Sharif Digital Repository

We introduce a new robust simulation optimization method in which the probability of occurrence of uncertain parameters is considered. It is assumed that the probability distributions are unknown but historical data are on hand and using φ-divergence functionality the uncertainty region for the uncertain probability vector is defined. We propose two approaches to formulate the robust counterpart problem for the objective function estimated by Kriging. The first method is a minimax problem and the second method is based on the chance constraint definition. To illustrate the methods and assess their performance, numerical experiments are conducted. Results show that the second method obtains... 

An algorithm is proposed to optimize the performance of multiphase structures (composites) under elastodynamic loading conditions. The goal is to determine the distribution of material in the structure such that the time-averaged total stored energy of structure is minimized. A penalization strategy is suggested to avoid the checkerboard instability, simultaneously to generate near 0-1 topologies. As a result of this strategy, the solutions of presented algorithm are sufficiently smooth and possess the regularity of H1 function space. A simple method for the continuum adjoint sensitivity analysis of the corresponding PDE-constrained optimization problem is presented. It is general and can be... 

one of the important issues of construction industry today, is providing a meaningful interconnectivity between Architecture and its technical and technological aspects. In construction projects aesthetic and form is habitually crucial for the architect while structural designers aim for efficiency and stability of the structure. This research is concerned with the design of an urban footbridge located in Tehran-Iran with social and cultural spaces in which the form of the bridge is obtained by the use of topology optimization process. The objective of this study is to investigate the utilization of topology optimization process in architecture in order to achieve a beneficial design... 

one of the important issues of construction industry today, is providing a meaningful interconnectivity between Architecture and its technical and technological aspects. In construction projects aesthetic and form is habitually crucial for the architect while structural designers aim for efficiency and stability of the structure. This research is concerned with the design of an urban footbridge located in Tehran-Iran with social and cultural spaces in which the form of the bridge is obtained by the use of topology optimization process. The objective of this study is to investigate the utilization of topology optimization process in architecture in order to achieve a beneficial design... 

A morphing-body optimization method is introduced to accelerate adjoint-based shape optimization techniques. The optimization process solves the flow and adjoint equations around a continuously deforming body whose shape is controlled by the cost function. Effect of various parameters on the efficiency of the scheme is studied. It is found that, for the best performance of the algorithm, the morphing rate of the airfoil should be restricted, since larger rates foster oscillations and lower values are not computationally feasible. Moreover, the iterative procedure in the adjoint solver should be adapted to the iteration scheme in the flow solver and to the morphing rate  

Similar to other existing classical production and inventory control models, the economic production quantity (EPQ) model is derived based upon some assumptions that cause its limited real-world applications. One of the assumptions in this model is that the orders are delivered in a continuous and constant rate. In order to make the EPQ model more applicable to real-world production and inventory control environments, in this research, an EPQ model is considered in which the orders are delivered discretely in the form of multiple pallets. Under this condition, the EPQ costs are derived and a new model is developed to find the optimum values of both the economic order quantity and the reorder... 

In this research, numerical optimization of the rear part of a gas turbine, consisting of a single-stage axial turbine, is carried out. Automated aerodynamic shape optimization is performed by coupling a CFD flow simulationcode with the genetic algorithm. An effective multipointoptimization method to improve efficiency and/or pressure ratio of the axial turbine is performed. Some variations of optimization parameters such as lean and sweep angels of stator and rotor blades are accomplished. Furthermore, during the optimization process, three-dimensionaland turbulent flow field is numerically investigatedusing a compressible Navier-Stokes solver. The gas turbine experimental investigations... 

A new methodology has been proposed to enhance inverse dynamics applications in the process of trajectory planning and optimization in Terrain Following Flights (TFF). The new approach uses least square scheme to solve a general two-dimensional (2D) Terrain Following Flight in a vertical plane. In the mathematical process, Chebyshev polynomials are used to model the geographical data of the terrain in a given route in a manner suitable for the aircraft at hand. The aircraft then follows the modeled terrain with sufficient clearance. In this approach the TF problem is effectively converted to an optimal tracking problem. Results show that. this method provides a flexible approach to solve the... 

The increasing variability of renewables and volatile chronological net-load in power grids engenders significant risks of an uncertain sufficiency of flexible capacity. Although considerable advances in power grid flexibility assessment have been made, modeling the effect of temporal correlations associated with wind generations on the system flexibility provision capability has remained a challenge. This paper proposes a novel UC-time-scale security-constrained affinely robust formulation for wind-originated uncertainty sets in order to evaluate the system flexibility capacity over time. An efficient model based on duality theorem and affine policy is proposed to assess a secure region in... 

