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    A multi-operator Imperialist Competitive Algorithm for solving Non-Convex Economic Dispatch problem

    , Article Indian Journal of Science and Technology ; Volume 9, Issue 6 , 2016 ; 09746846 (ISSN) Eghbalpour, H ; Nabati Rad, M ; Hassani, R ; Sharif University of Technology
    Indian Society for Education and Environment 
    Abstract
    Non-Convex Economic Dispatch (NED) has been addressed as an open and demanding optimization problem in power systems. Due to the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods are unable to effectively find the global solution. In recent years, because of their great potential to achieve optimal or close-to-optimal solution, meta-heuristic optimization techniques have attracted significant attention to tackle the complexity of NED problems. In this paper, an efficient approach is proposed based on Imperialist Competitive Algorithm (ICA). The proposed algorithm named multi-operator ICA (MuICA) merges the... 

    Multi-objective optimization of direct coupling photovoltaic-electrolyzer systems using imperialist competitive algorithm

    , Article ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE) ; Vol. 6A , November , 2014 Maroufmashat, A ; Sayedin, F ; Sattari, S ; Sharif University of Technology
    Abstract
    Photovoltaic-electrolyzer systems are one of the most promising alternatives for obtaining hydrogen from a renewable energy source. Determining size and the operational conditions are always a key issue while coupling directly renewable electricity sources to PEM electrolyzer. In this research, the multi objective optimization approach based on an imperialist competitive algorithm (ICA), which is employed to optimize the size and the operating conditions of a directly coupled photovoltaic (PV)-PEM electrolyzer. This allows the optimization of the system by considering two different objectives, including, minimization of energy transfer loss and maximization of hydrogen generation. Multi... 

    An imperialist competitive algorithm for service composition and optimal selection in cloud manufacturing

    , Article 5th International Symposium on Computational and Business Intelligence, ISCBI 2017, 11 August 2017 through 14 August 2017 ; 2017 , Pages 129-133 ; 9781538617717 (ISBN) Akbaripour, H ; Houshmand, M ; Kerdegari, A ; Sharif University of Technology
    Abstract
    Cloud manufacturing is an emerging service-oriented manufacturing paradigm that integrates and manages distributed manufacturing resources through which complex manufacturing demands with a high degree of customization can be fulfilled. The process of Service Composition and Optimal Selection (SCOS) is an important issue for practical implementation of cloud manufacturing. In this paper, a new Mixed Integer Programming (MIP) model for solving the SCOS with transportation consideration has been proposed. This model minimizes both manufacturing and transportation costs subject to some constraints such as necessity of transportation between manufacturing resources and the requirements specified... 

    Service composition and optimal selection in cloud manufacturing: landscape analysis and optimization by a hybrid imperialist competitive and local search algorithm

    , Article Neural Computing and Applications ; 2018 ; 09410643 (ISSN) Akbaripour, H ; Houshmand, M ; Sharif University of Technology
    Springer London  2018
    Abstract
    Cloud manufacturing as an emerging service-oriented manufacturing paradigm integrates and manages geographically distributed manufacturing resources such that complex and highly customized manufacturing tasks can be performed cooperatively. The service composition and optimal selection (SCOS) problem, in which manufacturing cloud services are optimally selected for performing subtasks, is one of the key issues for implementing a cloud manufacturing system. In this paper, we propose a new mixed-integer programming model for solving the SCOS problem with sequential composition structure. Unlike the majority of previous research on the problem, in the proposed model, the transportation between... 

    Service composition and optimal selection in cloud manufacturing: landscape analysis and optimization by a hybrid imperialist competitive and local search algorithm

    , Article Neural Computing and Applications ; Volume 32, Issue 15 , 2020 , Pages 10873-10894 Akbaripour, H ; Houshmand, M ; Sharif University of Technology
    Springer  2020
    Abstract
    Cloud manufacturing as an emerging service-oriented manufacturing paradigm integrates and manages geographically distributed manufacturing resources such that complex and highly customized manufacturing tasks can be performed cooperatively. The service composition and optimal selection (SCOS) problem, in which manufacturing cloud services are optimally selected for performing subtasks, is one of the key issues for implementing a cloud manufacturing system. In this paper, we propose a new mixed-integer programming model for solving the SCOS problem with sequential composition structure. Unlike the majority of previous research on the problem, in the proposed model, the transportation between... 

