Ali Goodarzi; Ali Mostafaeipour; Hasan Hosseini Nasab; Yahia Zare Mehrjerdi
Abstract
A multi-level sustainable supply chain is related to a system that includes all activities necessary to transfer and supply materials and services from the producer to the consumer. In this system, the focus is on providing materials and services based on a number of objectives, such as reducing costs, ...
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A multi-level sustainable supply chain is related to a system that includes all activities necessary to transfer and supply materials and services from the producer to the consumer. In this system, the focus is on providing materials and services based on a number of objectives, such as reducing costs, increasing quality, and preserving the environment. Due to the increase of uncertainty in the supply chain, organizations need to use resources for the prediction of internal uncertainties, needs, and supply, thereby minimizing vulnerability and elevating the tolerance of their supply. Understanding the uncer-tainties and the parameters causing factors causes the problem of risk management to be raised in some cases. Therefore, main contribution of current study is multi-objective planning for a sustainable, multi-level, multi-period model, consid-ering the determined conditions and boom as uncertainty scenarios, has been specifically considered. The most important goal of the research is to determine the best units of each level (suppliers, factories, ...) of chain networks according to the points and criteria determined in the model and network, design and determine the best communication routes (network) between the selected units Each level is optimal with other levels as well as determining the volume of transported goods in these routes. For this purpose, a mathematical model has been developed, which is solved through the limited epsilon method and NSGA-II meta-heuristic algorithm. Data comparing the mathematical model and NSGA-II meta-heuristic algorithm show the calculated errors of 0.022, which considering that it is less than 0.1, the calculation error is acceptable and can be compared to the results of the error methods. The sensitivity analysis on the probability of the boom scenario showed the value of the objective function can change between 7398.51 and 3245.73. Finally, the sensitivity analysis of the probability of recession scenario showed the value of the objective function can change between 3291.64 and 9364.35. The findings of this research show that using the multi-objective planning model in the sustainable supply chain, taking into account the boom and bust of the market, can create significant improvements in the performance and profitability of the supply chain.
Zahra Jiryaei Sharahi; Yahia Zare Mehrjerdi; Mohammad Saleh Owlia; Masoud Abessi
Abstract
In a data-driven decision-making process, there are various types of data that should be thoroughly processed and analyzed. Data mining is a well-recognized method to obtain such information by analyzing data and transforming it into actionable insights for further use. Among the various data mining ...
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In a data-driven decision-making process, there are various types of data that should be thoroughly processed and analyzed. Data mining is a well-recognized method to obtain such information by analyzing data and transforming it into actionable insights for further use. Among the various data mining techniques such as classification, clustering, and association rules, this research focused on classification techniques and presented an innovative regression-based learning approach in the decision tree (DT) models. DT algorithms are easy-to-understood and can work with different data types including continuous, discrete, and non-numerical. Despite a large number of existing studies, which attempt to enhance the performance of the DT models, there is still a gap in accurately extracting knowledge from databases. In this research, this issue is addressed by exploiting regression and coefficient of determination (R2) methods in a DT. The proposed tree provides new insights in the following aspects: split criterion, handling continuous and discrete variables, labeling leaf node, pruning process by stopping criteria and tree evaluation. The superiority of the proposed algorithm is demonstrated using a real-world hospital database and a comparison with existing approaches is provided. The results showed that the proposed algorithm outperforms the existing methods in terms of higher accuracy and lower complexity.
Marzieh Karimi; Hasan Khademi zare; Yahia Zare Mehrjerdi; Mohammad-Bagher Fakhrzad
Abstract
Vendor-managed inventory (VMI) is a popular inventory management system that allows a vendor to access sales data and manage inventory levels for his retailers. The formulation of service level and pricing decisions are finite in the VMI model literature. The study examines how a manufacturer and its ...
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Vendor-managed inventory (VMI) is a popular inventory management system that allows a vendor to access sales data and manage inventory levels for his retailers. The formulation of service level and pricing decisions are finite in the VMI model literature. The study examines how a manufacturer and its retailer communicate with one another to optimize their net profits through modifying service level, pricing, and inventory policy in a VMI system employing a Stackelberg game. The manufacturer produces a product and distributes it to several retailers at a similar wholesale price. The retailers subsequently offer the product at retail pricing in independent marketplaces. The Cobb-Douglas demand function could characterize the demand rate in every market, which is an enhancing function of the service level, however, a reducing function of retail prices. The manufacturer selects its wholesale pricing, replenishment cycles, backorder amount, and binary variable for production capacity to optimize profit. Retailers determine retail pricing and service levels so that they may optimize their profitability. Solution procedures are evolved for finding the Stackelberg game equilibrium from which no firm is inclined to deviate from maximizing its profit. The balance benefits the manufacturer while increasing the revenues of the retailers. If the retailers are prepared to engage with the manufacturer via a cooperative contract, the equilibrium could be enhanced to the advantage of both the manufacturer and his retailers. Ultimately, a numerical example is shown, along with the appropriate sensitivity analysis, to demonstrate that. 1) In certain circumstances, the manufacturer might benefit from his leadership and monopolize the additional profit generated by the VMI system. 2) The manufacturer's profit, and later the retailers' profit, could be increased more by the cooperative contract, in comparison to the Stackelberg equilibrium; 3) Market-related parameters have a substantial impact on the net profit of any enterprise.