Search for: genetic-algorithm
Total 1075 records
Article International Journal of Productivity and Quality Management ; Volume 18, Issue 4 , 2016 , Pages 518-536 ; 17466474 (ISSN) ; Noorossana, R ; Akhavan Niaki, S. T ; Sharif University of Technology
Inderscience Enterprises Ltd 2016
Employing profiles using variable sample size (VSS) may improve its effectiveness and hence is investigated in this paper. Besides, the implementation cost of a profile is an important factor in determining the main parameters. In this paper, the Lorenzen-Vance function is first extended to model implementation cost of VSS linear profiles. Then, the resulted economic model is solved using a genetic algorithm (GA). The average run length criterion when process is in control, ARL0 and the average run length measure when process goes out of control, ARL1 , is used to evaluate statistical properties of the designed profile. Moreover, a sensitivity analysis on the main parameters of the...
Article Journal of Modern Project Management ; Volume 4, Issue 2 , 2016 , Pages 64-73 ; 23173963 (ISSN) ; Akhavan Niaki, S. T ; Najafi, A. A ; Sharif University of Technology
Editora Mundos Sociais 2016
The present paper introduces a novel two-part self-adaptive technique in designing the genetic algorithm for project scheduling problems. One part of the algorithm includes a self-adaptive mechanism for genetic operators like crossover and mutation. The second part contains another self-adaptive mechanism for genetic parameters such as crossover probability. The parts come in turn repeatedly within a loop feeding each other with the information regarding the performance of operators or parameters. The capability of the method is tested and confirmed in comparison to metaheuristic and exact algorithms based on well-known benchmarks
A bi-objective multi-facility location-allocation problem with probabilistic customer locations and arrivals: two meta-heuristics using discrete approximation, Article Journal of Uncertain Systems ; Volume 12, Issue 2 , 2018 , Pages 123-140 ; 17528909 (ISSN) ; Akhavan Niaki, S. T ; Dadashi, M ; Sharif University of Technology
World Academic Union 2018
In this work, a bi-objective multi-facility location-allocation problem is investigated, in which the locations of the customers and their arrivals are stochastic. We first formulate the problem as a continuous location-allocation model with no constraints on the capacity of the facilities. Then, we develop an approximated discrete model in which the facilities with limited capacities can be located on a set of candidate points. The proposed model has two objective functions that are evaluated using discrete event system simulation. The first objective is to minimize the expected total time the customers spend in the system until their services begin. The time that each customer spends in...
Cost-based differential pricing for a make-to-order production system in a competitive segmented market, Article Journal of Revenue and Pricing Management ; Volume 19, Issue 4 , 2020 , Pages 266-275 ; Modarres, M ; Neishaboori, M ; Sharif University of Technology
Palgrave Macmillan 2020
Optimal queuing system design includes deciding about some variables such as location, capacity, price, and delivery time. In order to develop an optimized system, it is essential to solve the optimization problem for all the decision variables simultaneously. In this paper, a make-to-order system is considered. In this system, some facilities are developed in different points. According to the make-to-order system definition, these facilities keep no inventory from final product. Orders are received from customers and the requested products are assembled. Due to existence of some differences among customers, they are divided into two distinct categories including express and regular...
Article Proceedings of the 2008 16th International Conference on Networks, ICON 2008, 12 December 2008 through 14 December 2008, New Delhi ; 2008 ; 9781424438051 (ISBN) ; Mohammadi, M ; Movaghar, A ; Dehghan, M ; Sharif University of Technology
Sensor networks have recently emerged as a premier research topic. Sensor networks pose a number of new conceptual and optimization problems. Some, such as location, deployment, and tracking, are fundamental issues, in that many applications rely on them for needed information. While designing the sensor networks according to performed computation, the limited number of sensors to cover an area will be considered, so the proper placing of this limited number of sensors will cause costs to reduce regarding to coverage and development of the network in the next stage. In this paper we will present a genetic algorithm to solve the designing issue of the sensor network. The most important...
