mohammad ali vahdatzad

Hubs are facilities that can decrease the cost of many-to-many distribution systems by acting as an interconnector between the demand and supply nodes. This type of facility can reduce the number of direct links needed in a logistics network. Hub location problems (HLP) have been discussed by many authors for more than four decades, and different approaches have been developed for modeling and solving this problem. We propose a fuzzy type I and II programming approach for a new model presented in the literature, i.e., the single allocation ordered median problem. The level of flow among the nodes will be considered as a fuzzy parameter. In the fuzzy type I approach, a linear programming problem with fuzzy parameters is used, while for the fuzzy type II approach, the rules of interval arithmetic are developed to simplify the problem to the fuzzy type I case. Finally, we apply our method on Kalleh Dairy Co. data of transportation as a case study and compare crisp and fuzzy situations. We show that the results of the fuzzy approach could be 2% better than the crisp approach and also discuss the pros and cons of fuzzy type I and type II approaches.

The purpose of this article is to model and solve an integrated location, routing and inventory problem (LRIP) in cash-in-transit (CIT) sector. In real operation of cash transportation, to decrease total cost and to reduce risk of robbery of such high-value commodity. There must be substantial variation, making problem difficult to formulate. In this paper, to better fit real life applications and to make the problem more practical, a bi-objective multiple periods, capacitated facilities with time windows under uncertain demand (BO-PCLRIP-TW-FD) in the LRIP, motivated by the replenishment of automated teller machines, is proposed. Then, using the chance constrained fuzzy programming to deal with uncertain parameters, the comprehensive model is formulated as a crisp mixed-integer linear programming. At last, to validate the mathematical formulation and to solve the problem, the latest version of ε-constraint method (i.e., AUGMECON2) is used. The proposed solution approach is tested on a realistic instance in CIT sector. Numerical results demonstrate the suitability of the model and the formulation. The ability of the model to be useful references for security carriers in real-world cases.

The purpose of this research is to identify and prioritize customers' expectations about the quality of service of AGENCIES.. This research was carried out based on the Servqual model,and in terms of purpose, it is applicable, And in terms of approach, it's developmental... In this research, customers of travel agencies were considered as the statistical population that the number of the population were more than 100 thousand... According to Krejcie & Morgan tables, for a population of more than 100,000 people, at least 384 individuals are required, and the sampling process was carried out through cluster sampling with equal volume.. In this research, three questionnaires were used to identify, screen the customers' expectations,by descriptive and statistical (Kolmogorov-Smirnov test and confirmatory factor analysis) methods, And EXCEL-SPSS-LISREL software was used to perform the necessary tests.. In addition, in the phase of achieving weight and priority of cases, a "ahp" method was used, And for calculating it, the "EXPERT CHOICE" software was used.. The results of the research led to the identification of 14 service expectations in 5 general dimensions, And their relative weight and prioritization were determined.

Nowadays, universities and higher education institutions have a critical role in developing countries and it is essential that their performance is evaluated with appropriate methods and criteria. Among the various functions of universities, research and scientific production is the most important one. The evaluation of scientific outputs is an attempt to assess the performance of universities. The use of scientometric indicators is a way to assess the scientific outputs of universities. In this context, a number of indicators have been defined to assess the quantity and quality of scientific outputs of researchers that can be extended to assess the institutions. Through a descriptive survey, in this paper, 285,526 scientific outputs of 76 universities affiliated to Ministry of Science, Research and Technology were selected and evaluated. The data of each university were analyzed individually using the indicators such as the number of scientific outputs, number of citations, h-index, m-parameter and g-index and the institutions were ranked. The results show that Tehran University in number of scientific outputs and number of citations, Sharif University of Technology in h-index and g-index, and Babol Noshirvani University of Technology in m-parameter are as the top Iranian Universities in the surveyed universities. The overall ranking shows that Tarbiat Modares University and Sharif University of Technology are top. Finally, we compare and discuss our ranking results with ISC and URAP ranking systems. The results show that the ranking of universities in this research in terms of the number of scientific outputs, the number of citations, h-index and g-index has a high correlation with that of ISC and URAP systems.

Universities and higher education institutions, as knowledge-based organizations, have a critical role in the development of countries; therefore, it is essential that their performance is evaluated according to specific criteria. Among the various functions of universities, research and knowledge production is significant; so, evaluating their scientific outputs should be a substantial part of a performance evaluation system. One of the most well-known methods for a scientific production evaluation is the use of scientometrics measures. In recent years, the scientific production of Iranian universities in engineering has been favorable; hence, we selected and analyzed 85,097 scientific papers from Iranian universities under the Ministry of Science, Research and Technology. The universities were ranked based important measures including: cumulative number of scientific outputs, number of citations, qualitative contribution, h-index, m-parameter, and g-index. Results show that the University of Tehran in both cumulative number of scientific outputs as well as number of citations, Sharif University of Technology in both h-and g- indices, Polymer & Petrochemical Institute in qualitative contribution, and Babol Noshirvani University of Technology in m-parameter as well as portion of engineering faculties in engineering outputs are the best among the surveyed universities. Moreover, our ranking has a significant correlation with that of the ISC ranking system according to the cumulative number of scientific outputs, number of citations, h-index, and g-index.

The role of knowledge and science are paid attention in national development because creating expertise and improving the Total factor productivity of production. Furthermore, the position of technology and knowledge is considered vital as endogenous factors in this development process. On the other hand, the conversion of knowledge into product and service will meet the needs of different communities. Knowledge-based companies are included as institutions that work as factories converting knowledge into product and service. Although, knowledge-based companies create sustainable knowledge-based economy and development of indigenous knowledge in many countries, but in accordance with the country's 20-year outlook and in terms of quality and quantity, they are not in ideal situation and are faced with challenges in their own development process. This research aims at identifying challenges facing knowledge-based companies located in Yazd's Science and Technology Park of Eghbal and prioritizing these challenges using Artificial Neural Network. The case study includes 137 managers and senior staff of these companies. Fifty nine challenges obtained from related literatures and experts’ opinions have been compiled in a questionnare and distributed among target population. One hundred and twenty eight collected questionnairs were validated by BP Artificial Neural Network and confirmed with MSE=2.0332 and challenges were prioritized with Artificial Neural Networks Radial Basis Function. The research proved that 19 of 59 challenges were priority among which economic problems of the country, industry and domestic markets recession and government’s unbalanced support policies can be pointed out.