Inventory control of deteriorating items constitutes a large part of the world’s economy and covers various goods including any commodity, which loses its worth over time because of deterioration and/or obsolescence. Vendor managed inventory (VMI), which is a win-win strategy for both suppliers and buyers gains better results than traditional supply chain. In this research, we study an economic order quantity (EOQ) with shortage in form of partial backorder under VMI policy. The model is concerned with multi-item subject to multi-constraint including storage space, time period and budget constraints. Two metaheuristic algorithms, namely Simulated Annealing and Tabu Search, are used to find a near optimal solution for the proposed fuzzy nonlinear integer-programming problem with the objective of minimizing the total cost of the supply chain. Furthermore, the sensitivity analysis of the metaheuristic parameters is performed and five numerical examples containing different numbers of items are conducted in order to evaluate the performance of the algorithms.

A molecular mechanism of the [3+2] cycloaddition has been explored using various DFT theoretical levels. It was found that the reaction proceeds via transition states with different synchronicity, but no intervention of the theoretical possible zwitterionic intermediates. Additionally, regioselectivity of the cycloaddition process has been analysed using vibrational analysis of localised TSs

Nowadays, companies offer product bundles with special discounts in order to sell more products. However, it is important to note that customers show different levels of loyalties to companies, and each segment of the market has unique features, which influences the customers’ buying patterns. The primary purpose of this paper is to propose a novel model for product bundling in e-commerce websites by using market segmentation variables and customer loyalty analysis. RFM model is employed to calculate customer loyalty. Subsequently, the customers are grouped based on their loyalty levels. Each group is then divided into different segments based on market segmentation variables. The product bundles are determined for each market segment via clustering algorithms. Apriori algorithm is also used to determine the association rules for each product bundle. Classification models are applied in order to determine which product bundle should be recommended to each customer. The results demonstrate that the silhouette coefficient, support, confidence, and accuracy values are higher when both customer loyalty level and market segmentation variables are used in product bundling. Accordingly, the proposed model increases the chance of success in direct marketing and recommending product bundles to customers.

Mokran coasts have good potentials for development and investment, in terms of access to the high seas, geopolitical situation, especially, benefit from certain natural circumstances and history, but for various reasons, this area has no growth, commensurate with the potential. This study is conducted to evaluate investment opportunities in the region, to identify the necessary infrastructures and the promotion of entrepreneurial activities. The method identifies 22 investment opportunities through a comparative study and using best-worst multi-criteria decision method (BWM), and experts’ opinion, the possibility of implementing them are ranked in Mokran. Then, the necessary public infrastructure requirements are ranked in eleven groups with TOPSIS. The results show that, private port sites, loading, warehouses, commercial centers and special areas of fisheries, provide good opportunities for investors, and infrastructure, security, transport, sustainable energy, and the single window government services are the priorities for planning in the public sector.

Clustering is a popular data mining technique for grouping a set of objects into clusters so that objects in one cluster are very similar and objects in different clusters are quite distinct. K-means (KM) algorithm is an efficient data clustering method as it is simple in nature and has linear time complexity. However, it has possibilities of convergence to local minima in addition to dependence on initial cluster centers. Artificial Bee Colony (ABC) algorithm is a stochastic optimization method inspired by intelligent foraging behavior of honey bees. In order to make use of merits of both algorithms, a hybrid algorithm (MABCKM) based on modified ABC and KM algorithm is proposed in this paper. The solutions produced by modified ABC are treated as initial solutions for the KM algorithm. The performance of the proposed algorithm is compared with the ABC and KM algorithms on various data sets from the UCI repository. The experimental results prove the superiority of the MABCKM algorithm for data clustering applications.

