Tehran, as one of the most populated capital cities worldwide, is categorized in the group of highly polluted cities in terms of the geographical location as well as increased number of industries, vehicles, domestic fuel consumption, intra-city trips, increased manufacturing units, and in general excessive increase in the consumption of fossil energies. City logistics models can be effectively helpful for solving the complicated problems of this city. In the present study, a queuing theory-based bi-objective mathematical model is presented, which aims to optimize the environmental and economic costs in city logistics operations. It also tries to reduce the response time in the network. The first objective is associated with all beneficiaries and the second one is applicable for perishable and necessary goods. The proposed model makes decisions on urban distribution centers location problem. Subsequently, as a case study, the fruit and vegetable distribution network of Tehran city is investigated and redesigned via the proposed modelling. The results of the implementation of the model through traditional and augmented ε-constraint methods indicate the efficiency of the proposed model in redesigning the given network.

The environmental changes caused by industrial activities have spurred a significant interest in designing supply chain networks by considering environmental issues such as CO2 emission. The pivotal role of taking uncertainty and risk into account in closed-loop supply chain networks has induced numerous researchers and practitioners to develop appropriate decision making tools to cope with these issues in such networks. To design a supply chain regarding environmental impacts under uncertainty of the input data and to cope with the operational risks, this paper proposes a multi objective possibilistic optimization model. The proposed model minimizes traditional costs such as cost of products shipment, purchasing machines and so on, as well as minimizing the environmental impact, and as a results strikes a balance between the two objective functions. Furthermore, in order to solve the proposed multi objective fuzzy mathematical programming model, an interactive fuzzy solution approach is applied. Numerical experiments are used to prove the applicability and feasibility of the developed possibilistic programming model and the usefulness of the applied hybrid solution approach.

Density functional theory with the basis set of 6-31+G(d) was used to investigate on the carbon nano layers, C(sp2), potential as a drug delivery system for transferring of anti-cancer drug temozolomide to the target tissue. In order to elucidate the possibility of drug transmission by utilizing a carrier, the mechanisms of direct drug degradation, and loaded drug on the carrier are analyzed and examined completely. Two possible and different pathways for direct drug hydrolysis have been considered. According to obtained results activation barriers of these two pathways are 62.17 and 72.10 kcal mol^-1, and 64.30 and 70.10 kcal mol^-1 for two gas mode and also two aqueous solvent conditions respectively. By comparison of outcomes, it can be found out that these activation barriers for both degradation pathways are significantly greater than the activation barriers for drug separation from the surface of carbon carrier (18.59 and 51.92 kcal mol^-1 for gas mode and 11.79 and 44.67 kcal mol-1 for aqueous solvent). Therefore, by studying the achieved outcomes, it can be deduced that separation and releasing of the drug from the carrier occurs faster kinetically than direct degradation of temozolomide, so the drug can reach to the target before direct decomposition.

In this paper, the severe plastic deformation method (SPD) known as constrained groove pressing (CGP) was applied to produce ultrafine-grained microstructure in IF steel sheets. In the CGP technique, samples are subjected to repetitive shear deformation under the plane strain deformation condition using the constrained grooved and flat dies. For assessment of microstructure and mechanical properties of the CGPed IF steel sheet, several testing such as: uniaxial tensile test, hardness measurements, scanning electron microscopy (SEM) and X-ray diffraction analysis have been utilized. Finally, it was observed that the grains are significantly refined after the 16-step pressing of the interstitial free (IF) steel sheets. The grains were reduced from 45µm to 243 nm after four passes.

When a satellite is in orbit, micro vibration generated by its actuators (such as reaction wheels, deployable mechanisms, etc.) will affect the imaging quality of the camera. Viscoelastic materials are utilized as passive isolators to reduce these micro vibrations due to their simple construction and excellent energy dissipation capacity, A finite element model of the entire satellite as well as the camera is constructed using the ABAQUS software and then four reaction wheels are included as the sources of micro-vibrations and their forces are added to the model. To isolate these vibrations, four square sorbothane pads are designed and added in the finite element model as viscoelastic dampers located under the camera, between the camera and satellite bus. The generalized Maxwell model is employed to describe the dynamic properties of the viscoelastic elements in the ABAQUS software. Finally, by analyzing and comparing the dynamic responses of the system with and without the viscoelastic sorbothane pads, it is realized that this isolation system can effectively reduce the reaction wheel micro-vibrations on the camera and subsequently increase the image quality.