Application of the genetic algorithm to calculate the interaction parameters for multiphase and multicomponent systems, Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 26, Issue 3 , 2007 , Pages 89-102 ; 10219986 (ISSN) ; Ovaysi, S ; Taghikhani, V ; Ghotbi, C ; Sharif University of Technology
A method based on the Genetic Algorithm (GA) was developed to study the phase behavior of multicomponent and multiphase systems. Upon application of the GA to the thermodynamic models which are commonly used to study the VLE, VLLE and LLE phase equilibria, the physically meaningful values for the Binary Interaction Parameters (BIP) of the models were obtained. Using the method proposed in this work the activity coefficients for components at infinite dilution, obtained from the local composition based models, can be accurately predicted comparing to the experimental data available in the literature. In this work, a Global Optimization Procedure (GOP) based on the GA was developed to obtain...
Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 26, Issue 3 , 2007 , Pages 1-9 ; 10219986 (ISSN) ; Pishvaie, M. R ; Bozorgmehry, R ; Sharif University of Technology
For large and complex reacting systems, computational efficiency becomes a critical issue in process simulation, optimization and model-based control. Mechanism simplification is often a necessity to improve computational speed. We present a novel approach to simplification of reaction networks that formulates the model reduction problem as an optimization problem and solves it using genetic algorithm (GA).The aim of simplification kinetics modeling is to derive the simplest reaction system, which retains the essential features of the full system. Numerical results for H2/O2 combustion reaction mechanism illustrate the potential and proficiency of this approach
An exergetic model for the ambient air temperature impacts on the combined power plants and its management using the genetic algorithm, Article International Journal of Air-Conditioning and Refrigeration ; Volume 29, Issue 1 , 2021 ; 20101325 (ISSN) ; Norouzi, N ; Fani, M ; Sharif University of Technology
World Scientific 2021
4E analysis is used on a Brayton-Rankine combined cycle power plant (CCPP) with a dual pressure heat recovery steam generation (HRSG) system. A multi-objective genetic-based evolutionary optimization has been used to estimate the most optimal exergy efficiency status, exergy cost reduction, carbon emission reduction, and NOx emission reduction. For the validation of the data, the simulation results are compared with the plant's data. This study investigates the effect of every decisive parameter on the objective performance parameters of the CCPP. The primary estimated results are the emission rates, efficiencies, and the exergoeconomic cost of the system. At the optimum operational state,...
Critical temperature evaluation of moment frames by means of plastic analysis theory and genetic algorithm, Article Iranian Journal of Science and Technology - Transactions of Civil Engineering ; 2021 ; 22286160 (ISSN) ; Saedi Daryan, A ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH 2021
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...
Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 24, Issue 4 , 2005 , Pages 37-46 ; 10219986 (ISSN) ; Masoori, M ; Bozorgmehry Boozarjomehry, R ; Sharif University of Technology
This study is focused on the development of a systematic computational approach which implements Genetic Algorithm (GA) to find the optimal rigorous kinetic models. A general Kinetic model for hydrogenolysis of dibenzothiophene (DBT) based on Langmuir Hinshelwood type has been obtained from open literature. This model consists of eight continuous parameters(e.g., Arrhenus and Van't Hoff parameters) and six discrete parameters representing the order of the reaction with respect to each concentration. The optimal value of these parameters have been obtained based on Genetic Algorithm. Furthermore, the best type of Genetic operators and their corresponding parameters for this type of problems...
