Sharif Digital Repository

In multi-tower heliostat fields, although heliostats are capable of aiming at different receivers during the day, due to different orientations, neighboring heliostats might affect shading and blocking efficiency of each other reciprocally. In the proposed method of this paper, considering the mentioned effects and based on a group decision-making approach, each heliostat chooses the best receiver thus ensuring the highest possible instantaneous efficiency of the field. As a case study, this method is applied for the optimal design of a multi-tower field. Then, the field performance is simulated in a case where heliostats make decisions individually without considering the interactions.... 

Solar energy will make a valuable contribution for power generation in the future. However the intermittency of solar energy has become an important issue in the utilization of PV system, especially small scale distributed solar energy conversion systems. The issue can be addressed through the management of production and storage of the energy in the form of hydrogen. The hydrogen can be produced by solar photovoltaic (PV) powered electrolysis of water. The amount of transferred energy to an electrolyzer from a PV module is a function of the distance between maximum power points (MPP) of PV module and the electrolyzer operating points. The distance can be minimized by optimizing the number... 

In this paper, a continuous review inventory system is considered in which an order in a batch of size Q is placed immediately after the inventory position reaches R. Transportation time is constant and demands are assumed to be generated by a stationary Poisson process with one unit demand at a time. Demands not covered immediately from the inventory are backordered. In a recent paper, the exact evaluation of batch-ordering policies for two-level inventory systems was derived. This evaluation is based on a recursive procedure for determining the exact policy costs in case of one-for-one replenishment policies. In this paper, we show how this result can be applied to find the optimal... 

Single-Row Facility Layout Problem (SRFLP) is a http://library.sharif.ir/web-manage/catalog/resource.do?method=edit&flowLastAction=view&id=447751special class of facilitylayout problems, consists of finding an optimal linear placement of rectangularfacilities with varying dimensions on a straight line. In this research, wefirst present a theorem to find the optimal solution of a special case of SRFLP.The results obtained by this theorem are very useful in reducing thecomputational efforts when, later on, a new algorithm based on tabu search ispresented for SRFLP. Computational results of the proposed algorithm onbenchmark problems show the efficiency of the algorithm compared to the... 

Process planning (PP) has an important role in manufacturing systems design and operations. Volume decomposition and machinable volumes (MVs) or machining features determination is the core activity in process planning. This process requires extraction of elementary volumes (EVs), merging or clustering EVs to construct feasible MVs and finally selecting an optimal combination of MVs. Development of MVs is an important activity, so that better solution is obtained by better developed MVs. Generation of limited number of MVs or machining features, which is often performed by experts may miss the optimal solution. Also, using exact methods such as combinatorial optimization not only generate... 

Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is... 

Recently, many meta-heuristic algorithms are proposed for optimization of various problems. Some of them originally are presented for continuous optimization problems and some others are just applicable for discrete ones. In the literature, sizing optimization of truss structures is one of the discrete optimization problems which is solved by many meta-heuristic algorithms. In this paper, in order to discover an efficient and reliable algorithm for optimization of truss structures, a discrete optimizer, entitled Soccer League Competition (SLC) algorithm and ten popular and powerful solvers are examined and statistical analysis is carried out for them. The fundamental idea of SLC algorithm is... 

The activity coefficient at infinite dilution is a representative of the limiting non-ideality of a solute in a mixture. Various methods for the prediction of infinite dilution activity coefficients (IDACs) have been developed. Artificial neural networks are powerful mapping tools for nonlinear function approximations. Accordingly, an artificial neural network model is proposed for the prediction of the IDACs of binary systems where the properties of the individual components are used as inputs to the network. The input parameters of the neural network are the mixture temperature, critical temperature, critical pressure, critical volume, molecular weight, dipole moment and the acentric... 

Laser shock peening (LSP) is known as a post processing surface treatment which can improve the mechanical properties of some materials. Shock waves are generated by confining the laser-induced plasma to cause a large pressure shock wave over a significant surface area. In the present study, effects of LSP on the electrochemical corrosion and micro hardness properties of 316L stainless steel alloy were investigated by changing the laser parameters such as the laser spot size, the average number of impacts, and the laser intensity. Since laser parameters do not cover the desired region of LSP, we have to use the proper design of experiment method, in which the D-optimal design of MATLAB was... 

MapReduce and its open source implementation, Hadoop, have gained widespread adoption for parallel processing of big data jobs. Since the number of such big data jobs is also rapidly rising, reducing their energy consumption is increasingly more important to reduce environmental impact as well as operational costs. Prior work by Mashayekhy et al. (IEEE Trans. Parallel Distributed Syst. 26, 2720–2733, 2016), has tackled the problem of energy-aware scheduling of a single MapReduce job but we provide a far more efficient heuristic in this paper. We first model the problem as an Integer Linear Program to find the optimal solution using ILP solvers. Then we present a task-based greedy scheduling... 