    Wind Farm Layout Optimization

    , M.Sc. Thesis Sharif University of Technology Kiamehr, Koosha (Author) ; Kazemzadeh Hannani, Siamak (Supervisor)
    Abstract
    In this work, wind farm layout optimization problem is dealt with a new approach. The aim of this work is maximizing the output power of a wind farm by considering wake loses. Layout optimization minimizes the wake loses regarding the wind direction. Three different wind scenarios including different wind direction angles, wind direction blowing probabilities and Weibull distribution parameters for wind speed are assumed. Since, the problem is nonlinear and constrained, imperialist competitive algorithm is used as a modern and powerful algorithm for continuous optimization problems. The optimization outcomes indicate that imperialist competitive algorithm yields promising results.... 

    Optimal distribution of the injured in a multi-type transportation network with damage-dependent travel times: Two metaheuristic approaches

    , Article Socio-Economic Planning Sciences ; 2018 ; 00380121 (ISSN) Shiripour, S ; Mahdavi Amiri, N ; Sharif University of Technology
    Elsevier Ltd  2018
    Abstract
    We study a location-allocation-routing problem for distribution of the injured in a disaster response scenario, considering a three-type transportation network with separate links. A circle-based approach to estimate the impacts of the disaster is presented. After formulating relations for computing the percentage of the injured, the destruction percentage and the damage-dependent travel times, the problem is formulated as an integer nonlinear program. We utilize a genetic algorithm and a discrete version of the imperialist competitive algorithm for solving large problems. An empirical study focused on earthquakes in Tabriz, Iran, illustrates applicability of the proposed model and... 

    Feasibility of imperialist competitive algorithm to predict the surface settlement induced by tunneling

    , Article Engineering with Computers ; 2018 ; 01770667 (ISSN) Tashayo, B ; Behzadafshar, K ; Soltani Tehrani, M ; Afkhami Banayem, H ; Hashemi, M. H ; Taghavi Nezhad, S. S ; Sharif University of Technology
    Springer London  2018
    Abstract
    Surface settlement is considered as an adverse effect induced by tunneling in the civil projects. This paper proposes the use of the imperialist competitive algorithm (ICA) for predicting the maximum surface settlement (MMS) resulting from the tunneling. For this work, three forms of equations, i.e., linear, quadratic and power are developed and their weights are then optimized/updated with the ICA. The requirement datasets were collected from the line No. 2 of Karaj urban railway, in Iran. In the ICA models, vertical to horizontal stress ratio, cohesion and Young’s modulus, as the effective parameters on the MSS, are adopted as the inputs. The statistical performance parameters such as root... 

    Feasibility of imperialist competitive algorithm to predict the surface settlement induced by tunneling

    , Article Engineering with Computers ; Volume 35, Issue 3 , 2019 , Pages 917-923 ; 01770667 (ISSN) Tashayo, B ; Behzadafshar, K ; Soltani Tehrani, M ; Afkhami Banayem, H ; Hashemi, M. H ; Taghavi Nezhad, S. S ; Sharif University of Technology
    Springer London  2019
    Abstract
    Surface settlement is considered as an adverse effect induced by tunneling in the civil projects. This paper proposes the use of the imperialist competitive algorithm (ICA) for predicting the maximum surface settlement (MMS) resulting from the tunneling. For this work, three forms of equations, i.e., linear, quadratic and power are developed and their weights are then optimized/updated with the ICA. The requirement datasets were collected from the line No. 2 of Karaj urban railway, in Iran. In the ICA models, vertical to horizontal stress ratio, cohesion and Young’s modulus, as the effective parameters on the MSS, are adopted as the inputs. The statistical performance parameters such as root... 

    Design and Implementation of Evolutionary Network Defusion Model as a Tool for Network Marketing

    , M.Sc. Thesis Sharif University of Technology Nouri Khoshknab, Hamid (Author) ; Shavandi, Mohammad Hassan (Supervisor)
    Abstract
    People’s interaction and their impressions on each other has been one of the specifications of the societies; which has been studied and are used in various ways for widening the circle of thoughts and introducing the concepts. Low cost of the use of this method and feasibility of controlling the sensitivity about the considered issue (and some times the source of the issue), are the advantages of this advancement. This issue has also had numerous usages in the marketing and business. In this thesis an approximate algorithm has been designed for extracting the structure of the network, diffusion rate and the effective nodes in the network. This algorithm is... 

