Discrete Dynamics in Nature and Society

In the present study, a mathematical model is provided for inventory management in a three-level supply chain including a supplier, a manufacturer, and a distributor, taking into account the potential for product deficiency. Significant parameters such as the optimal order size for raw materials, optimal production rate, optimal allowed deficiencies at each supply chain level, the of the vehicles and the number of times the products are delivered between the supply chain components have been provided aiming at minimizing inventory management costs in the supply chain. The problem was solved using a heuristic algorithm. The proposed model is implemented for 20 different numerical examples. According to the results, the difference between the solutions obtained from the algorithm and the solutions obtained from the optimal values with the real variables is an average of 1.52%.

In this study, due to the importance of emergency centers and patient transport vehicles in epidemic conditions, the performance of emergency centers has been evaluated based on health protocols. The criteria were first divided into preventive and operational sections by collecting opinions, health experts, standard criteria, and the Delphi method. Preventive criteria for evaluating emergency centers and operating criteria for assessing vehicles in these centers are considered. The weighting of the determined criteria was done by the triangular fuzzy aggregation method. According to the standard criteria, the emergency centers have been evaluated for a 30-day period. The results have been assessed as a qualitative and quantitative matrix using the PROMETHEE method. The results showed better performance of Center A (63%) due to proper performance and better compliance with protocols in both criteria (preventive and operational). The reason for the superiority of this center over Center B can be considered the better performance of this center in terms of prevention indicators and better performance of the center’s vehicles (Ambulance A-1 and Ambulance A-2) in the performance index by observing the standards.

Model selection and parameter estimation are very important in many fields. However, the existing methods have many problems, such as low efficiency in model selection and inaccuracy in parameter estimation. In this study, we proposed a new algorithm named improved approximate Bayesian computation sequential Monte Carlo algorithm (IABC-SMC) based on approximate Bayesian computation sequential Monte Carlo algorithm (ABC-SMC). Using the IABC-SMC algorithm, given data and the set of two models including logistic and Gompertz models of infectious diseases, we obtained the best fitting model and the values of unknown parameters of the corresponding model. The simulation results showed that the IABC-SMC algorithm can quickly and accurately select a model that best matches the corresponding epidemic data among multiple candidate models and estimate the values of unknown parameters of model very accurately. We further compared the effects of IABC-SMC algorithm with that of ABC-SMC algorithm. Simulations showed that the IABC-SMC algorithm can improve the accuracy of estimated parameter values and the speed of model selection and also avoid the shortage of ABC-SMC algorithm. This study suggests that the IABC-SMC algorithm can be seen as a promising method for model selection and parameter estimation.

This research article is devoted to presenting the concept of 2-tuple linguistic -polar fuzzy sets (2 TL FSs) and introducing some fundamental operations on them. With 2 TL FSs, we shall be able to capture imprecise information with high generality. With the appropriate operators, we shall be able to apply 2 TL FSs in decision-making efficiently. The aggregation operators that we propose are the 2 TL  F Hamacher weighted average (2 TL FHWA) operator, 2 TL  F Hamacher ordered weighted average (2 TL FHOWA) operator, 2 TL Hamacher hybrid average (2 TL FHHA) operator, 2 TL  F Hamacher weighted geometric (2 TL HWG) operator, 2 TL Hamacher ordered weighted geometric (2 TL HOWG) operator, and 2 TL  F Hamacher hybrid geometric (2 TL FHHG) operator. We investigate their properties, including the standard cases of monotonicity, boundedness, and idempotency. Then we develop an algorithm to solve multicriteria decision-making problems formulated with 2 TL  F information. The 2 TL  F data in multiattribute decision-making are merged with the help of aggregation operators, and we consider the particular instances of the 2 TL FHA and 2 TL FHG operators. The influence of the parameters on the outputs is explored with a numerical simulation. Moreover, a comparative study with existing methods was performed in order to show the applicability of the proposed model and motivate the discussion about its virtues and advantages. The results confirm that the model here developed is reliable for decision-making purposes.

This study adopts the revised gravity model to construct the spatial association network of trade in RECP countries and reveals its characteristics through a social network analysis method. The results are as follows: the spatial correlation of trade among RECP countries presents a complex, multithreaded network structure; the spatial correlation network of trade among RECP countries appears to fluctuate, indicating that their correlations, although influenced by the national environment, are still moving in the direction of regional integration; the degree centrality of China, Australia, and Korea is higher in terms of intermediary centrality and proximity centrality. This indicates that these countries are not only at the core of the network and have many associated relationships with other countries but also all are located at the center of the trade spatial association network; and the analysis results of the block model show that the trade spatial association network of RECP countries can be divided into four sections: net spillover, net benefit, broker, and two-way spillover. The spillover effect between the two sections has obvious gradient transmission characteristics.

As an important component of modern service industry, tourism is regarded as a “green” driver to regional economic growth and industrial upgrading. Applying the “quasi-natural experiment” advocated by the “The Belt and Road” initiative, this paper, based on the method of DID, assessed the influence of this initiative on regional tourism development by analyzing panel data collected from 286 prefecture-level cities in China over the period of 2007–2018. It is found that the “The Belt and Road” initiative has stimulated market dynamics and promoted tourism development in the regions along the route and has significantly improved indicators such as per capita domestic and inbound tourism revenue and per capita domestic and inbound tourist receipt. Also, the degree of contribution of domestic tourists to the tourism economy of the regions where the policy has been implemented is stronger than that of inbound tourists. In sum, the results of this paper not only confirm that the “The Belt and Road” initiative has significantly contributed to the high-quality tourism development of Chinese provinces along the routes but also provide important policy enlightenment for the upgrading of regional tourism industry and regional economic balance.