Department of Systems and Productivity Management (1988 - Present)
Technology Management
, Bradford, England
industrial engineering
, Tarbiat Modares University,
Operations Research
, Shahid Beheshti University,
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Expert: Mrs Ryahei
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Reza Baradaran Kazemzadeh is a Professor at the Faculty of Industrial and System Engineering, Tarbiat Modares University. He received a BS in Operations Research and an MS in Industrial Engineering. He holds a Ph.D. in Technology Management from the University of Bradford. His research interests are quality and reliability engineering, and statistical modeling in Data Science. His publications have appeared in Quality and Reliability Engineering International, European Journal of Operational Research, Communications in Statistics, and International Journal of Advanced Manufacturing Technology.
Reliability importance measures are significant and effective tools for analyzing systems reliability, risk and safety. These measures are traditionally defined in fault tree context, and are widely used in eminent methods such as probabilistic safety and risk assessment. Although fault tree is a well-known and powerful tool in systems risk analysis, but it has remarkable weaknesses. The most important weakness of fault tree is its inability in considering dynamic dependencies between system components that is caused by its restriction in considering the effect of time of failure of the system components. Another significant weakness is that fault tree considers system components to be unrepairable, while most of the real world systems are
In this research, a new multi-objective-multi-criteria model is presented to determine physical asset management strategy for capital equipment. Initially, a multi-objective model is formulated to determine non-dominated strategies considering cost, reliability, and availability as objective functions. Secondly, the strategies will be ranked based on decision maker preferences and restrictions using a PROMETHEE-entropy module. Each strategy is a vector of procurement variables (dealer-manufacturer and contract type) and maintenance planning variables (PM action level, PM interval and the degree of upgrade action). The multi-objective model, which is a new nonlinear mixed integer optimisation model, is solved using a customised NSGA-II. Buy,
In this paper, we focus on solving the integrated energy and flexiramp procurement problem in the day-ahead market. The problem of energy and ramp procurement could be perfectly analyzed through Stackelberg concept because of its hierarchical nature of decision-making process. Such a circumstance was modeled via a bi-level programming in which suppliers acted as leaders and the Independent System Operator (ISO) was the follower. The ISO intended to minimize energy and spinning reserve procurement cost, and the suppliers aimed to maximize their profit. To solve the proposed model, a fuzzy max-min approach was applied to maximizing the utilities of players. The objectives and dynamic offers of suppliers, determined with regard to the market c
In recent years, the share of renewable energy sources (RES) in electricity generation portfolio has been growing, primarily supported by local and international energy policies to reduce the carbon footprint of the electricity sector. However, the large-scale integration of variable and uncertain RES has adverse effects on the power system operations. Therefore, the power system operators should apply advanced scheduling models and enhance the flexibility of the systems to compensate for the variability and uncertainty of RES. To deal with these challenges and covering the ramp scarcities and severe contingencies, not only more operational reserves are required but also the urgent actions is needed to develop the efficient markets, contrac
Considering the players' bargaining power, designing a bi-level programming model is suitable to reflect the hierarchical nature of the decision-making process. In this paper, typical negotiation components perfectly match with the mathematical model and its solution procedure. For this purpose, a mathematical negotiation mechanism is designed to minimize the negotiators' costs in a distributed procurement problem at two echelons of an automotive supply chain. The buyer's costs are procurement cost and shortage penalty in a one-period contract. On the other hand, the suppliers intend to solve a multi-period, multi-product production planning to minimize their costs. Such a mechanism provides an alignment among suppliers' production planning
This paper presents a cooperative bidding model for energy, reserve, and flexiramp providing by a group of suppliers. Procurement problems in electricity markets have been analysed through Stackelberg concept and modelled via bi-level programming. However, previous bi-level models have captured the game only in the context of the day-ahead or real-time market. In this paper, a stochastic two-stage multi-objective bi-level model for procurement problem in the dayahead and balancing markets is proposed; in which the Stackelberg game is simultaneously considered in these markets. In each stage of the proposed model, multiple decision-makers (DMs) including conventional and wind generating units as well as a demand response (DR) aggregator act
In this paper, a novel trilevel programming model for energy, reserve, and flexiramp procurement problem in the day‐ahead market is proposed. The conventional and wind generating units are the strategic decision makers (DMs) in the upper level, which maximize their profit. In the middle level, a large industry and a demand response (DR) aggregator maximize their profit according to the market's status. Finally, the independent system operator (ISO) minimizes its total cost in the lower level. To solve the proposed trilevel model, a fuzzy max‐min technique for multilevel programming problem (MLPP) is proposed. The proposed model is applied to the 24‐bus IEEE test system to demonstrate the benefits of implementing the proposed model in
