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    Robust simulation optimization using φ-divergence

    , Article International Journal of Industrial Engineering Computations ; Volume 7, Issue 4 , 2016 , Pages 517-534 ; 19232926 (ISSN) Moghaddam, S ; 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... 

    A new model for robust facility layout problem [electronic resource]

    , Article Information Sciences, Elsevier ; Volume 278, 10 September 2014, Pages 498–509 Neghabi, H. (Hossein) ; Eshghi, Kourosh ; Salmani, Mohammad Hassan ; Sharif University of Technology
    Abstract
    The Facility Layout Problem (FLP) is the problem of locating each department in a long plant floor without any overlap between departments in order to minimize the material handling cost. The main purpose of this study is to show the effectiveness of a robust approach to solve FLP. In this study, it is assumed that the departments’ length and width are not predetermined. For modeling this kind of uncertainty, the size of each department is considered as a bounded variable and two new parameters are also introduced to implement a robust approach. Moreover, a new adaptive algorithm is designed to determine the robust layout with respect to the decision makers’ requirements. Furthermore, the... 

    A robust multi-objective production planning

    , Article International Journal of Industrial Engineering Computations ; Volume 1, Issue 1 , 2010 , Pages 73-78 ; 19232926 (ISSN) Gharakhani, M ; Taghipour, T ; Jalali Farahani, K ; Sharif University of Technology
    2010
    Abstract
    When a production facility is designed, there are various parameters affecting the number machines such as production capacity and reliability. It is often a tedious task to optimize different objectives, simultaneously. The other issue is the uncertainty in many design parameters which makes it difficult to reach a desirable solution. In this paper, we present a new mathematical model with two objectives. The primary objective function is considered to be the production capacity and the secondary objective function is total reliability. The proposed model is formulated on different units of production which are connected together in serial form and for each unit, we may have various... 

    Reconfiguring a set of coverage-providing facilities under travel time uncertainty

    , Article Socio-Economic Planning Sciences ; 2017 ; 00380121 (ISSN) Berman, O ; Hajizadeh, I ; Krass, D ; Rahimi Vahed, A ; Sharif University of Technology
    Elsevier Ltd  2017
    Abstract
    We study networks of facilities that must provide coverage under conditions of uncertainty with respect to travel times and customer demand. We model this uncertainty through a set of scenarios. Since opening new facilities and/or closing existing ones is often quite expensive, we focus on optimal re-configuration of the network, that is finding a facility set that achieves desired thresholds with respect to expected and minimal coverage, while retaining as many of the existing facilities as possible. We illustrate our model with an example of Toronto Fire Service. We demonstrate that relocating just a few facilities can have the same effect as opening a similar number of new ones. We... 

    Viable medical waste chain network design by considering risk and robustness

    , Article Environmental Science and Pollution Research ; 2021 ; 09441344 (ISSN) Lotfi, R ; Kargar, B ; Gharehbaghi, A ; Weber, G. W ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    Medical waste management (MWM) is an important and necessary problem in the COVID-19 situation for treatment staff. When the number of infectious patients grows up, the amount of MWMs increases day by day. We present medical waste chain network design (MWCND) that contains health center (HC), waste segregation (WS), waste purchase contractor (WPC), and landfill. We propose to locate WS to decrease waste and recover them and send them to the WPC. Recovering medical waste like metal and plastic can help the environment and return to the production cycle. Therefore, we proposed a novel viable MWCND by a novel two-stage robust stochastic programming that considers resiliency (flexibility and... 

    A data-driven robust optimization for multi-objective renewable energy location by considering risk

    , Article Environment, Development and Sustainability ; 2022 ; 1387585X (ISSN) Lotfi, R ; Kargar, B ; Gharehbaghi, A ; Afshar, M ; Rajabi, M. S ; Mardani, N ; Sharif University of Technology
    Springer Science and Business Media B.V  2022
    Abstract
    Using Renewable Energy (RE) is growing day by day. We need to locate RE in the best place to maximize energy production and supplier profit. As a result, we propose a novel method for RE location (REL). This model suggests a Data-Driven Robust Optimization (DDRO) for multi-objective REL by considering Risk (DDROMORELR). We consider risk by adding min function in energy and profit objectives (government and supplier objectives). A DDRO approach is added to the model to tackle uncertainty and be close to the real world. We utilize an improved Augmented ε-constraint (AUGEPS2) to solve objectives and produce a Pareto front. We compare problems with DDRO and without considering DDRO, and the... 

    A robust optimization method for co-planning of transmission systems and merchant distributed energy resources

    , Article International Journal of Electrical Power and Energy Systems ; Volume 118 , 2020 Ranjbar, H ; Hosseini, S. H ; Zareipour, H ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    This paper presents a new robust co-planning model for transmission investment and merchant distributed energy resources (DERs). The problem is formulated from the viewpoint of power system regulators and planners such that they will build the new transmission facilities and identify optimal locations to direct merchant DERs. The proposed model is a tri-level min-max-min optimization problem where the upper, middle, and lower levels are investment decision of transmission lines and DERs, worst case realization of uncertain parameters, and the best actions in order to minimize the operation costs. The model considers the uncertainties associated with future peak load and generation capacity,... 

