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simulation-and-optimization
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Modeling and Simulation Optimization of Hotel Revenue Management with Customer Choice Behavior
, M.Sc. Thesis Sharif University of Technology ; Shavandi, Hassan (Supervisor)
Abstract
In this thesis, the problem of the hotel revenue management with the customer choice behaiver has been studied . In this model , each customer has a preference order among the set of products. He purchased or booked his products according to his ordered list of preferences. Because the high number of hotel products are assumed, each customer can only choices different fare classes and the list of the preference customers is made up of different fare classes. Two different approaches have been used to solve this problem . The first approach is The linear programming model in which α percent of the capacity is allocated to business customers and the remaining capacity to leisuer customers...
A Robust Simulation Optimization Algorithm using Bayesian Method
, M.Sc. Thesis Sharif University of Technology ; Akhavan Niaki, Taghi (Supervisor)
Abstract
Huge availability of data in last decade has raised the opportunity to use data for decision making. The idea of using existing data to achieve more coherent reality solution has led to a branch of optimization called data-driven optimization. Presence of uncertain variables makes it crucial to design robust optimization methods for this area. On the other hand, in many real-world problems, the closed-form of the objective function is not available and a meta-model based framework is necessary. Motivated by this, we are using a Gaussian process in a Bayesian optimization framework to design a method that is consistent with the data in predefined confidence level. The goodness of the...
Simulation Optimization Using Hybrid and Adaptive Metamodels
, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor)
Abstract
In this thesis we propose a new metamodel based simulation optimization algorithm using sequential design of experiments. The main objective is to have a new method which can be used without deep knowledge of different kinds of metamodels, optimization techniques and design of experiments. The method uses three metamodels simulataneously and gradually adapts to the best metamodel. In each iteration, some points are chosen as candidates for future simulation. These points are ranked based on the quality of metamodel prediction and their placement among simulated points, the best point will be chosen for simulation. Comparing the proposed algorithm with some of the popular simulation...
Using Simulation-Optimization Approach for Fire Station Location and Vehicle Assignment Problem: a Case Study in Tehran, Iran
, M.Sc. Thesis Sharif University of Technology ; Amini, Zahra (Supervisor)
Abstract
In this research, the problem of locating fire stations and allocating equipment has been studied and a simulation-optimization approach has been presented to solve the problem. The mathematical models of this research were developed based on the idea of the randomness of the covered demand and the maximum expected coverage model. In these models, the issue of non-availability of equipment to cover accidents, the random nature of accidents, various fire incidents and the equipment needed to cover them are considered. Two mathematical models with deterministic and non-deterministic approach with different scenarios for demand are proposed. The non-deterministic model is developed with the aim...
A robust simulation optimization algorithm using kriging and particle swarm optimization: application to surgery room optimization
, Article Communications in Statistics: Simulation and Computation ; Volume 50, Issue 7 , 2021 , Pages 2025-2041 ; 03610918 (ISSN) ; Seifi, F ; Moghadam, S ; Sharif University of Technology
Taylor and Francis Ltd
2021
Abstract
Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)...
Optimisation of combined cooling, heating and power (CCHP) systems incorporating the solar and geothermal energy: a review study
, Article International Journal of Ambient Energy ; Volume 43, Issue 1 , 2022 , Pages 42-60 ; 01430750 (ISSN) ; Assareh, E ; Moltames, R ; Olazar, M ; Nedaei, M ; Parvaz, F ; Sharif University of Technology
Taylor and Francis Ltd
2022
Abstract
Recently, numerous studies have focused on simulation and optimisation of combined cooling, heat, and power (CCHP) systems. This research, from a different perspective, aims to conduct a comprehensive review of the studies performed in the field of solar, geothermal or combined sources, and subsequently analysing the multi-objective evolutionary algorithms to identify the most efficient situation, which satisfy researchers' needs in order to attain a better performance in their ongoing or future research projects. It is worth noting that multi-objective optimisation in these cycles is based on optimising a thermodynamic term (exergy efficiency, thermal efficiency, etc.) and an economic term...
A new metamodel-based method for solving semi-expensive simulation optimization problems
, Article Communications in Statistics: Simulation and Computation ; Volume 46, Issue 6 , 2017 , Pages 4795-4811 ; 03610918 (ISSN) ; Mahlooji, H ; Sharif University of Technology
Taylor and Francis Inc
2017
Abstract
In this article, a new algorithm for rather expensive simulation problems is presented, which consists of two phases. In the first phase, as a model-based algorithm, the simulation output is used directly in the optimization stage. In the second phase, the simulation model is replaced by a valid metamodel. In addition, a new optimization algorithm is presented. To evaluate the performance of the proposed algorithm, it is applied to the (s,S) inventory problem as well as to five test functions. Numerical results show that the proposed algorithm leads to better solutions with less computational time than the corresponding metamodel-based algorithm. © 2017 Taylor & Francis Group, LLC
A robust simulation optimization algorithm using kriging and particle swarm optimization: application to surgery room optimization
, Article Communications in Statistics: Simulation and Computation ; 2019 ; 03610918 (ISSN) ; Seifi, F ; Moghadam, S ; Sharif University of Technology
Taylor and Francis Inc
2019
Abstract
Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)...
