Sharif Digital Repository

A special hybrid genetic algorithm (GA) is designed to solve the long-term coordination of hydro-thermal power systems with cascaded reservoirs and stochastic inflows. Since decision variables are continuous, in the proposed GA we employ real number rather than binary encoding. To create superior children we introduce dynamic tuning of the weights of operators. An exponential normalization is also developed such that better chromosomes have more chance to reproduce. To test the proposed method, 16 GAs are investigated which differ based on real or binary encoding, dynamic tuning or fixed weights for operators, inverse or exponential normalization and mixed or pure random initial populations.... 

This paper presents a meta-heuristic algorithm for solving bi-objective fuzzy job shop scheduling problems. These objectives are to minimize the makespan and minimize the early and late penalty. Processing time and due date are considered as fuzzy triangular numbers. This paper also introduces a novel use of data mining algorithm for solving of combinatorial optimization problems. The proposed algorithm combines genetic algorithms and an attribute-oriented induction algorithm, which is much quicker than previous methods providing the optimal solution. By considering the structure of proposed algorithm, the whole feasible solutions of a special job shop-scheduling problem are considered as a... 

This article presents an overview of the mechanical design features, fabrication and control of a Rescue Robot (CEDRA) for operation in unstructured environments. As a preliminary step, the essential characteristics of a robot in damaged and unstable situations have been established. According to these features and kinematical equations of the robot, design parameters are optimized by means of Genetic Algorithm. Optimum parameters are then utilized in construction. Upon fabrication, this unit has been tested in clean laboratory environment, as well as, ill-conditioned arenas similar to earthquake zones. The obtained results have been satisfactory in all aspects, and improvements are... 

Control of MMA polymerization batch reactor has intensively investigated. The nonlinear and time varying behavior of the system makes its control a challenging task. MPC algorithm is enjoying an increasing application for control of chemical processes. A sequential linearized model based predictive controller based on the DMC algorithm was designed to control the temperature of a batch MMA polymerization reactor. A genetic algorithm (GA) is suggested to optimize the cost function of DMC. The controller performance was studied via simulation. The controller performance in tracking the profile, noise and disturbances rejection is very good  

Due to the deregulation and restructuring in many countries, it is expected that amount of small-scale generations connected to the distribution networks increase. So it is necessary that impact of these kinds ofgenerators on VoltNar control would be investigated. This paper presents a new approach for VoltNar control in distribution system with Distributed Generation (DG) and it has shown that DG can improve the entire performance of network, by means of better controlling of the system and decreasing losses in network. In this approach Genetic Algorithm (GA) has been used as the optimization method where the amount of Dispersed Generation and its controlling parameters, Voltage regulators... 

In this paper, two new approaches, using the combination of Hopfield Neural Network and Genetic Algorithm for solving the Robot Motion Planning Problem both in Crisp and Fuzzified environments are presented. Based on the hypothesis of Genetic Algorithms, the Genomes and Chromosomes of the algorithm are modified so that they can he used to solve the Motion Planning Problem. Because of some problem restrictions and limits hinder us to use the generic Genetic Algorithm; some modifications are applied to the main algorithm to able us to solve the problem. Although the proposed algorithms are both rely on Genetic Algorithm, the heart of both is based on Hopfield Neural Network Robot Path Planner... 

The sidelobe level (SLL) of a linear array is optimized using modified continuous genetic algorithms (GAs) in this work. The amplitude and phase of the current as well as the separation of the antennas are all taken as variables to be controlled. The results of the design using modified GA versions are compared with other methods. Two design problems were studied several continuous modified GA version and the results are presented as several plots. As a final example, the design specifications for an array with 200 elements is given. The effectiveness and advantages of the modified GA version is outlined  

Nowadays, deliberate or unwanted fire incidents have created much attention to the behavior of structures against these types of events. Since the properties of structural members are influenced by the increase in the temperature of the members, it is more difficult to predict the general and local behavior of the structures during the fire. In this research, a method has been proposed to calculate the critical temperature in two-dimensional structures at its collapse with desirable accuracy. In this process, the upper-bound theory of plastic analysis is used. The plastic analysis is performed by applying the initial fire scenario to the structure, and its collapse load factor with the... 