    Economically optimal uncertainty set characterization for power system operational flexibility

    , Article IEEE Transactions on Industrial Informatics ; Volume 15, Issue 10 , 2019 , Pages 5456-5465 ; 15513203 (ISSN) Pourahmadi, F ; Hosseini, S. H ; Fotuhi Firuzabad, M ; Sharif University of Technology
    IEEE Computer Society  2019
    Abstract
    Assessing the operational flexibility of the grid with high penetration of renewable resources remains an issue of critical importance. Operational flexibility insufficiency may bring about two major problems: 1) there may exist no feasible solution for operation under uncertain conditions due to insufficient available flexibility capacity; 2) even if the solution feasibility criterion is ensured, dispatch limitations of the flexible resources may force the system operating point to deviate from the optimal economic point with increased redispatch. In this paper, an optimal uncertainty set at the unit commitment time scale is proposed and characterized as a reliable operational metric. A... 

    Forecasting and Optimization a Portfolio Using Robust Optimization

    , M.Sc. Thesis Sharif University of Technology Badri, Hamid Reza (Author) ; Modarres Yazdi, Mohammad (Supervisor)
    Abstract
    In this Thesis, a multi period portfolio optimization consisting stocks, gold and risk free asset is considered, in which periodical reinvestment and withdrawing is possible. Maximizing the net present value of investor’s cash flow is the objective. Due to the existence of uncertain parameters, two robust counterpart models are developed. In the first model, a conservative robust model is presented to generate feasible solution in all cases. In the second one, the conservative degree of investor is adjustable to control the risk of the model by investor appropriately. For evaluating the proposed models, the data of 5 well known stocks of Tehran market and gold prices are gathered. By using... 

    Portfolio Management with Robust Optimization Approaches

    , M.Sc. Thesis Sharif University of Technology Hosseini, Maryam (Author) ; Kiyanfar, Farhad (Supervisor)
    Abstract
    Todays, one of the most important problems is optimal allocation of capital to different investment options that many researchers studied about this problem and presented a lot of solutions. In this thesis, we solve portfolio optimization problem to maximize the return of investment. The options of investment are different kinds of stocks, gold coins and we consider bank deposits as a risk free asset. We apply the problem in multi period and we can buy and sell stocks and gold coins in each period. To improve the efficiency of the proposed models, we use real data and consider transaction fees. The return of some options is uncertain, so we use robust optimization approach. At first we apply... 

    A Multi-Objective Robust Optimization Model for Logistics Planning in the Earthquake Response Phase [electronic resource]

    , Article Transportation Research Part E: Logistics and Transportation Review, Elsevier ; Volume 49, Issue 1, January 2013, , Pages 217–249 Najafi, M. (Mehdi) ; Eshghi, Kourosh ; Dullaert, Wout ; Sharif University of Technology
    Abstract
    Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and multi-period stochastic model to manage the logistics of both commodities and injured people in the earthquake response. Also, a robust approach is developed and used to make sure that the distribution plan performs well under the various situations that can follow an earthquake. Afterwards, it proposes a solution methodology according to hierarchical objective functions and uses it to illustrate the... 

    A bi-objective robust optimization model for a blood collection and testing problem: an accelerated stochastic benders decomposition

    , Article Annals of Operations Research ; 2018 ; 02545330 (ISSN) Yousefi Nejad Attari, M ; Pasandideh, S. H. R ; Aghaie, A ; Akhavan Niaki, S. T ; Sharif University of Technology
    Abstract
    Blood transfusion services are vital components of healthcare systems all over the world. In this paper, a generalized network optimization model is developed for a complex blood supply chain in accordance with Iranian blood transfusion organization (IBTO) structure. This structure consist of four types facilities. Blood collection centers, blood collection and processing centers, mobile teams and blood transfusion center have various duties in IBTO structure. The major contribution is to develop a novel hybrid approach based on stochastic programming, ε-constraint and robust optimization (HSERO) to simultaneously model two types of uncertainties by including stochastic scenarios for total... 

    Dynamic uncertainty set characterization for bulk power grid flexibility assessment

    , Article IEEE Systems Journal ; Volume 14, Issue 1 , 2020 , Pages 718-728 Pourahmadi, F ; Heidarabadi, H ; Hosseini, S. H ; Dehghanian, P ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    The increasing variability of renewables and volatile chronological net-load in power grids engenders significant risks of an uncertain sufficiency of flexible capacity. Although considerable advances in power grid flexibility assessment have been made, modeling the effect of temporal correlations associated with wind generations on the system flexibility provision capability has remained a challenge. This paper proposes a novel UC-time-scale security-constrained affinely robust formulation for wind-originated uncertainty sets in order to evaluate the system flexibility capacity over time. An efficient model based on duality theorem and affine policy is proposed to assess a secure region in... 