Medical tourism industry is an international phenomenon, which most of medical tourists for some reasons such as high costs of treatment, long waiting queues, lack of insurance and lack of access to health care in the origin country, travel long distances to benefit from health care services of destination country. Given the competitive nature of this industry, most countries are designing practical and legal services and planning for their development. For this purpose, this study has been conducted to develop a strategic planning framework for development of medical tourism industry in Yazd province of Iran; because in recent years Yazd has recognized as the health pole by patients in developing countries. In sum, emphasizing on servicing, enhancing and developing specialized treatment centers, has attracted patients from center, south and east of the country as well as Middle East and Central Asia countries. The dominant approach in this study is developmental – practical and also the research method is descriptive, analytical and survey. In order to analyzing the data, the SWOT model and best-worst techniques have been used. In the following, after identifying strategic position of Yazd province in terms of medical tourism industry, the related strategies were formulated and practical results were presented.

Tourism infrastructure development in different regions of the world does not follow a symmetrically equal pattern. Because of the importance of infrastructure in the tourism development, the present research is an attempt to examine the hard elements of tourism infrastructure in different provinces of Iran, using the indicators proposed by Pearce and Wu (2015) [Pearce, P. L. & Wu, M. Y. (2015). Soft infrastructure at tourism sites: identifying key issues for Asian tourism from case studies. Tourism Recreation Research, 40 (1), 120-132.]. To accomplish this, the data registered in the statistical yearbook of the Statistical Center of Iran were investigated. The method of research was analytical survey. To analyze and rank the data collected from the yearbook, VIKOR and TOPSIS methods were employed. The results of the analysis show that Tehran Province was under the best conditions of the Iranian tourism infrastructure, whereas Ilam Province was under the worst condition. The results about the condition of hard tourism infrastructure in the provinces of Iran, next to their tourism potentials, can provide necessary data for the future planning of the industry.

Proper functioning of electrical connectors used in high oscillation is of great importance. Vibrations in connector pins cause stress and electrical resistance variations in the contact surface. In the present paper, the impacts of vibrational loads on electrical connectors is being modeled using the finite element method, and the electrical resistance oscillations of the connectors will be examined. Ultimately, the parameters affecting the electrical resistance oscillations of contacts will be determined and their relations with oscillations in electrical resistance are specified as well.

In the present work, an elasto-plastic model is proposed for the numerical analysis of dynamic nonlinear behavior of composite thick shells with reinforcements in spirals subjected to impulsive loading. Wilkins algorithm was taken to analysis physical and geometrical non-linearity of stress-strain state of elasto-plastic thick composite shells. This study is carried out on two types of cylindrical composite shells in different reinforcement winding angles and different magnitudes of impulse loads. By a calculation code in finite difference, first the influence of physical non linearity on the stress-strain state of cylindrical monolayer shell was established and then the relationship between residual strains and the winding angle of the symmetric reinforcements was investigated. Finally, the influence of the winding angle of the orthogonal reinforcements on the residual strains of a bilayer composite shell was analyzed numerically.

Heterogeneity is an important factor controlling fracture initiation, accumulation, and propagation within rock destruction. Traditionally, rock reaction instability within rock destruction is associated with rock non-homogeneity or considered self-excited, but no clear relations between rock structure options and reaction force oscillation were proposes. This work hypothesizes the idea rock structure options are one of the factors of drill bit whirling. The authors innovated the Wojtanowicz and Kuru’s force static balance model to numerically simulate 3-cutter movement in a rock space, assuming a crack propagates by rock grains getting around. Instability of deviation between directions of cutting force and crack propagation causes rock reaction instability. Novelty of this work is to consider the mutual influence of rock granulomentric composition options (sizes, shape and distribution of grains) and drill bit design options (cutter diameter, distance between adjacent cutters, etc.) on rock reaction force oscillation. The follow tendencies were observed: rock grain dimension increasing and grain concentration increasing were accompanied with rock reaction force magnitude decreasing; random grain placing and/or grain random dimensions caused increasing of rock reaction force scattering; random grain sizes are more essential for rock reaction forces (and their projections) scattering than random grain distribution.