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Showing 5 results for Karimi

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Volume 20, Issue 1 (IJIEPR 2009)
Abstract

  The problem of lot sizing, sequencing and scheduling multiple products in flow line production systems has been studied by several authors. Almost all of the researches in this area assumed that setup times and costs are sequence –independent even though sequence dependent setups are common in practice. In this paper we present a new mixed integer non linear program (MINLP) and a heuristic method to solve the problem in sequence dependent case. Furthermore, a genetic algorithm has been developed which applies this constructive heuristic to generate initial population. These two proposed solution methods are compared on randomly generated problems. Computational results show a clear superiority of our proposed GA for majority of the test problems.


Seyed Omid Hasanpour Jesri, Abbas Ahmadi, Behrooz Karimi, Mohsen Akbarpour ,
Volume 23, Issue 4 (IJIEPR 2012)
Abstract

One of the most important issues in urban planning is developing sustainable public transportation. The basic condition for this purpose is analyzing current condition especially based on data. Data mining is a set of new techniques that are beyond statistical data analyzing. Clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. The result of this research shows relations and similarities in different segments that its usage is from strategic to tactical and operational areas. The approach in transportation is completely novel in the part of trip patterns and a novel process is proposed that can be implemented in highway analysis. Also this method can be applied in traffic and vehicle treats that need automatic number plate recognition (ANPR) for data gathering. A real case study has been studied here by developed process.
Hadi Karimi, Abbas Seifi,
Volume 23, Issue 4 (IJIEPR 2012)
Abstract

The analytic center cutting plane method (ACCPM) is one of successful methods to solve nondifferentiable optimization problems. In this paper ACCPM is used for the first time in the vehicle routing problem with time windows (VRPTW) to accelerate lagrangian relaxation procedure for the problem. At first the basic cutting plane algorithm and its relationship with column generation method is clarified then the new method based on ACCPM is proposed as a stabilization technique of column generation (lagrangian relaxation). Both approaches are tested on a benchmark instance to demonstrate the advantages of proposed method in terms of computational time and lower bounds quality.
Masoud Yaghini, Faeze Ghofrani, Mohammad Karimi, Majedeh Esmi-Zadeh,
Volume 27, Issue 4 (IJIEPR 2016)
Abstract

The locomotive assignment and the freight train scheduling are important problems in railway transportation. Freight cars are coupled to form a freight rake. The freight rake becomes a train when a locomotive is coupled to it. The locomotive assignment problem assigns locomotives to a set of freight rakes in a way that, with minimum locomotive deadheading time, rake coupling delay and locomotive coupling delay all freight rakes are hauled to their destinations. Scheduling freight trains consists of sequencing and ordering freight trains during the non-usage time between passenger trains but with no interference and with minimum delay times. Solving these two problems simultaneously is of high importance and can be highly effective in decreasing costs for rail transportation. In this paper, we aim to minimize the operational costs for the locomotive assignment and the freight train scheduling by solving these two problems concurrently. To meet this objective, an efficient and effective algorithm based on the ant colony system is proposed. To evaluate the performance of the proposed solution method, twenty-five test problems, which are based on the conditions of Iran Railways, are solved and the computational results are reported.


Zahra Karimi Ezmareh, Gholam Hossein Yari,
Volume 30, Issue 2 (IJIEPR 2019)
Abstract

In this paper, a new distribution that is highly applicable in the fields of reliability and economics is introduced. Also the parameters of this distribution is estimated using two methods of Maximum Likelihood and Bayes with two prior distributions Weibull and Uniform, and these two methods are compared using Monte-Carlo simulation. Finally, this new model is fit on the real data(with the failure time of 84 aircraft) and some of comparative criteria are calculated to confirm superiority of the proposed model compared to other models.

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