Since today’s world is moving ahead rapidly, the condition for the survival and durability of insti-tutions and organizations depend on research, development, innovation, and communication, the realization of which requires the presence of a new and creative model. Therefore, this paper aims to formulate and explain an open successful innovation management model by seeking the factors affecting the diffusion of innovation model at sports federations. The study in term of goal is ap-plied and in term of data analysis method is descriptive correlational study. The statistical popula-tion consists of sports federations of Iran in 2017. The sample size was 70 individuals selected us-ing Morgan table and the simple random sampling method from 10 federations. The research col-lection data tool was a questionnaire. The correlation matrix was used to determine the relationships between independent and dependent variables. Furthermore, a novel hybrid technique of fuzzy DEMATEL and fuzzy ANP was used to rank the factors affecting open innovation. The results showed that structural factors, interorganizational joint venture, customer relationships, research and development department, and new technologies affected the open innovation. Moreover, struc-tural factors were ranked the most effective factors. Then, customer relationships and interorganiza-tional joint venture were known as the weakest factors affecting the creation of open innovation.

Supply Chain Management (SCM) is the set of approaches used for the appropriate integration and utilization of suppliers, manufacturers, warehouses and retailers to ensure the production and delivery of products to end users in the right quantities and at the right time. Integration of the stages in the supply chain can make it more effective and profitable as a whole. In the present study, an integrated production and distribution problem in a two-stage supply chain is considered. The supply chain consists of m manufacturers with different locations and rates of production, and a distributer that delivers the ordered products to customers in different locations. Here, products are seasonal and perishable and must be delivered before a specified time. To characterize the problem, a Mixed Integer Programming (MIP) model is proposed and to solve the proposed model, a Hybrid Simulated Annealing (HSA) and a Genetic Algorithm (GA) with mixed repair and penalize strategies are introduced. Computational results of HSA are compared with those of the GA algorithm as the current best algorithm for solving similar problems in the literature.

Very recently, Qiupeng and Zuxing (2017) [Qiupeng, G., & Zuxing, X. (2017). A new approach for ranking fuzzy numbers based on possibility theory. Journal of Computational and Applied Mathematics, 309, 674-682.] suggested a new fuzzy ranking technique on the basis of possibility theory. In this note, we show that this method leads to the incorrect result in various cases.

Fuzzy Analytical Network Process (F-ANP) method is able to consider the complex relationships among different levels of decisions, transactions, and feedbacks of criteria and alternatives to calculate the weights of the elements. The large number of pair-wise comparisons in F-ANP and also difficulties in understanding the way of comparisons for the expert, have reduced the efficiency and practicality of this method. In this paper, in order to eliminate the above-mentioned problems, it has been tried to provide an approach using the Fuzzy Best-Worst method, called F-BWANP. The proposed method, requires less comparison data and leads to more consistent comparisons, which means that more reliable results can be obtained, while making it much easier for responding by experts. Finally, in order to describe the proposed method and evaluate its capability, a numerical example is provided.

As an attractive feature for modern transportation systems, the potential of the transfers capability (the load/passenger transfer between the two vehicles in its route) in reducing costs, increasing customer satisfaction and increasing the flexibility of the system, has been approved. But how profitable it could be under different circumstances? In other words, to which factors its influence depends on? what are its benefits versus its costs? The present research aimed to give a relatively comprehensive answer to these questions using a mathematical model of the pickup and delivery system with transfers. According to the model results under different situations, many factors such as modeling assumptions, system goals, transportation network scheme, vehicle fleet in terms of capacity, cost rate, and time window of activity and requests in terms of the length (direct distance between the pickup and delivery points), time windows and the volume to vehicle capacity ratio, affect the transfers benefits. As the small-scale numerical results indicate, we have an average of 5.7% reduction in the trip cost under normal conditions, which increases with the heterogeneity of vehicles, shorter time windows, and an increase in the length of the request. On the other hand, it is expected that profitability increases by problem size.