One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive control method based on dynamic programming has been used to design a stabilizing power system and a complementary static var compensator (SVC) controller. By applying a single line to ground fault in the network, the robustness of the designed control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive control method based on dynamic programming for the stabilizing design of the power system and the complementary SVC controller. The performance of the control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

In this paper, we propose a new method for solving of optimal operation problem of active distribution networks (ADNs) in energy, spinning reserve service, and reactive power service markets using technical virtual power plant (TVPP) concept. TVPP with considering network and its DER constraints provide active operation of distribution network in order to maximize its profit. A security constraints price-based unit commitment (SCPBUC) model, whose security constraints are related to the supply-demand balancing and to the operation of distribution network, is proposed. In addition to optimal bidding in the markets, the proposed model results show that ADN with using VPP concept can operate its network securely. The presented model is a non-convex nonlinear Mixed-integer optimization solved by Mixed-integer nonlinear programming (MINLP).

Computational grids have provided the usage of computational distributed resources for computation-intensive applications. The development of programs that use these capabilities is one of the challenging issues for grid computing. In this article, an effort has been made in order to solve this problem by presenting mobile-agent-based parallel programming on the grid. The presentation of this model, which has been materialized by extending Alchemi™ grid infrastructure, adding agent properties and navigational commands that let the user to develop his/her program by using agents’ mobility and communication between them. In order to evaluate the system, algorithm of matrix multiplication as well as algorithm of finding the convex hull of a series of points has been implemented in the mentioned system.

The portfolio of urban and public projects should be balanced in terms of completion time, districts, and strategic objectives. For this purpose, we suggest a mixedinteger nonlinear programming model based on the goal programming approach. Projects are selected to minimize the squared deviation of urban and regional development indicators from their respective targets. In the proposed model there are two types of indicators: coverage indicators that are measured based on the distance of each neighborhood from the nearest covering facility, and general indicators that are usually measured based on the capacities and capabilities of each district. It is assumed that the location of covering facilities has already been selected, but the construction of these facilities will be prioritized and planned based on budget constraints and competition with other regional development projects. Numerical results show that the proposed genetic algorithm has superior performance compared with the Generalized Algebraic Modeling System (GAMS) solvers. Finally, the application of the model is illustrated by an example.

In this study, we discussed a fuzzy programming approach to bi-level linear programming problems and their application. Bi-level linear programming is characterized as mathematical programming to solve decentralized problems with two decision-makers in the hierarchal organization. They become more important for the contemporary decentralized organization where each unit seeks to optimize its own objective. In addition to this, we have considered Bi-Level Linear programming (BLPP) and applied the Fuzzy Mathematical programming (FMP) approach to get the solution of the system. We have suggested the FMP method for the minimization of the objectives in terms of the linear membership functions. FMP is a supervised search procedure (supervised by the upper Decision Maker (DM)). The upper-level decision-maker provides the preferred values of decision variables under his control (to enable the lower level DM to search for his optimum in a wider feasible space) and the bounds of his objective function (to direct the lower level DM to search for his solutions in the right direction).

There are many cases that a nonlinear fractional programming, generated as a result of studying fractional stochastic programming, must be solved. Sometimes an approximate solution may be sufficient enough to start a new process of calculations. To this end, this author introduces a new linear approximation technique for solving a fractional chance constrained programming (CCP) problem. After introducing the problem, the equivalent deterministic form of the fractional nonlinear programming problem is developed. To solve the problem, a fuzzy goal programming model of the equivalent deterministic form of the fractional chance constrained programming is provided and then the process of defuzzification and linearization of the problem is started. A sample test problem is solved for presentation purposes.

In mammals, the intrauterine condition has an important role in the development of fetal physiological systems in later life. Suboptimal maternal environment can alter the regulatory pathways that determine the normal development of the fetus in utero, which in post-natal life may render the individual more susceptible to cardiovascular or metabolic adult-life diseases. Changes in the intrauterine availability of nutrients, oxygen and hormones can change the fetal tissue developmental regulatory planning, which occurs genomically and non-genomically and can cause permanent structural and functional changes in the systems, leading to diseases in early years of life and those that particularly become overt in adulthood. In this review we take a brief look at the main elements which program the fetal system development and consequently induce a crucial impact on the cardiovascular, nervous and hormonal systems in adulthood.

In this study, supply chain network design is considered. Responsibility and profitability are the company's main features, so we proposed a model to maximize profit, reducing logistic costs, especially shortage costs, to increase responsibility. Adopting the right sales policy by a seller is an issue that needs to be addressed. In this research, we try to improve sales conditions based on each channel's capacity by considering the all unit discount policy for each channel's sale. We used a pricedependent demand function to bring the situation closer to the real world. We considered the factor of advertising and inflation on demand in this issue. A mixedinteger nonlinear programming model is introduced for the problem and formulated in GAMS software; then, sensitivity analysis examines some parameters.

Wheat is a staple food in many countries and as a result, the , rst most cultivated crop worldwide. Since wheat is a vital product in terms of food security, its supply chain needs to be studied and planned carefully. This paper proposes a mixedinteger linear programming model for integrated planning of imported and domestically produced wheat that addresses supplier selection, order planning, transportation, storage, and distribution problems at the same time. Speci, cally, this model focuses on the wheat quality and wheat sleep period. Moreover, di, erentiation of long-term and shortterm storage facilities and consideration of intra-layer ows between storage facilities are other characteristics of this model. A fuzzy chance-constrained programming approach is employed to cope with the uncertainties associated with domestic supply, demand, and global wheat prices. The applicability and advantages of the developed model are demonstrated using real data from the wheat supply chain of Iran. Results illustrate that the current status of the wheat supply chain of Iran is far from optimality and there are many opportunities for improvement.

We are concerned with solving Fuzzy Flexible Linear programming (FFLP) problems. Even though, this model is very practical and is useful for many applications, but there are only a few methods for its situation. In most approaches proposed in the literature, the solution process needs at least, two phases where each phase needs to solve a linear programming problem. Here, we propose a method to solve the given problem in just one phase using only one problem. Furthermore, using our approach, sensitivity analysis of Fuzzy Flexible Linear programming (FFLP) problem is simpler. For an illustration of our method, some numerical examples given. In particular, a practical problem is formulated and is solved by our method and several other methods and the obtained results are compared.