A robust simulation optimization algorithm using kriging and particle swarm optimization: Application to surgery room optimization
, Article Communications in Statistics: Simulation and Computation ; 2019 ; 03610918 (ISSN) ; Seifi, F ; Moghadam, S ; Sharif University of Technology
Taylor and Francis Inc
2019
Abstract
Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)...
Simulation and optimization of pulsating heat pipe flat-plate solar collectors using neural networks and genetic algorithm: a semi-experimental investigation
, Article Clean Technologies and Environmental Policy ; Volume 18, Issue 7 , 2016 , Pages 2251-2264 ; 1618954X (ISSN) ; Kargarsharifabad, H ; Abbasi Godarzi, A ; Ghofrani, A ; Shafii, M. B ; Sharif University of Technology
Springer Verlag
2016
Abstract
This research study presents an investigation on the behavior of a Pulsating Heat Pipe Flat-Plate Solar Collector (PHPFPSC) by artificial neural network method and an optimization of the parameters of the collector by genetic algorithm. In this study, several experiments were performed to study the effects of various evaporator lengths, filling ratios, inclination angles, solar radiation, and input chilled water temperature between 9:00 A.M. to 5:00 P.M., and the output temperature of the water tank, which was the output of the system, was also measured. According to the input and output information, multilayer perceptron neural network was trained and used to predict the behavior of the...
Simulation and optimization of a pulsating heat pipe using artificial neural network and genetic algorithm
, Article Heat and Mass Transfer/Waerme- und Stoffuebertragung ; Volume 52, Issue 11 , 2016 , Pages 2437-2445 ; 09477411 (ISSN) ; Abbasi Godarzi, A ; Saber, M ; Shafii, M. B ; Sharif University of Technology
Springer Verlag
Abstract
In this paper, a novel approach has been presented to simulate and optimize the pulsating heat pipes (PHPs). The used pulsating heat pipe setup was designed and constructed for this study. Due to the lack of a general mathematical model for exact analysis of the PHPs, a method has been applied for simulation and optimization using the natural algorithms. In this way, the simulator consists of a kind of multilayer perceptron neural network, which is trained by experimental results obtained from our PHP setup. The results show that the complex behavior of PHPs can be successfully described by the non-linear structure of this simulator. The input variables of the neural network are input heat...
Study of association of 2-methoxyethanol in the aqueous phase
, Article Theoretical Chemistry Accounts ; Volume 106, Issue 3 , 2001 , Pages 194-198 ; 1432881X (ISSN) ; Jalili, S ; Sharif University of Technology
Springer New York
2001
Abstract
Monte Carlo simulations have been carried out for 2-methoxyethanol in an isothermal-isobaric ensemble (NPT) at 298.15 K and 1 atm pressure. The optimized potential for liquid simulation force field parameters has been used for modeling 2-methoxyethanol and the TIP4P model for water. Intramolecular rotations are described by an analytical potential function fitted to ab initio energies. It has been shown that the water molecules can form hydrogen bonds between adjacent O atoms of CH3OCH2CH2OH in aqueous media. The self-association of 2-methoxyethanol in aqueous media has been studied by statistical perturbation theory
A system dynamics approach to analyze water resources systems
, Article 31st IAHR Congress 2005: Water Engineering for the Future, Choices and Challenges, 11 September 2005 through 16 September 2005 ; 2005 , Pages 4991-5000 ; 8987898245 (ISBN); 9788987898247 (ISBN) ; Baradarannia, M.R ; Sarang, A ; Hjorth, P ; Byong-Ho J ; Sang I.L ; Won S.I ; Gye-Woon C ; Sharif University of Technology
Korea Water Resources Association
2005
Abstract
Several mathematical modeling approaches are used to model water resources systems such as deterministic and non-deterministic, lumped and distributed, steady and dynamic, simulation and optimization approaches. All these modeling paradigms - categorized as open systems - assume that the input conditions to the system will not change during their operation. What is happening in the real world is somewhat different. Due to their dynamic behaviors, real world events exert feedbacks from their outputs to their inputs which may cause the input conditions vary with time. This is the main focus of the system dynamics theory which has been introduced in this paper to be applied in water resources...
Simulation, optimization & control of styrene bulk polymerization in a tubular reactor
, Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 32, Issue 4 , 2013 , Pages 69-79 ; 10219986 (ISSN) ; Mohammad, S ; Hossein, A ; Sharif University of Technology
Jihad Danishgahi
2013
Abstract
In this paper, optimization and control of a tubular reactor for thermal bulk post-polymerization of styrene have been investigated. By using the reactor mathematical model, static and dynamic simulations are carried out. Based on an objective function including polymer conversion and polydispersity, reactor optimal temperature profile has been obtained. In the absence of model mismatch, desired product characteristic can also be obtained by applying the corresponding reactor wall or jacket temperature profile. To achieve this temperature trajectory, reactor jacket is divided into three zones and jacket inlet temperatures are used as manipulated variables. Effectiveness of the proposed...
