Nezam Mahdavi-Amiri
Sharif University of Technology, Mathematical Sciences, Faculty Member
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The rapid growth of information and communication technologies prompted the need for developing the strategic implementation framework of IT/ICT programs in universities. Here, we propose a strategic framework for the development of the... more
The rapid growth of information and communication technologies prompted the need for developing the strategic implementation framework of IT/ICT programs in universities. Here, we propose a strategic framework for the development of the IT/ICT programs in the universities of the province of Mazandaran in Iran. We use the SWOT analysis to assist the formulation of the strategy, where the Analytic Hierarchy Process (AHP) is applied to weigh the SWOT factors and the fuzzy TOPSIS is used to evaluate the strategic plans. Based on Iran and Mazandaran Digital Indices (DI) and considering the SWOT matrix, four strategies are identified. Finally, an analytical concept, namely the strategy shooting, is considered to show the role of SWOT factors and strategic plans on the performance of the system.
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[bold We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path... more
[bold We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α‐cuts by proposing a ...
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원문정보. ...
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Abstract Here, a capacitated location-multi-allocation-routing problem with intelligent stochastic travel times is considered. In our study, the concept of intelligent stochastic travel times incurs two issues: (1) consideration of some... more
Abstract Here, a capacitated location-multi-allocation-routing problem with intelligent stochastic travel times is considered. In our study, the concept of intelligent stochastic travel times incurs two issues: (1) consideration of some random factors in computing the travel times and (2) impact of the traveling population on these random factors simultaneously. Here, a deterministic factor of road length and two random factors of the time spent in traffic and the number of accidents are considered. It is assumed that the time spent in traffic is distributed based on an exponential distribution function and the other factor is distributed based on a Poisson distribution function. Also, the capacities of server nodes and arcs for accepting the population are assumed to be limited. Using multiple linear regression, we formulate the problem as a mixed-integer nonlinear programming model. The objective is to find appropriate locations as server locations among the candidate locations, allocate the existing population in each demand node to server locations and determine the movement path of each member to reach its corresponding server with respect to the simultaneous change of the stochastic travel times so that the expected total transportation time is minimized. Also, to investigate the validation and behavior of the proposed probabilistic model, a network example is provided and computational results are analyzed.
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ABSTRACT
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Abstract A main component of a transportation network is travel time or distance. Due to stochastic events such as accidents and failures in roads, a deterministic estimation of the travel time between two cities or regions is impossible.... more
Abstract A main component of a transportation network is travel time or distance. Due to stochastic events such as accidents and failures in roads, a deterministic estimation of the travel time between two cities or regions is impossible. Also, on special occasions like holidays, with increase in the traveling population in the transportation network, probabilities of occurrence of these events increase. The increase in traveling population has a direct effect on the estimation of travel times and subsequently on the decision-making process. Therefore, provision of an appropriate model for the intelligent probabilistic travel times to distribute the population in a transportation network is a practical necessity. Here, we study a capacitated location-multi allocation-routing problem with intelligent probabilistic travel times. In our study, the concept of intelligent probabilistic travel times incurs two issues: (1) consideration of some random factors in computing the travel times and (2) impact of the traveling population on these random factors simultaneously. Here, we consider three random factors of the time spent in traffic, the number of accidents and the number of road failures. It is assumed that server nodes and arcs have limited capacities for accepting the population. After proposing a function for computing the intelligent probabilistic travel time, we first formulate the problem as a mixed-integer nonlinear programming model, and then suitably transform it into a mixed-integer linear programming one. Our aim is to determine appropriate server locations among the candidate locations, allocate the existing population in each demand node to server locations, and find the movement path of each member to reach its corresponding server with respect to the simultaneous change of the probabilistic travel times so that the expected total transportation time is minimized. For small problems, the model is efficiently solvable by the CPLEX software package. For large problems, two solution approaches, a heuristic algorithm incorporating genetic algorithm and local search, and an evolutionary simulated annealing algorithm, are proposed. Comparative numerical results demonstrate the effectiveness of the proposed probabilistic model and the proposed algorithms.
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Some efficient interior-point methods (IPMs) are based on using a self-concordant barrier function related to the feasibility set of the underlying problem.Here, we use IPMs for solving fractional programming problems involving second... more
Some efficient interior-point methods (IPMs) are based on using a self-concordant barrier function related to the feasibility set of the underlying problem.Here, we use IPMs for solving fractional programming problems involving second order cone constraints. We propose a logarithmic barrier function to show the self concordant property and present an algorithm to compute $\varepsilon-$solution of a fractional programming problem. Finally, we provide a numerical example to illustrate the approach.