In this paper, a seismic reliability-based approach is proposed to design inelastic steel moment frame structures isolated by lead-rubber bearing (LRB) systems. An equivalent two-degree-of-freedom system is assumed in which a bilinear behaviour is assigned to both the superstructure and the base. Furthermore, uncertainties associated with the equivalent superstructure mass, stiffness, and yield properties are taken into account by employing proper probability density functions. The proposed design approach is twofold: 1) Reliability curves that return the key design parameters of the inelastic base-isolated structure including: the period of the superstructure, the target base displacement,... 

Many companies regularly run Big Data analysis, and need to optimize their resource usage considering cost, deadline, and environmental impact simultaneously. The cloud allows choosing from various virtual machines (VM) where the number and type of VMs affect the outcome such as the time for data placement and data shuffle phases, a task's energy consumption and execution time, and the makespan of jobs. We provide provisioning and scheduling algorithms to minimize environmental impact, considering the above factors, for frequently executed MapReduce jobs. To mathematically model the problem and obtain the optimal solution, we present an Integer Linear Programming (ILP) model and then... 

Economic production and on-time ordering are among the most important topics related to production and inventory control issues. An economical production needs a comprehensive and precise planning to be implemented in all production stages. To have a controlled and comprehensive planning system, economic order quantity (EOQ) or economic production quantity (EPQ) models are usually used in various production-inventory environments to minimize costs, avoid delays in orders, and achieve high performance. To meet the demands, sometimes a multiperiod production-inventory planning that involves several products requires outsourcing. In this paper, a production-procurement plan that integrates EOQ... 

In this paper, assuming porosity varies only along thickness direction, its optimal distributions in functionally graded porous (FGP) beams are tailored. Two multi-objective optimization problems are defined. In the first one, critical buckling load and mass are optimized simultaneously while in the second one, we concentrate on simultaneous optimization of mass and fundamental frequency. Employing Timoshenko beam theory, we present governing equations for a FGP beam. For the solution, we use Ritz method and propose appropriate trial functions according to the boundary conditions (Hinged-Hinged, Clamped-Clamped, Clamped-Hinged and Clamped-Free). Since the porosity distribution along... 

Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is... 

The railroad blocking problem emerges as an important issue at the tactical level of planning in freight rail transportation. This problem consists of determining the optimal paths for freight cars in a rail network. Often, demand and supply resource indicators are assumed certain; hence, the solution obtained from a certain model might not be optimal or even feasible in practice due to the stochastic nature of these parameters. To address this issue, this paper develops a robust model for this problem with uncertain demand and travel time as supply resource indicators. Since the model combines integer variables and nonlinear functions, a branch-And-cut algorithm is used to solve the... 

We present a linear programming based algorithm for a class of optimization problems with a multi-linear objective function and affine constraints. This class of optimization problems has only one objective function, but it can also be viewed as a class of multi-objective optimization problems by decomposing its objective function. The proposed algorithm exploits this idea and solves this class of optimization problems from the viewpoint of multi-objective optimization. The algorithm computes an optimal solution when the number of variables in the multi-linear objective function is two, and an approximate solution when the number of variables is greater than two. A computational study... 

This paper presents optimal scheduling in a two-machine flow shop, in which the objective function is to minimize the sum of maximum earliness and tardiness (n/2/P/ETmax). Since this problem tries to minimize earliness and tardiness, the results can be useful for different production systems such as just in time (JIT). This objective function has already been considered for n jobs and m machines, but the proposed algorithms are not efficient to solve large scale problems. In this paper, neighborhood conditions are developed and the dominant set for any optimal solution is determined. The branch-and-bound (B&B) method is used to solve the problem and the proper upper and lower bounds are also... 

In this study the properties of muscle synergies, arising from optimal feedback control are investigated. Three different tasks namely reaching, via-point, and hitting are performed using optimization of corresponding cost functions. Then by applying non-negative matrix factorization method to a dataset of muscle tensions, synchronous muscle synergies are obtained. In this way, different muscle patterns can be generated by linear combination of these basis vectors with non-negative time-varying scaling coefficients. According to our simulations some of obtained muscle synergies are shared between tasks and some of them are specific for one task. This finding is also in agreement with the... 

This paper proposes a solver-friendly model for disjoint, non-smooth, and nonconvex optimal power flow (OPF) problems. The conventional OPF problem is considered as a nonconvex and highly nonlinear problem for which finding a high-quality solution is a big challenge. However, considering practical logic-based constraints, namely multiple-fuel options (MFOs) and prohibited operating zones (POZs), jointly with the non-smooth terms such as valve point effect (VPE) results in even more difficulties in finding a near-optimal solution. In complex problems, the nonlinearity itself is not a big issue in finding the optimal solution, but the nonconvexity does matter and considering MFO, POZ, and VPE...