In this research, a new multi-objective optimisation model is developed from equipment user's point of view who is seeking to select from among the buy/lease/upgrade decisions and maintenance schedule options when the equipment performance criteria and total cost are in consideration. The proposed model determines the possible non-dominated physical asset management (AM) strategies by interconnecting procurement parameters, maintenance scheduling variables, and equipment's working historical data. Total operational cost, the equipment reliability and unavailability are the objectives of the model which is solved using NSGA-II. Each of the achieved strategies consists of a procurement method (buy/lease/upgrade) and a maintenance strategy (PM
Importance measures are integral parts of risk assessment for risk‐informed decision making. Because the parameters of a risk model, such as the component failure rates, are functions of time and a perturbation (change) in their values can occur during the mission time, time dependence must be considered in the evaluation of the importance measures. In this paper, it is shown that the change in system performance at time t, and consequently the importance of the parameters at time t, depends on the parameters perturbation time and their value functions during the system mission time. We consider a nonhomogeneous continuous time Markov model of a series‐parallel system to propose the mathematical proofs and simulations, while the ideas
Determining a unique goal in Goal Programming (GP) method for each objective function due to restriction of information is difficult and inefficient. To overcome this problem, a type of goal programing methods called multiple-choice goal programing has been developed, in which multiple levels introduced for each objective. In this paper, the goals are considered as alternatives, which decision-makers express their agreement or disagreement with them through interval-valued intuitive fuzzy numbers (IVIFNs). In the complex multi-attribute large-group decision making problems where attribute values are interval-valued intuitionistic fuzzy numbers, the number of decision attributes is often large and their correlation degrees are high, which in
Importance measures (IMs) are used for risk-informed decision making in system operations, safety, and maintenance. Traditionally, they are computed within fault tree (FT) analysis. Although FT analysis is a powerful tool to study the reliability and structural characteristics of systems, Bayesian networks (BNs) have shown explicit advantages in modeling and analytical capabilities. In this paper, the traditional definitions of IMs are extended to BNs in order to have more capability in terms of system risk modeling and analysis. Implementation results on a case study illustrate the capability of finding the most important components in a system.
An chart with variable sampling interval (VSI) has been shown superior to the traditional chart with fixed ratio sampling (FRS). A constraint approach is not an efficient method for Economic Statistical Design (ESD) of VSI control charts because statistical properties are of the same importance as economic properties and should be optimized simultaneously. Then, a Multi-Objective Genetic Algorithm for ESD is proposed for identifying the Pareto optimal solutions of control chart design. The proposed method allows the practitioner to be provided with a set of optimal designs rather than a single solution, and they can select the locally optimal solution according to the process information. Through an illustrative example, the advantages of t
Ebrahim Mazrae Farahani, Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran Reza Baradaran Kazemzadeh, Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran Amir Albadvi, Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran Babak Teimourpour, Industrial Engineering Department, Tarbiat Modares University, Tehran, Iran
In this paper, we focus on solving the integrated energy and flexiramp procurement problem in the day-ahead market. The problem of energy and ramp procurement could be perfectly analyzed through Stackelberg concept, because of its hierarchical nature of the decision-making process. Such a circumstance is modeled via a bi-level programming, in which suppliers act as leaders and the ISO appear as the follower. The ISO intends to minimize the energy and spinning reserve procurement cost, and the suppliers aim to maximize their profit. To solve the proposed model, a fuzzy max-min approach is applied to maximize the players’ utilities. The objectives and suppliers’ dynamic offers, determined regarding the market clearing prices, are reformul
Importance measures are well-known and important tools which are widely used in risk-informed decision making. Their outstanding traditional definitions have made them useful in many applications related to risk and reliability aspects of different systems. These perfect traditional definitions help researchers to find the most important components in a system, and consequently, to detect and obviate weaknesses in system structure and operations. Generally, these measures are based on fault tree technique. Although fault tree is a powerful tool to study risk, reliability, and structural characteristics of systems, Bayesian networks have indicated explicit advantages over it in modeling and analysis abilities. Classical fault tree is not sui
Statistical process control provides useful tools to improve the quality of multistage machining processes, specifically in continuous manufacturing lines, where product characteristics are measured at the final station. In order to reduce process errors, variation source identification has been widely applied in machining processes. Although statistical estimation and pattern matching-based methods have been utilized to monitor and diagnose machining processes, most of these methods focus on stage-by-stage inspection using complex models and patterns. However, because of the existence of high rate alarms and the complexity of the machining processes, a surrogate modelling is needed to solve quality control problems. Here, a novel approach
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