A new algorithm for the solution of multimaterial topology optimization problems is introduced in the present study. The presented method is based on the splitting of a multiphase topology optimization problem into a series of binary phase topology optimization sub-problems which are solved partially, in a sequential manner, using a traditional binary phase topology optimization solver; internal solver. The coupling between these incomplete solutions is ensured using an outer iteration strategy based on the block coordinate descend method. The presented algorithm provides a general framework to extend the traditional binary phase topology optimization solvers for the solution of multiphase... 

This paper presents an improved firefly algorithm (FA) for fast optimization of truss structures with discrete variables. The enhanced accelerated firefly algorithm (AFA) is a simple, but very effective modification of FA. In order to investigate the performance and robustness of the proposed algorithm, some benchmark (structural optimization) problems are solved and the results are compared with FA and other algorithms. The results show that in some test cases, AFA not only finds lighter structures compared to other algorithms, but also converges faster. In the rest test cases, the optimal solutions are found with very less computational effort. The study also shows that the proposed AFA... 

In distribution system planning studies, reliability evaluation is performed during optimization procedure to calculate the interruption cost, DISCO's income and to check the viability of constraints related to reliability indices. In each iteration of the optimization algorithm a special plan is evaluated that is different from other plans. So the configuration and specification of the network which is one of the input information for reliability evaluation is changing continuously that makes difficulties for this evaluation. To solve these difficulties, this paper presents a systematic method for reliability evaluation in distribution planning studies. The proposed approach can be... 

Integer multipliers with finite output bit-widths are widely used in many Digital Signal Processing (DSP) applications. In such circuits high-level optimizations like Residue Number System (RNS) can be utilized to achieve more efficient architectures compared to the conventional binary representations. This paper presents an efficient high-level Don't-Care Optimization (DC-Opt) method for integer multipliers and in general Multiply Accumulator (MAC) units when the output result is limited to a finite bit-width. This high-level optimization approach can then be combined with logic optimizations at gate-level. Experimental results have shown major improvements in terms of area and latency... 

Assessing the operational flexibility of the grid with high penetration of renewable resources remains an issue of critical importance. Operational flexibility insufficiency may bring about two major problems: 1) there may exist no feasible solution for operation under uncertain conditions due to insufficient available flexibility capacity; 2) even if the solution feasibility criterion is ensured, dispatch limitations of the flexible resources may force the system operating point to deviate from the optimal economic point with increased redispatch. In this paper, an optimal uncertainty set at the unit commitment time scale is proposed and characterized as a reliable operational metric. A... 

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

In this paper, Bat Algorithm is proposed to solve the Optimal Power Flow (OPF) problem. The approach employs a Meta heuristic optimization algorithm called bat optimization algorithm to determine the optimal settings of control variables of OPF problem. The performance of proposed method examined on the IEEE 9, 14, 30 and 57-buses test systems with fuel cost minimization as the objective function. The numerical results are compared to those of Particle Swarm Optimization (PSO), Harmony Search (HS) and Cuckoo algorithms. Simulation results obtained from the proposed approach demonstrate that this method provide effective and robust high-quality answer for the OPF problem. © 2016 IEEE  

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

Optimal well placement is a crucial step in reservoir development process. The key points in such an optimization process are using a fast function evaluation tool and development of an efficient optimization algorithm. This study presents an approach that uses particle swarm optimization algorithm in conjunction with streamline simulation to determine the optimum well locations within a reservoir, regarding a modified net present value as the objective. Performance of this algorithm was investigated through several different examples, and compared to that of genetic algorithm (GA) and simulated annealing (SA) methods. It was observed that particle swarm optimization algorithm outperformed... 

Estimation of distribution algorithms have evolved as a technique for estimating population distribution in evolutionary algorithms. They estimate the distribution of the candidate solutions and then sample the next generation from the estimated distribution. Bayesian optimization algorithm is an estimation of distribution algorithm, which uses a Bayesian network to estimate the distribution of candidate solutions and then generates the next generation by sampling from the constructed network. The experimental results show that the Bayesian optimization algorithms are capable of identifying correct linkage between the variables of optimization problems. Since the problem of finding the...