    Robust Optimization of Portfolio with Stock Options

    , M.Sc. Thesis Sharif University of Technology Hassanzadeh Mofrad, Maryam (Author) ; Modarres Yazdi, Mohammad (Supervisor)
    Abstract
    In this thesis, we apply robust optimization to analyze the uncertainty of model parameters of a portfolio optimization which contains stock options. We also develop two robust counterpart models for single period and multiperiod problems. By assuming that the probability distribution of parameters is not known, their uncertainty is considered to lie within known linear intervals. Due to the existence of nonlinear relations (piecewise linear) between uncertain data (stock and option price), we present an over-conservative robust model to make the solution feasible for all parameters. However in the second model by adopting a different approach we develop a robust counterpart model with... 

    Robust Optimization of Inventory in Supply Chain Management

    , M.Sc. Thesis Sharif University of Technology AminGhafouri, Reza (Author) ; Modarres Yazdi, Mohammad (Supervisor)
    Abstract
    In this research, the determination of inventory management policy is investigated in two-level supply chains. Two scenarios are considered to analyze this problem. In the first one, all parameters are assumed to be deterministic while in the other one, the retailer’s demand is assumed to be uncertain. We extend the previous studies by considering the real world conditions; and introduce a model in which the costs of lost-sale and backorder are considered simultaneously. A genetic algorithm is developed to solve the proposed model. To evaluate the efficiency of the model, the results are compared over five different examples when only complete backorder is considered. In case of uncertain... 

    Developing a Joint Location-Inventory-Transportation Model under Uncertainty

    , M.Sc. Thesis Sharif University of Technology Poursaeidi, Mohammad Hossein (Author) ; Mahlooji, Hashem (Supervisor)
    Abstract
    In this research, an integrated location-inventory-transportation problem with uncertainty in the parameters is analyzed using Robust Optimization techniques. Unknown demand distribution is the underlying assumption, which relates better to the reality. The model’s main purpose is to determine the number and locations of the Distribution Centers (DC) that connect the supplier to the retailers, and then to assign retailers to them. The problem’s mathematical model is developed on the basis of Robust Optimization techniques and the solution space is explored by Tabu Search. The results show that the Tabu Search method achieves optimality in small-scale cases, while providing desirable... 

    A Robustification Approach in Unconstrained Quadratic Optimization

    , M.Sc. Thesis Sharif University of Technology Kavand, Razieh (Author) ; Peyghami, Mohammad Reza (Supervisor) ; Fotouhi Firouzabad, Morteza (Supervisor)
    Abstract
    In this thesis, unconstrained convex quadratic optimization problems subject to parameter perturbations are considered. A robustification approach is proposed and analyzed which reduces the sensitivity of the optimal function value with respect to the parameter. Since reducing the sensitivity and maintaining a small objective value are competing goals, strategies for balancing these two objectives are discussed. Numerical examples illustrate the approach  

    Solving the P-Center Problem under Uncertainty

    , M.Sc. Thesis Sharif University of Technology Taghavi, Majid (Author) ; Shavandi, Hassan (Supervisor)
    Abstract
    Facility location decisions play a prominent role in strategic planning of many firms, companies and governmental organizations. Since in many real-world facility location problems, the data are subject to uncertainty, in this thesis, we consider the P-center problem under uncertainty of demand nodes. Using Bertsimas and Sim approach, we modeled the problem as a linear optimization model. Furthermore, we develop a tabu search algorithm to solve the problem. Finally we designed some experiments to adjust the parameters of tabu search algorithm. We presented the numerical result accordingly  

    Robust Optimization of Integrated Model of Facility Location and Scheduling

    , M.Sc. Thesis Sharif University of Technology Imanpoor Yourdshahy, Mona (Author) ; Modarres Yazdi, Mohammad (Supervisor)
    Abstract
    In facility location problem with uncertain data, some model parameters such as demand or transportation time are not known in advance and in many cases, no historical information exists to derive their probability distribution functions. In this situation, robust optimization is a prevalent approach. In this study, to apply robust optimization in our model, first we review its concepts and methods. Then, a mathematical model for a new facility location problem, as well as its robust counterpart is developed. Furthermore, we also develop a model for simultaneous decision making regarding facility location problem and sequencing. In this model, it is also assumed the process times are... 

    Integrated Location-Allocation and Scheduling Model

    , M.Sc. Thesis Sharif University of Technology Karamyar, Fatemeh (Author) ; Modarres Yazdi, Mohammad (Supervisor)
    Abstract
    Location-allocation problem is known as one of the classical problems in industrial engineering. The goals of these problems are finding optimal location of facilities and assigning these facilities to service demands from a given set of point. Location-allocation decisions are widespread through all organization in the world concerning private and public businesses. Therefore, in this study, a practical mathematical model is formulated and solved.In this paper we present a new approach for a budgeted constraint capacitated location-allocation problem integrated with cellular layout approach containing cell formation and group scheduling. Main decisions are composed of formation of...