Sharif Digital Repository

A novel and robust approach is proposed to find the optimum shape of concrete arch dams located on any unsymmetrical shape of a valley. The approach is capable of finding the optimum shape for any given valley type in suitable time, based on abutment stability analysis, against thrust forces from an arch dam. The behavior and stability of a concrete arch dam is strongly dependent on the bedrock on which the dam rests. The stability of the abutment is considered a constraint in the proposed approach. In addition, a new objective function is introduced to decrease the final volume of the arch dam. Furthermore, a computer program was developed, which takes the effect of the dam foundation... 

This paper presents a biomechanical model with seven degrees of freedom as a seated human exposed to vertical vibration. Experimental data is used to find the stiffness and damping parameters of the model. The data includes values of seat to head transmissibility, driving point mechanical impedance and apparent mass. The multi-objective function is used to obtain theoretical results similar to three different experimental cases. The unknown coefficients are calculated by a genetic algorithm. Improved results, in comparison with previous models, are achieved from the presented model. Next, this modified model is assembled on a quarter car and parameters of the cushion and the suspension... 

The bulk of the worldwide annual commercial production of ethylene is based on thermal cracking of petroleum hydrocarbons with steam. In this research, the effect of coil outlet temperature on the reactor yield has been studied. In order to investigate a reliable mathematical correlation, several data points were obtained by adjusting coil outlet temperature in a real plant. In order to investigate best coil outlet temperature, an objective function was represented. Based on the obtained mathematical correlation and the assumed objective function, it was found that best coil outlet temperature for investigating maximum income is 1,128 K  

In this study, a Discrete Particle Swarm Optimization (DPSO) algorithm is assimilated to solve the Transit Network Design Problem (TNDP). First, A Mixed Integer Model is developed for the TNDP. The solution methodology utilized here is made of two major elements. A route generation module is firstly developed to generate all the feasible transit lines. Through the second part, a DPSO algorithm is utilized to select the optimal set of lines from the constructed ones. The objective function is to maximize coverage index while satisfying the operator cost upper level constraints. The efficacy and accuracy of the implemented algorithms is compared with ones obtained by an enumeration process as... 

The bus network design problem is an important problem in transportation planning. It is the problem of determining a network of bus lines which best achieves a predetermined objective. This may be done with or without the presence of rapid transit lines. This study is devoted to solving this problem using genetic algorithm. The fitness function is defined as the benefit to the users of the bus network less the cost of the operator of the network, which is to be maximized subject to constraints that properly distribute bus routes over the study area. Objective function calculation depends on the basic data of the city and its bus lines and does not need traffic assignment results. So, it is... 

A gradient based optimization using the continuous adjoint method for inverse design of a turbine blade cascade is presented. The advantage of the adjoint method is that the objective function gradients can be evaluated by solving the adjoint equations with coefficients depending on the flow variables. This method is particularly suitable for aerodynamic design optimization for which the number of design variables is large. Bezier polynomials are used to parameterize suction side of the turbine blade. The numerical convective fluxes of both flow and adjoint equations are computed by using a Roe-type approximate Riemann solver. An approximate linearization is applied to simplify the... 

In the literature, although a few studies can be found regarding the application of revenue management to special cases of Make-to-Order manufacturing systems with stochastic capacity, there is not any study when capacity or demand (or both) are random variables with general distribution function. Therefore, in this paper, an approach is developed to study a more general case of Make-to-Order manufacturing systems based on the concept of revenue management. Due to the random nature of capacity and demand, the exact size of capacity to satisfy the orders is not known at the time of arriving orders. Consequently, the vital decision is either to accept or reject an order at the time of arrival.... 

Response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. The main idea of RSM is to use a set of designed experiments to obtain an optimal response. RSM tries to simplify the original problem through some polynomial estimation over small sections of the feasible area, elaborating on optimum provision through a well known optimization technique, say Gradient Method. As the real world problems are usually very complicated, polynomial estimation may not perform well in providing a good representation of the objective function. Also, the main problem of the Gradient Method, getting trapped in local minimum (maximum),... 

As many fields around the world are reaching maturity, the need to develop new tools that allows reservoir engineering to optimize reservoir performance is becoming more demanding. One of the more challenging and influential problems along these lines is the well placement optimization problem. Determining of the location of new wells is a complex problem that depends on reservoir and fluid properties, well and surface equipment specifications, and economic criteria. Various approaches have been proposed for this problem. Among those, direct optimization using the simulator as the evaluation function, although accurate, is in most cases infeasible due to the number of simulations required.... 

In this work, the modified Flory-Huggins coupled with the free-volume concept and the artificial neural network models were used to obtain the osmotic pressure of aqueous poly(ethylene glycol) solutions. In the artificial neural network, the osmotic pressure of aqueous poly(ethylene glycol) solutions depends on temperature, molecular weight and the mole fractions of poly(ethylene glycol) in aqueous solution. The network topology is optimized and the (3-1-1) architecture is found using optimization of an objective function with batch back propagation (BBP) method for 134 experimental data points. The results obtained from the neural network in obtaining of the osmotic pressure of aqueous... 

A new and general procedure for history matching that uses streamline simulation and a gradual deformation technique has been proposed. Streamline trajectories define the major flow paths and help the algorithm to modify the reservoir model only in the regions that cause the mismatch between simulation results and field observations. The use of a gradual deformation technique enables the algorithm to remain constrained to reservoir geostatistics. It also reduces the number of independent variables in the optimization problem. In our algorithm, effective conductivities are defined along each streamline. The effective streamline conductivities are then adjusted using the values of measured and... 

Osmotic power generation is one of the cleaner and sustainable methods for energy generation. This paper presents a study on the optimal size and design of pressure retarded osmosis (PRO) power plant as a viable source of renewable energy in the selected site in Bahmanshir river of Iran. The optimal sizing and design problem is formulated as a Non-Linear Programming (NLP) optimization problem and solved using the standard optimization software titled generalized algebraic modeling system (GAMS). The objective function is minimizing the total cost while considering the technical and economic constraints. Optimization results show that the optimal capacity of the PRO osmotic power plant is... 

Proliferation of private distributed energy resources (DERs) necessitates devising effective energy management frameworks. This paper aims at establishing a decentralized model for the optimal dispatch of DERs in smart grids. The objective function is to minimize expected procurement cost of demand while profit of private DER owners is not sacrificed. Unit management modules (UMMs) embedded in private DERs and a central agent are autonomous agents of the model. The approach is iterative. In each iteration, the central agent announces to UMMs its procurement strategy, which contains purchased powers and their prices. Then, UMMs optimize and send back their output power and selling price... 

In this paper, we introduce a novel approach based on Tucker Decomposition and quasi-periodic nature of ECG signal for fetal ECG extraction from abdominal ECG mixture. We adapt variable periodicity constraint of the ECG components to main objective function of the Tucker Decomposition and shape it to matrix form in order to simply optimize the objective function. We form a 3rd order tensor by stacking the mixed multichannel ECG and reconstructed fetal and maternal subspaces using BSS methods in order to have the benefit of further artificial observations, and apply our proposed penalized decomposition on it. The proposed method is evaluated on synthetic and real datasets using the criteria... 

This paper presents evolutionary methods for optimization in dynamic mobile robot path planning. In dynamic mobile path planning, the goal is to find an optimal feasible path from starting point to target point with various obstacles, as well as smoothness and safety in the proposed path. Pattern search (PS) algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to find an optimal path for mobile robots to reach to target point with obstacle avoidance. For showing the success of the proposed method, first they are applied to two different paths with a dynamic environment in obstacles. The first results show that the PSO algorithms are converged and minimizethe...