BEM/FEM simulation of acoustic field and shape optimization of submarine using neural network and genetic algorithm, Article 2004 International Symposium on Underwater Technology, UT'04, Taipei, 20 April 2004 through 23 April 2004 ; 2004 , Pages 283-287 ; 0780385411 (ISBN) ; Delnavaz, A ; Sharif University of Technology
Shape optimization of a submarine for minimized noise emission has been the objective of this work. Boundary element method and finite element methods have been employed to determine the acoustic field around the object. A combined neural network and genetic algorithm scheme is developed to find the optimum external geometric ratios of the submarine for a minimized emitted acoustic energy in certain reference points. The obtained optimum geometric values stay in normal range for minimum hydrodynamic forces and show a close agreement with the trend of change for models coming to operation. © 2004 IEEE
Article Proceedings of the 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies (DRPT2004), Hong Kong, 5 April 2004 through 8 April 2004 ; Volume 2 , 2004 , Pages 680-685 ; 0780382374 (ISBN); 9780780382374 (ISBN) ; Ranjbar, A. M ; Shirani, A. R ; Barkeseh, A ; Sharif University of Technology
In this paper we discuss an improved method for the calculation of Available Transfer Capability (ATC) in a restructured power system. The ATC calculation is performed through an optimal power flow approach. The objective function is to maximize the sum of the receiving-end load in a specified area as well as to send generation to other control areas while a minimum cost of generation is continuously achieved. The constraints are ac power flow equations and system operation limits. It is assumed that the generation cost curve of each generator is available. A genetic algorithm is used for the optimization process. An IEEE 30 bus test system is used for testing the proposed algorithm and the...
Article Iranian Journal of Science and Technology, Transaction B: Engineering ; Volume 28, Issue 2 B , 2004 , Pages 201-216 ; 03601307 (ISSN) ; Ghasemi, F ; Farrokhzad, D ; Sharif University of Technology
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....
An efficient algorithm for solving bi-objective fuzzy job-shop scheduling problems by genetic algorithms and data mining, Article Amirkabir (Journal of Science and Technology) ; Volume 15, Issue 58 D , 2004 , Pages 570-591 ; 10150951 (ISSN) ; Moghaddam, R. T ; Ranjbar, M ; Sharif University of Technology
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...
Article 2004 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Salt Lake City, UT, 28 September 2004 through 2 October 2004 ; Volume 2 A , 2004 , Pages 541-548 ; Pishkenari, H. N ; Gaskarimahalle, A. L ; Mahboobi, S. H ; Karimi, R ; Sharif University of Technology
American Society of Mechanical Engineers 2004
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...
Constrained model predictive control of MMA polymerization reactor based on genetic algorithm optimization, Article Proceedings of 2003 IEEE Conference on Control Applications, Istanbul, 23 June 2003 through 25 June 2003 ; Volume 1 , 2003 , Pages 464-469 ; Solgi, R ; Abbaszadeh, M ; Sharif University of Technology
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
Article 5th IFAC Symposium on Power Plants and Power Systems Control 2003, 15 September 2003 through 19 September 2003 ; Volume 36, Issue 20 , 2003 , Pages 547-552 ; 14746670 (ISSN) ; Ranjbar, A. M ; Shirane, A. R ; Sharif University of Technology
IFAC Secretariat 2003
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...
Article IEEE International Conference on Industrial Technology, IEEE ICIT 2002, 11 December 2002 through 14 December 2002 ; Volume 1 , 2002 , Pages 175-180 ; 0780376579 (ISBN) ; Taheri, J ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc 2002
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...
Article IEEE Antennas and Propagation Society, AP-S International Symposium (Digest) ; Volume 1 , 2002 , Pages 742-745 ; 15223965 (ISSN) ; Rashed Mohassel, J ; Sharif University of Technology
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
M.Sc. Thesis Sharif University of Technology ; Ardakanian, Reza
Long-term coordinated operation of hydro-thermal power systems has important rule in energy generation planning and management. Therefore a new approach for optimization and long-term planning of hydro-thermal power system is developed. In this research main parameters of the system like inflows and energy are considered as uncertain and so scenario optimization technique is applied. The advantage of this research compare to similar approaches is about applying two objective functions which minimize cost of energy generation and flood control.The Noisy GA and NSGA-II algorithms are used to run the model solving the khouzistan hydro-thermal power system in Iran.The results of this model is...