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    Optimal design and operation of a photovoltaic-electrolyser system using particle swarm optimisation

    , Article International Journal of Sustainable Energy ; 2014 ; ISSN: 14786451 Sayedin, F ; Maroufmashat, A ; Roshandel, R ; Khavas, S. S
    Abstract
    In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different... 

    An integrated mathematical programming model for a dynamic cellular manufacturing system with limited resources

    , Article International Journal of Services and Operations Management ; Volume 37, Issue 1 , January , 2020 , Pages 1-26 Mehdizadeh, E ; Shamoradifar, M ; Akhavan Niaki, S. T ; Sharif University of Technology
    Inderscience Enterprises Ltd  2020
    Abstract
    This paper proposes an integrated integer nonlinear programming model for a concurrent cell formation and production planning problem in a dynamic cell-manufacturing system (DCMS) with limited resources to setup cells and to procure machines. The proposed model seeks to minimise the total costs associated with the production planning and the cell construction and formation under a dynamic system. To validate the model, it is first converted to a linear programming. Then, a numerical example is presented based on which the branch and bound method is used to solve it employing the Lingo 8 software. Besides, due to NP-hardness of the problem, two meta-heuristic algorithms namely a GA and a PSO... 

    A Weibull distributed deteriorating inventory model with all-unit discount, advance payment and variable demand via different variants of PSO

    , Article International Journal of Logistics Systems and Management ; Volume 40, Issue 2 , 2021 , Pages 145-170 ; 17427967 (ISSN) Duary, A ; Banerjee, T ; Shaikh, A. A ; Akhavan Niaki, S. T ; Bhunia, A. K ; Sharif University of Technology
    Inderscience Publishers  2021
    Abstract
    The goal of this research is to formulate an inventory control problem of a single item with variable demand dependent on displayed stock level and selling price of the commodity. The item deteriorates based on a three-parameter Weibull distribution and advance payment is needed to purchase the item with the all-unit discount policy. Shortages are allowed partially and backlogged with the rate dependent on the length of customers' waiting time. The corresponding problem is formulated as a profit maximisation model. For solving this problem, four different variants of particle swarm optimisation (PSO) are utilised. Then, the application of the model is illustrated with the help of a numerical... 

    Flowshop sequence-dependent group scheduling with minimisation of weighted earliness and tardiness

    , Article European Journal of Industrial Engineering ; Volume 13, Issue 1 , 2019 , Pages 54-80 ; 17515254 (ISSN) Keshavarz, T ; Salmasi, N ; Varmazyar, M ; Sharif University of Technology
    Inderscience Enterprises Ltd  2019
    Abstract
    In this research, we approach the flowshop sequence-dependent group scheduling problem with minimisation of total weighted earliness and tardiness as the objective for the first time. A mixed integer linear programming model is developed to solve the problem optimally. Since the proposed research problem is proven to be NP-hard, a hybrid meta-heuristic algorithm based on the particle swarm optimisation (PSO) algorithm, enhanced with neighbourhood search is developed to heuristically solve the problem. Since the objective is a non-regular, a timing algorithm is developed to find the best schedule for each sequence provided by the metaheuristic algorithm. A lower bounding method is also... 

    Integration of the intelligent optimisation algorithms with the artificial neural networks to predict the performance of a counter flow wet cooling tower with rotational packing

    , Article International Journal of Ambient Energy ; 2021 ; 01430750 (ISSN) Assari, N ; Assareh, E ; Alirahmi, M ; Hosseini, H ; Nedaei, M ; Rahimof, Y ; Fathi, A ; Behrang, M ; Jafarinejad, T ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    The present study investigated a counter-flow cooling tower performance by integrating the Artificial Neural Networks and Intelligent Optimisation Algorithms (ANN-IOAs). For this purpose, two scenarios were evaluated. In the first scenario, inlet air wet-bulb temperature (T aw), inlet air dry bulb temperature (T ad), water to the air mass flow rate ratio (mw /ma), and rotor speed (υ) were the input parameters for the ANNs, while the output temperature (T wo) was the ANNs output. In the second scenario, the same input parameters applied for the first scenario were used as input variables and the tower efficiency (ε) was considered as an output parameter. The well-known IOAs methods, namely,... 

    Hybrid bi-objective economic lot scheduling problem with feasible production plan equipped with an efficient adjunct search technique

    , Article International Journal of Systems Science: Operations and Logistics ; 2022 ; 23302674 (ISSN) Kayvanfar, V ; Zandieh, M ; Arashpour, M ; Sharif University of Technology
    Taylor and Francis Ltd  2022
    Abstract
    In this research, the economic lot scheduling problem (ELSP), as an NP-hard problem in terms of a bi-objective approach considering deteriorating items and shortage, is studied. The goal is to simultaneously minimise ‘setup and inventory holding costs, comprising deterioration’, and ‘total amount of units facing shortage throughout every period. Two policies besides a heuristic method are employed simultaneously, named extended basic period and Power-of-Two (PoT), to make sure of having feasible replenishment cycles. For handling the considered problem, three multi-objective techniques are employed: non-dominated sorting genetic algorithm II (NSGAII), non-dominated ranking genetic algorithm... 

    Optimal design and operation of a photovoltaic–electrolyser system using particle swarm optimisation

    , Article International Journal of Sustainable Energy ; Volume 35, Issue 6 , 2016 , Pages 566-582 ; 14786451 (ISSN) Sayedin, F ; Maroufmashat, A ; Roshandel, R ; Sattari Khavas, S ; Sharif University of Technology
    Taylor and Francis Ltd 
    Abstract
    In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different... 

    Integration of the intelligent optimisation algorithms with the artificial neural networks to predict the performance of a counter flow wet cooling tower with rotational packing

    , Article International Journal of Ambient Energy ; Volume 43, Issue 1 , 2022 , Pages 5780-5787 ; 01430750 (ISSN) Assari, N ; Assareh, E ; Alirahmi, S. M ; Hosseini, S. H ; Nedaei, M ; Rahimof, Y ; Fathi, A ; Behrang, M ; Jafarinejad, T ; Sharif University of Technology
    Taylor and Francis Ltd  2022
    Abstract
    The present study investigated a counter-flow cooling tower performance by integrating the Artificial Neural Networks and Intelligent Optimisation Algorithms (ANN-IOAs). For this purpose, two scenarios were evaluated. In the first scenario, inlet air wet-bulb temperature (T aw), inlet air dry bulb temperature (T ad), water to the air mass flow rate ratio (mw /ma), and rotor speed (υ) were the input parameters for the ANNs, while the output temperature (T wo) was the ANNs output. In the second scenario, the same input parameters applied for the first scenario were used as input variables and the tower efficiency (ε) was considered as an output parameter. The well-known IOAs methods, namely,... 

    Distribution system reliability enhancement using optimal capacitor placement

    , Article IET Generation, Transmission and Distribution ; Volume 2, Issue 5 , 2008 , Pages 621-631 ; 17518687 (ISSN) Etemadi, A. H ; Fotuhi Firuzabad, M ; Sharif University of Technology
    2008
    Abstract
    Failure statistics of most utilities indicate that distribution systems make the greatest individual contribution to the unavailability of supply to customers. Optimal capacitor placement in distribution systems has a number of advantages such as reducing losses, improving voltage profile, improving power factor and so on. The conventional objective function of the optimal capacitor placement consists of the total cost of losses and investments. Since capacitors supply reactive loads locally, they improve the load-carrying capability of the lines and therefore play the same role as redundant lines. Thus, optimal capacitor placement can also improve the reliability indices of a distribution...