Sharif Digital Repository

The random PRF method has been suggested for the design of LPD (low probability of detection) radar signals. The LPD improvement in using this kind of signal is discussed quantitatively. First, a detection theoretic approach is used to find the optimum detectors of the unauthorised receiver (ESM receiver) and their performance for both constant PRF and random PRF signals. Then, the effect of the random PRF method on the authorised receiver (radar receiver) is investigated. Based on these analyses and definition of a proper measure, the constant PRF signals are compared with random PRF signals from the LPD point of view. By finding a simple formula for the improvement caused by the random PRF... 

In a competitive electricity market, a generation company (GenCo) optimizes its operation schedules, referred to as self-scheduling, in order to maximize its profit. However, various sources of uncertainty, such as market price fluctuations or forced outage of generating units, may impact the GenCo's profit. In this paper, a non-probabilistic information-gap model is proposed to model the uncertainties in short-term scheduling of a GenCo. The self-scheduling problem is formulated for risk-neutral, risk-averse, and risk-seeker GenCos. Robustness of the decisions against low market prices are evaluated using a robustness model. Furthermore, windfall higher profit due to unpredicted higher... 

The present study presents a new risk-constrained bidding strategy formulation of large electric utilities in, presence of demand response programs. The considered electric utility consists of generation facilities, along with a retailer part, which is responsible for supplying associated demands. The total profit of utility comes from participating in day-ahead energy markets and selling energy to corresponding consumers via retailer part. Different uncertainties, such as market price, affect the profit of the utility. Therefore, here, attempts are made to make use of Information Gap Decision Theory (IGDT) to obtain a robust scheduling method against the unfavorable deviations of the market... 

In this paper, we will discuss two special classes of mathematical programming models with fuzzy random variables. In the first model, a linear programming problem with fuzzy decision variables and fuzzy random coefficients is introduced. Then an algorithm is developed to solve the model based on fuzzy optimization method and fuzzy ranking method. In the second model, a fuzzy random quadratic spanning tree problem is presented. Then the proposed problem is formulated and solved by using the scalar expected value of fuzzy random variables. Furthermore, illustrative numerical examples are also given to clarify the methods discussed in this paper  

In this paper, we show that by considering the factor of usage in instruction bundles in VLIW processors and using the slots filled with NOPs in bundles, we can improve the overall performance by reducing the total execution time of the program. By our proposed scheme, Combined Bundle Scheduling (CBS), we have gained better performance compared to that for the PDT scheme (Predicted Decision Tree scheduling) which is the best scheduling strategy known so far. © 2006 IEEE  

In this paper, a new transmission expansion planning (TEP) model considering wind farms (WFs) optimal integration to power systems is proposed based on the information-gap decision theory (IGDT). The uncertainties of WFs output power and forecasted demand are considered in the problem, and IGDT is used to control the investment risk as well as to reduce the effects of these uncertainties on the investors' strategies. The TEP model is formulated for the risk-averse and risk-seeker investors through the robustness and opportunity models, respectively. Moreover, this TEP model allows WF lines and network lines to be added at multiple time points during a multi-stage time horizon. A genetic... 

This paper presented a combined scheduling and bidding algorithm for constructing the bidding curve of an electric utility that participated in the day-ahead energy markets. Day-ahead market price uncertainty was modeled using non-probabilistic information gap decision theory (IGDT). The considered utility consisted of generation units and a retailer part; the retailer part of the utility and its demand response program (DRP) could affect the utility's profit, which should be considered in the bidding strategy problem. The bidding strategy algorithm proposed in this paper dispatched units by optimizing the demand response programs of the retailer part. In addition, non-decreasing bidding... 

Deregulation in power systems has created new uncertainties and increased the previous ones. The presence of these uncertainties causes the transmission network to remain monopoly and the private investors not being interested in investing in this section. This paper presents a new merchant-based transmission expansion planning (TEP) formulation from the viewpoint of private investors. The information-gap decision theory (IGDT) is used to model the inherent uncertainties associated with the estimated investment cost of candidate lines and the forecasted system load and NSGAII is utilized to solve the multi-objective optimization problem. This algorithm helps private investors to select the... 

