methods demonstrates that the hexagonal beams have less cost than cellular beams. It is observed that optimization results obtained by the CBO-PSO for more design examples have less cost in comparison to the results of the other methods.

In this paper, for topology optimization of double layer grids, an efficient optimization method is presented by combination of Imperialist Competitive Algorithm (ICA) and Gravitational Search Algorithm (GSA) which is called ICA-GSA method. The present hybrid method is based on ICA but the moving of countries toward their relevant imperialist is done using the law of gravity of GSA. In topology optimization process, the weight of the structure is minimized subjected to displacements of joints, internal stress and slenderness ratio of members constraints. Through numerical example, topology optimization of a typical large-scale double layer grid is obtained by ICA, GSA and ICA-GSA methods. The numerical results indicate that the proposed algorithm, ICA-GSA, executes better than ICA, GSA and the other methods presented in the literatures for topology optimization of largescale skeletal structures.

In this study, a two-echelon supplier-manufacturer system with finite production rate and lead time is proposed. It is assumed that shortage is not permitted and the lot size of manufacturer (second echelon) is m-factors of the lot size of supplier (first echelon) and supplier can supply the manufacturer’s lot size in several shipments in each cycle. So, the production rate of supplier is greater than manufacturer’s. The proposed model aims to determine the optimal lot-size of each echelon such that the total cost of system is minimized. First, the problem is studied regardless of lead time and the optimal value of the lot sizes and the number of shipments is determined through analytical relations. Then, an exact solution algorithm for the problem is presented for the case with non-zero lead time. Finally, the performance of the proposed algorithm is reviewed by solving some numerical instances of the problem.