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Here, we refine our recent proposed method for computing a positive definite solution to an overdetermined linear system of equations with multiple right-hand sides. This problem is important in several process control contexts including... more
Here, we refine our recent proposed method for computing a positive definite solution to an overdetermined linear system of equations with multiple right-hand sides. This problem is important in several process control contexts including quadratic models for optimal control. The coefficient and the right-hand side matrices are, respectively, named data and target matrices. In several existing approaches, the data matrix is unrealistically assumed to be error free. We have recently presented an algorithm for solving such a problem considering error in measured data and target matrices. We defined a new error in variables (EIV) error function considering error for the variables, the necessary and sufficient optimality conditions and outlined an algorithm to directly compute a solution minimizing the defined error. Moreover, the algorithm was specialized for a special case when the data and target matrices are rank deficient. Here, after giving a detailed review of the proposed algorit...
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Recently, public bicycle sharing system (PBSS) has become one of the most favorite urban transportation systems that can help governments to decrease environmental problems such as pollution and traffic. This paper studies a sharing... more
Recently, public bicycle sharing system (PBSS) has become one of the most favorite urban transportation systems that can help governments to decrease environmental problems such as pollution and traffic. This paper studies a sharing system that includes two types of stations. The first category contains stations that users can rent or return back bicycles and each bicycle can be rented by any new user who arrives to the stations. The second group is the stations which are near shopping centers, historical and other places that users and tourists can stop and visit them. These stations are used only for parking the rented bicycles for a period of time and after that, the users must ride their bicycles and turn them back to their destination stations. After discussing the network of the model under the closed Jackson network, the Mean Value Analysis (MVA) method will be used to calculate the mean queue of each station and analyzing the proposed model.
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A new mixed-integer nonlinear programming model is presented for the time-dependent vehicle routing problem with time windows and intelligent travel times. The aim is to minimize fixed and variable costs, with the assumption that the... more
A new mixed-integer nonlinear programming model is presented for the time-dependent vehicle routing problem with time windows and intelligent travel times. The aim is to minimize fixed and variable costs, with the assumption that the travel time between any two nodes depends on traffic conditions and is considered to be a function of vehicle departure time. Depending on working hours, the route between any two nodes has a unique traffic parameter. We consider each working day to be divided into several equal and large intervals, termed as a time interval of traffic. Here, allowing for long distances between some of the nodes, travel time may take more than one time interval of traffic, resulting in resetting the time interval of traffic at the start of each large interval. This repetition of time interval of traffics has been used in modeling and calculating travel time. A tabu search optimization algorithm is devised for solving large problems. Also, after linearization, a number o...
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Public Bicycle Sharing System (PBSS) is used as a way to reduce traffic and pollution in cities. Its performance is related to availability of bicycles for picking up and free docks to return them. Existence of different demand types... more
Public Bicycle Sharing System (PBSS) is used as a way to reduce traffic and pollution in cities. Its performance is related to availability of bicycles for picking up and free docks to return them. Existence of different demand types leads to the emergence of imbalanced stations. Here, we try to balance inventory of stations via defining maximal response rates for each type of rental request. If the maximal response rate for a destination is lower than 100 percent, a part of the proposed destination requests is rejected in the hope of balancing the inventory. The goal is to minimize the mean extra inventory and the mean rejected requests by providing proper amounts of the maximal response rates. An approximation method named as Mean Value Analysis (MVA) is used to develop a genetic algorithm for solving the problem. Different examples are worked through to examine the applicability of the proposed method. The results show that the proposed policy leads to a significant improvement a...
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We propose a new method for ordering bipolar fuzzy numbers. In this method, for comparison of bipolar LR fuzzy numbers, we use an extension of Kerre’s method being used in ordering of unipolar fuzzy numbers. We give a direct formula to... more
We propose a new method for ordering bipolar fuzzy numbers. In this method, for comparison of bipolar LR fuzzy numbers, we use an extension of Kerre’s method being used in ordering of unipolar fuzzy numbers. We give a direct formula to compare two bipolar triangular fuzzy numbers in O(1) operations, making the process useful for many optimization algorithms. Also, we present an application of bipolar fuzzy number in a real life problem.