This paper suggests several improvements over the original Time-expanded Decision Network (TDN; a powerful and generic methodology introduced by Silver and de Weck for designing evolvable complex systems) in order to leverage its ease, flexibility, and scope of use. A more accurate model of the switching process, a simpler network representation, and the ability to address systems with unknown lifetime are some of the improvements. However, the most important added feature is the ability to account for other design requirements within the process, which enables the designers to embed the TDN methodology into their general concept exploration phase. As a result, the enhanced TDN (ETDN)... 

The secretary problems are of types of the optimal stopping theory problems and are also distinguished as well known problems in applied probability, statistics and decision theory fields. The importance of these kinds of problems defines many new conditions which have been discussed till now. The significance of these types of problems in social issues causes to define many conditions which are vastly discussed. In this paper, a new condition of this problem is considered. These conditions which have been performed using a real time method are based on Multi-Agent Systems techniques. In this paper, after evaluating this method, the resulted answers are examined using Multi-Agent system... 

This study develops a fuzzy multi-objective linear programming (FMOLP) model for solving the multi-objective no-wait flow shop scheduling problem in a fuzzy environment. The proposed model attempts to simultaneously minimize the weighted mean completion time and the weighted mean earliness. A numerical example demonstrates the feasibility of applying the proposed model to no-wait flow shop scheduling problem. The proposed model yields a compromised solution and the decision maker's overall levels of satisfaction. © 2008 The#Franklin#Institute  

The objective of this research is to design a method for selection of an appropriate location to establish plywood and veneer plants in Iran. Due to the climate of this region as well as the destruction of the forests and lack of proper plantation, the supporting forests to feed this industry are limited. Thus, it is vital to optimize the other strategically factors in order to make these plants capable of competing with the foreign plants which have access to less expensive input materials. In case of improper utilization of the resources, this industry can not compete with the imported products. The decision is made within the framework of benefits, opportunities, costs and risks (BOCR).... 

A novel approach in minimum time trajectory planning in Terrain Following/Terrain Avoidance (TF/TA) flight is proposed. In this research, terrain is understood based on fuzzy logic and small changes in terrain are omitted. Another novelty is constructing a relationship between slope of terrain and aircraft height with speed of aircraft by fuzzy approach. Finally after a decision making process and based on governing dynamics and cost function, trajectory is constructed by a polynomial. This method is state of the art in literature  

Video transcoding comprises the necessary operations for the conversion of a compressed video stream from one syntax to another one for inter-network communications, without the need of any further decoding and re-encoding process. The two most recent and popular standard video coders are H.263 and H.264. In this paper, we present tools to enable low complexity intra transcoding from H.263 to H.264 using a novel fast intra prediction mode decision algorithm that does not require extra computation. It is shown that due to basic similarities of H.263 and H.264 it is possible to reuse predictor side information, so this side information is used to simplify the mode and direction decision for... 

In a medium term planning horizon, a retailer should determine its forward contracting and pool participating strategies as well as the selling price to be offered to the customers. Considering a competitive retail electricity market, the number of clients being supplied by any retailer is a function of the selling prices and some other characteristics of all the retailers. This paper presents an equilibrium problem formulation to model the retailer's medium term decision making problem considering the strategy of other retailers. Decision making of any single retailer is formulated as a risk constraint stochastic programming problem. Uncertainty of pool prices and clients' demands is... 

This paper presents a risk-constrained programming approach to solve a retailer's medium-term planning problem. A retailer tries to maximize its profit via determining the optimal price offered to the customers as well as optimal strategy of participating in futures and pool markets. The uncertainty of pool prices is modeled by an envelope-bound information-gap model. Another source of uncertainty in this problem is the clients' demand, which is considered via a scenario generation method. The proposed method is formulated as a bi-level stochastic programming problem based on the information-gap decision theory. The Karush-Kuhn-Tucker optimality conditions are used to convert the bi-level...