    An imperialist competitive algorithm approach for multi-objective optimization of direct coupling photovoltaic-electrolyzer systems

    , Article International Journal of Hydrogen Energy ; Vol. 39, Issue 33 , 11 November , 2014 , pp. 18743-18757 ; ISSN: 03603199 Maroufmashat, A ; Sayedin, F ; Khavas, S. S
    Abstract
    In the context of sustainable clean hydrogen production pathways, photovoltaic-electrolyzer systems are one of the most promising alternatives for acquiring hydrogen from renewable energy sources. In fact, determining the optimal set of design and operating variables are always a key issue while coupling directly renewable electricity sources to PEM electrolyzers. Few previous studies have attempted to find the optimal size and operational condition of directly coupled photovoltaic-electrolyzer (PV/El) systems in order to maximize the hydrogen production or to minimize energy transfer loss between photovoltaic devices and the electrolyzer. Nevertheless an easy and efficient approach still... 

    Wind farm layout optimization using imperialist competitive algorithm

    , Article Journal of Renewable and Sustainable Energy ; Vol. 6, Issue. 4 , July , 2014 ; ISSN: 19417012 Kiamehr, K ; Hannani, S. K ; Sharif University of Technology
    Abstract
    In this work, the wind farm layout optimization problem is dealt with using a new approach. The aim of wind farm layout optimization is to maximize the output power of a wind farm considering the wake losses. Layout optimization minimizes the wake losses regarding the location of the turbines. Three different wind scenarios with different wind direction angles, wind direction blowing probabilities, and Weibull distribution parameters are assumed. Since, the problem is nonlinear and constrained, imperialist competitive algorithm is used as a modern and powerful algorithm for continuous optimization problems. The optimization outcomes indicate that imperialist competitive algorithm yields... 

    Disaster relief on destructive transportation networks using a circle-based approach

    , Article Transportation Letters ; Volume 13, Issue 8 , 2021 , Pages 568-590 ; 19427867 (ISSN) Shiripour, S ; Mahdavi Amiri, N ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    We formulate an integrated mathematical model for distribution of the injured on a three-type transportation network with destroyable independent links and with actual travel times considering two different groups of the injured. The aim is to find the temporary locations for aid stations and their capacities, the percentage of the injured with various severities allocated to each station and to different routes and the number of vehicles so that the total relief time is minimized. For this, we present a new approach, called circle-based approach, in which the effects of the disaster are considered as a number of concentric circular regions. The original problem is formulated as an integer... 

    An evolutionary optimization-based approach for simulation of endurance time load functions

    , Article Engineering Optimization ; Volume 51, Issue 12 , 2019 , Pages 2069-2088 ; 0305215X (ISSN) Mashayekhi, M. R ; Esmail pour Estekanchi, H ; Vafai, H ; Ahmadi, G ; Sharif University of Technology
    Taylor and Francis Ltd  2019
    Abstract
    A novel optimization method based on Imperialist Competitive Algorithm (ICA) for simulating endurance time (ET) excitations was proposed. The ET excitations are monotonically intensifying acceleration time histories that are used as dynamic loading. Simulation of ET excitations by using evolutionary algorithms has been challenging due to the presence of a large number of decision variables that are highly correlated due to the dynamic nature of the problem. Optimal parameter values of the ICA algorithm for simulating ETEFs were evaluated and were used to simulate ET excitations. In order to increase the capability of the ICA and provide further search in the optimization space, this... 

    Advanced modeling and control of 5 MW wind turbine using global optimization algorithms

    , Article Wind Engineering ; Volume 43, Issue 5 , 2019 , Pages 488-505 ; 0309524X (ISSN) Jafari, S ; Majidi Pishkenari, M ; Sohrabi, S ; Feizarefi, M ; Sharif University of Technology
    SAGE Publications Inc  2019
    Abstract
    This article presents a methodological approach for controller gain tuning of wind turbines using global optimization algorithms. For this purpose, the wind turbine structural and aerodynamic modeling are first described and a complete model for a 5 MW wind turbine is developed as a case study based on a systematic modeling approach. The turbine control requirements are then described and classified using its power curve to generate an appropriate control structure for satisfying all turbine control modes simultaneously. Next, the controller gain tuning procedure is formulated as an engineering optimization problem where the command tracking error and minimum response time are defined as... 