Simulation and optimization of HEMTs
, Article 3rd International Conference on Advances in Computational Tools for Engineering Applications, 13 July 2016 through 15 July 2016 ; 2016 , Pages 1-6 ; 9781467385237 (ISBN) ; Ashrafi, R ; Khorasani, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
Abstract
We have developed a simulation system for nanoscale high-electron mobility transistors, in which the self-consistent solution of Poisson and Schrödinger equations is obtained with the finite element method. We solve the exact set of nonlinear differential equations to obtain electron wave function, electric potential distribution, electron density, Fermi surface energy and current density distribution in the whole body of the device. For more precision, local dependence of carrier mobility on the electric field distribution is considered. We furthermore compare the simulation to a recent experimental measurement and observe perfect agreement. We also propose a novel graded channel design,...
Post Optimal Analysis application on the reliability evaluation of the Iran power grid
, Article EEEIC 2012, Venice, 18 May 2012 through 25 May 2012 ference on Environment and Electrical Engineering, EE ; 2012 , Pages 873-878 ; 9781457718281 (ISBN) ; Fotuhi-Firuzabad, M ; Sharif University of Technology
IEEE
2012
Abstract
Access to a computational tractable method for representing the system more realistically has always been an important issue in power system reliability assessment. The Post Optimal Analysis (POA), as a well recognized technique to attack a set of similar optimization problems, has been successfully used to assess the reliability of composite systems. This method exploits the similarity of the system states to speed up the contingency evaluation procedure without sacrificing the accuracy of the results. In this paper, the performance and practical feasibility of the POA technique for power system reliability evaluation is tested using the Iran power grid. The POA based approach is applicable...
Robust simulation optimization using φ-divergence
, Article International Journal of Industrial Engineering Computations ; Volume 7, Issue 4 , 2016 , Pages 517-534 ; 19232926 (ISSN) ; Mahlooji, H ; Sharif University of Technology
Growing Science
Abstract
We introduce a new robust simulation optimization method in which the probability of occurrence of uncertain parameters is considered. It is assumed that the probability distributions are unknown but historical data are on hand and using φ-divergence functionality the uncertainty region for the uncertain probability vector is defined. We propose two approaches to formulate the robust counterpart problem for the objective function estimated by Kriging. The first method is a minimax problem and the second method is based on the chance constraint definition. To illustrate the methods and assess their performance, numerical experiments are conducted. Results show that the second method obtains...
Assessment of a parallel evolutionary optimization approach for efficient management of coastal aquifers
, Article Environmental Modelling and Software ; Volume 74 , December , 2015 , Pages 21-38 ; 13648152 (ISSN) ; Ataie Ashtiani, B ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
This study presents a parallel evolutionary optimization approach to determine optimal management strategies of large-scale coastal groundwater problems. The population loops of evolutionary algorithms (EA) are parallelized using shared memory parallelism to address the high computational demands of such applications. This methodology is applied to solve the management problems in an aquifer system in Kish Island, Iran using a three-dimensional density-dependent groundwater numerical model. EAs of continuous ant colony optimization (CACO), particle swarm optimization, and genetic algorithm are utilized to solve the optimization problems. By implementing the parallelization strategy, a...
A novel methodology for designing a multi-ejector refrigeration system
, Article Applied Thermal Engineering ; Volume 151 , 2019 , Pages 26-37 ; 13594311 (ISSN) ; Hakkaki Fard, A ; Sharif University of Technology
Elsevier Ltd
2019
Abstract
Ejector refrigeration system has many advantages over traditional compressor-based systems, including: simplicity, low installation and operating costs and the ability to operate with low-grade thermal energy sources. However, its main drawbacks are low Coefficient of Performance (COP) and failure at high ambient temperatures. To overcome these problems, a novel methodology for designing a multi-ejector refrigeration system is proposed. This system utilizes a parallel array of ejectors instead of one ejector. Therefore, the system can continuously operate at its optimum efficiency. Each ejector works within a specific range of condensing pressures. The condenser pressure governs the...
Finite element optimization of sample geometry for measuring the torsional shear strength of glass/metal joints
, Article Ceramics International ; Volume 46, Issue 4 , 2020 , Pages 4857-4863 ; Malzbender, J ; Groß Barsnick, S. M ; Abdoli, H ; Kokabi, A. H ; Faghihi Sani, M. A ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
Assessment of mechanical properties of glass/metal joints is a challenging process, especially when the application relevant conditions of the joints have to be considered in the test design. In this study, a finite element method (FEM) is implemented to analyze a torsional shear strength test designed for glass-ceramic/steel joints aiming towards solid oxide fuel/electrolysis cells application. Deviations from axial symmetry of the square flanges (ends) of respective hourglass-shaped specimens and also supporting and loading sockets of the test set-up are included in the model to simulate conditions close to reality. Undesirable tensile stress and also shear stress concentration appear at...