CLUSTERING OF DAIRY PRODUCTS CONSUMERS BASED ON BRAND CONSIDERATION: A CASE STUDY OF IRAN

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       Article 1, Volume 3, Issue 1, Summer 2016, Page 1-9 

ABBAS KERAMATI1*, MEHDI KESHAVARZ2, & ABOLGHASEM YOUSEFI-BABADI3

1* Department of Industrial Engineering, Faculty of Engineering, University of Tehran, keramati@ut.ac.ir

2 Department of Industrial Engineering, Faculty of Engineering, University of Tehran, mehdikeshavarz@ut.ac.ir

3 Department of Industrial Engineering, Faculty of Engineering, University of Tehran, a.yousefibabadi@ut.ac.ir

Abstract

An increasing demand of dairy product worldwide gives a good opportunity for dairy industries; and under the blows of globalization and pierce of technology to various corners, the competition amongst dairy industries are getting tougher and harder day-by-day. Dairy companies in order to sustain their competitiveness should segment and analyze customer attitudes and behaviors. This paper segments the customers in the Urmia city of Iran based on their attention and important degree of dairy products brand. The various customer characteristics such as age, income, gender and ethnicity are used for segmenting and clustering. Several dairy products such as cheese, butter, milk, chocolate milk, yogurt, Doogh and ice cream are utilized in this paper and for each of them a separate clustering has been performed. In this paper, the hierarchical approach is used to find the initial number of clustering, then by utilizing the K-mean algorithm the best cluster is calculated.

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WASTE COLLECTION VEHICLE ROUTING PROBLEM CONSIDERING SIMILARITY PATTERN OF TRASH CAN AND GARBAGE UNLOADING

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       Article 2, Volume 1, Issue 7,  July 2014, Page 204-219 

SOMAYEH FOOLADI, HAMED FAZLOLLAHTABAR

Abstract

Rapid urbanization poses a serious environmental threat of solid waste management (SWM) and reverse supply chain. In this paper, a mathematical model is proposed in order to reduce the cost of waste collection and transporting for recycling process. First a mixed-integer nonlinear programming model is provided including a waste collection routing problem and the following processes after garbage unloading, so that, there is a balance between the distance between trashcans, and the similarity of the trashcans in terms of the types of waste which is in the trashcans, in order to select the optimal route for each garbage transport vehicles. For this purpose, a similarity pattern is designed. By following the similarity pattern for route selection, recovery rate of waste will be increased being shown in the model. Then, we solved the model by using LINGO 0.9 software and analyze the output results of solved model.

PORTFOLIO SELECTION USING DEA AND GENETIC ALGORITHM

MAJID SHARIAT PANAHI
Faculty member of Management and Accounting department of “Alameh Tabatabaee” University

 

MOHAMAD TAGHI TAGHAVI FARD
Faculty member of Industrial Engineering department of “Alameh Tabatabaee” University

 

MEHDI YARBOD
M.A. of “Alameh Tabatabaee” University

Abstract

This research is aimed at determining and introducing a suitable model for investment decision in security market. To this end, effective measures are extracted for portfolio selection according to research literature. Therefore, the numbers of basic variables are determined with regard to the fact that there is correlation between financial ratios. In the following data envelopment analysis is used to rate understudy population including fundamental metals, metallic minerals, chemicals, medicine, properties and real states and cement industries. For the reason, 3-year average of real data in the period of 2006-2008 is used. After rating company of each mentioned industry, those companies having efficiency above 0.9 are located in the selected portfolio. 3-year output of portfolio of 2006-2008 is calculated to optimize selected portfolio and then it is compared with portfolio of unselected companies. Finally, genetic algorithm is used to evaluate optimization of selected portfolio according to Terner scale using optimization of the mentioned portfolio. Results show that the portfolio selected from the companies having higher efficiency leads to better output compared with unselected companies. This model is fitted to designate investors’ resource and gain more output.

PRIORITIZATION AND IDENTIFICATION OF EVENTFUL PIECES FOR TRAVELERS AND TOURISTS OF QESHM-LOFT ROUTE BY USING GIS AND SAW-AHP TECHNIQUE

MOHAMAD KAZEMI
Ph.D. Watershed student, Hormozgan University, Iran

 

AHMAD NOHEGAR
Professor of Environmental Science, Tehran University, Tehran, Iran

 

MIRDAD MIRDADI
Master degree of remote sensing and GIS, Campus of Qeshm, Iran

 

SHIMA MORTAZAVI
Master degree of Environmental Science, Payam Noor University, Tehran, Iran

Abstract

One of the basic steps in the process of road safety management is defining the causes of accidents depending on the geometry and environmental conditions. The purpose of this study is to provide a new method for consideration of an accident due to environmental and geometrical conditions of the route and preparation of these factors in geographical information system, which takes accidents into consideration according to the interaction of their components. Multi-criterion decision-making method gives advantages which allow the causes of accidents to be ranked and prioritized appropriately in terms of seismic event. In this study, in order to provide criteria and its sub criteria, GIS and the formed database in this space was used and then this information was weighted in the analytical hierarchy technique so that the main causes of accidents in Qeshm loft axis be recognized. The results showed that the criteria of the distance from the intersection, the radius of the arc, and road width respectively with weights of 0.279, 0.255, and 0.140 are the most important accident factors according to the geometric conditions and environment axis.