    A Multisource Location-routing-inventory Problem with Backlogging

    , M.Sc. Thesis Sharif University of Technology Ghorbani, Atiye (Author) ; Akbari Jokar, Mohammad Reza (Supervisor)
    Abstract
    This thesis studies a multi-product location-routing-inventory problem in which location-allocation, inventory and routing decisions are to be taken in a three-level supply chain including suppliers, depots and customers. Each product for each depot could be supplied by more than one supplier and each supplier has a limited supplying capacity per period. Products are distributed from depots to customers by a homogeneous fleet of vehicles. Backlogging is allowable for each customer on the condition of not exceeding a fraction of customer’s demand. A mixed-integer programming formulation is presented to describe the problem then a new hybrid heuristic algorithm based on the simulated annealing... 

    Characterization and Investigating the Effectiveness of Reservoir uncertainty on Waterflooding in a Shared Oil Field

    , M.Sc. Thesis Sharif University of Technology Panbei, Mahdi (Author) ; Masihi, Mohsen (Supervisor) ; Ayatollahi, Shahaboddin (Supervisor)
    Abstract
    In field management workflow, after preparation of dynamic reservoir model, next step is determining the uncertain parameters and history matching. In this step, simulation model is conditioned to available field data. In this inverse problem, different geological and petrophysical properties may provide equally good history matches. Such diverse models are likely to show different production behaviors in future. This ties the history matching with the second step, uncertainty quantification of predictions. Multiple history matched models are essential for a realistic uncertainty estimate of the future field behavior.This thesis introduces the application of two novel population-based... 

    Energy Optimization of an Arm with Seven Degrees of Freedom Using Imperialistic Competitive Algorithm (ICA) and Designing an Artificial Neural Network

    , M.Sc. Thesis Sharif University of Technology Abedini, Amin (Author) ; Ahmadian, M.T (Supervisor) ; Asghari, M (Supervisor)
    Abstract
    In recent years, great attention has been devoted to the design of artificial arms. The most crucial problem in such a design is the trajectory of movement. In this paper, a seven degree of freedom arm is modeled and simulated. Also, the optimization method named “Imperialistic Competitive Algorithm” has been modified and better performance of the new version is presented. Energy optimization is performed based on trajectory of the arm with angular velocity, angular acceleration and joint angles using modified imperialistic competitive algorithm (ICA). Considering ICA as a fast optimization algorithm, it would be reasonable to use this algorithm for robotic purposes for online answering. The... 

    Generation of Endurance Time Excitation Functions using Wavelet Transform and Heuristic Optimization Methods

    , Ph.D. Dissertation Sharif University of Technology Mashayekhi, Mohammad Reza (Author) ; Vafai, Abolhassan (Supervisor) ; Esmaeil Purestekanchi, Homayoon (Supervisor)
    Abstract
    Endurance Time (ET) method is a dynamic analysis in which structures are subjected to intensifying acceleration time histories. These excitations are also called Endurance Time Excitation Functions (ETEF). The reliability and accuracy of the ET method heavily depends on the accuracy of ETEFs. ETEFs are generated so that ETEFs dynamic characteristics must be consistent with dynamic characteristics of real ground motions. Since the number of ETEFs equations are considerably more than variables noninear optimization is used to generate ETEFs. In order to improve the accuracy of ETEFs two approaches can be used. First, modifying the objective function equations by considering more dynamic... 

    A Novel Metamodel-based Simulation Optimization Algorithm using a Hybrid Sequential Experimental Design

    , M.Sc. Thesis Sharif University of Technology Ajdari, Ali (Author) ; Mahlooji, Hashem (Supervisor)
    Abstract
    In this work, we propose a metamodel-based simulation optimization algorithm using a novel hybrid sequential experimental design. The algorithm starts with a metamodel construction phase in which at each stage, a sequential experimental design is used to select a new sample point from the search space using a hybrid exploration-exploitation search strategy. Based on the available design points at each stage, a metamodel is constructed using Artificial Neural Network (ANN) and Kriging interpolation techniques. The resulting metamodel is then used in the optimization process to evaluate new solutions. We use Imperialist Competitive Algorithm (ICA) which is a powerful population-based...