In this paper, a multi-item multiperiod inventory control problem with all-unit and/or incremental quantity discount policies under limited storage capacity is presented. The independent random demand rates of the items in the periods are known and the items are supplied in distinct batch sizes. The cost consists of ordering, holding, and purchasing. The objective is to find the optimal order quantities of all items in different periods such that the total inventory cost is minimized and the constraint is satisfied. A mixed binary integer programming model is first developed to model the problem. Then, a parameter-tuned genetic algorithm (GA) is employed to solve it. Since there is no... 

In this paper, a multi-product economic production quantity problem with limited warehouse-space is considered in which the orders are delivered discretely in the form of multiple pallets and the shortages are completely backlogged. We show that the model of the problem is a constrained non-linear integer program and propose a genetic algorithm to solve it. Moreover, design of experiments is employed to calibrate the parameters of the algorithm for different problem sizes. At the end, a numerical example is presented to demonstrate the application of the proposed methodology  

The Stability of machining process depends on the dynamics of the machine tool, among other things. However, the dynamics of the machine tool changes when the tool is changed. To avoid the need for repeating the measurements, sub-structuring analysis may be used to couple the tool and spindle frequency response functions. A major difficulty in this approach is the determination of joint stiffness and damping between the two sub-structures. In particular, the measurement of rotational responses (RDOFs) at joints is a difficult task. In this research, a simple joint model that accounts for RDOFs is proposed. It is shown that this model avoids RDOF measurement while taking into account the... 

A hybrid genetic algorithm (HGA) was introduced to allocate optimum amount of gas. This method was applied to a group of wells in gas lift in the case of availability limited amount of gas. For testing the ability of the proposed HGA, the results of this work with those of previous works in a field with six wells were compared. Then for an Iranian southern west oil field with nine wells, gas allocation is performed using different amount of available gas. The results show that the introduced method (HGA) is very efficient tool in gas allocation issue  

In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idletime percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed... 

A flexible flow shop is a generalized flow shop with multiple machines in some stages. This system is fairly common in flexible manufacturing and in process industry. In most practical environments, scheduling is an ongoing reactive process where the presence of real time information continually forces reconsideration of pre-established schedules. This paper studies a flexible flow shop system considering non-deterministic and dynamic arrival of jobs and also sequence dependent setup times. The problem objective is to determine a schedule that minimizes average tardiness of jobs. Since the problem class is NP-hard, a novel dispatching rule and hybrid genetic algorithm have been developed to... 

In this paper, the capabilities of tuned mass dampers (TMDs) for the mitigation of response of nonlinear frame structures subjected to earthquakes have been studied. To determine the optimal parameters of a TMD, including its mass, stiffness and damping, we developed an optimization algorithm based on the minimization of a performance index, defined as a function of the response of the nonlinear structure to be controlled. Distributed genetic algorithm has been used to solve the optimization problem. For illustration, the method has been applied to the design of a linear TMD for an eight-story nonlinear shear building with bilinear hysteretic material behavior subjected to earthquake. The... 

In addition to reducing carbon dioxide (CO2) emission, the high oil recovery efficiency achieved by CO2 injection processes makes CO2 injection a desirable enhance oil recovery (EOR) technique. Minimum miscibility pressure (MMP) is an important parameter in successful designation of any miscible gas injection process such as CO2 flooding; therefore, its accurate determination is of great importance. The current experimental techniques for determining MMP are expensive and time-consuming. In this study, multi-gene genetic programming has been combined with constrained multivariable search methods, and a simple empirical model has been developed which provides a reliable estimation of MMP in a... 

This paper presents a novel approach for power allocation and cooperative node selection to enhance physical layer security in presence of an eavesdropper in a wireless network. Our network consists of a source–destination pair and a number of cooperative nodes which can be used as relays to increase throughput at the destination, or as friendly jammers to confuse eavesdropper. First, we introduce a low complexity method, for which relay−jammer selection and power allocation are performed, simultaneously. Then, we propose self-adaptive genetic algorithm to solve the non-linear non-convex programing problem. Using the proposed method, the number of friendly jammers that ensure the secrecy... 

In this paper, the effect of various arrangements of displacement, velocity and acceleration related weighting matrices on the performance of active control systems on nonlinear frames has been studied. Different arrangements of weighting matrices and feedback combinations of the response have been considered to design the active controllers using a single actuator for reducing the response of an eight-storey bilinear hysteretic frame under white noise excitations. The nonlinear Newmark-based instantaneous optimal control algorithm has been used, where the distributed genetic algorithm (DGA) is employed to determine the proper set of weighting matrices. For each set of feedback and weighting...