Scientia Iranica
Volume:31 Issue: 22, Nov-Dec 2024

Nowadays, due to the rapid pace of technology enhancement, growing consumer expectations, and market competitiveness, life cycle of products is shortening faster than it used to be. In such situations, where new generations of products lead to the obsolescence of those currently available, the simultaneous pricing of both newly developed and available products is a challenging task. In this paper, using game theory approaches, we investigate various possible conditions in which two firms may introduce new generations of products with short life cycles. Optimum price of newly developed and planned obsolescence products are determined by the proposed method. The effectiveness of the proposed method is verified using various numerical calculations and sensitivity analyses. A real case study from textile industry illustrates the application of the proposed approach in industry.

Abstract. This article discusses the problem of data synchronization methods using microservice architecture. Microservices is a popular and widespread software architecture today. The article reviews three main ways of interaction of microservices. They are event-based communication, interaction through direct HTTP requests and messaging, and also highlights and analyzes their advantages and disadvantages. The main purpose of the article is to analyze and make offer of the optimal option for solving the problem of synchronizing interacting microservices in real time. The optimal solution involves using the Apache Kafka message broker. It publishes data streams and subscriptions to them, as well as stores and processes them. Mathematical modeling of the proposed data synchronization method was described by constructing its state macine, as well as a system of canonical equations.

In this study, an economic production quantity (EPQ) model with deterioration is developed where the production rate is stock dependent and the demand rate is unit selling price and stock dependent. The low unit selling price and more stocks correspond high demand but more stock corresponds to slow production because of the avoidance of unnecessary stocks. First of all, we develop the production model by solving some ordinary differential equations having deterministic profit function under some specific assumptions. Later, we develop the fuzzy model by solving the fuzzy differential equations using Generalized Hukuhara derivative. In fact, the differential equation of the model has been split into two parts namely gH(L-R) and gH(R-L) on the basis of left(L) and right(R) α- cuts of fuzzy numbers for which the problem itself is transformed into multi-objective EPQ problem. A new formula of aggregation of several objective values obtained at different aspiration levels has been discussed to defuzzify the fuzzy multi-objective problems. We solve the crisp and fuzzy models using LINGO software. Numerical and graphical illustrations confirm that the model under Generalized Hukuhara derivative of (R-L) type contributes more profit which is one of the basic novelties of the proposed approach.

This research proposes a model that calculates the customer lifetime value and simultaneously considers the network effects. An oligopoly market is also considered in which companies compete with each other. Each company has a number of buyers and sellers and offers its services to the buyers free while receiving the sellers' membership fees in return. Interestingly, the customers interact with each other and change the companies' clients. This interaction between them is known as word-of-mouth marketing, and it also exists among the sellers. It is noteworthy that the existence of both buyers and sellers is only meaningful. Indeed, the increase of buyers leads to a rise in the number of sellers and also makes the company more profitable. In fact, the network effects are categorized into four forms that are as follows: (1) buyers’ effects on each other, (2) sellers’ effects on each other, (3) buyers’ effects on sellers, and (4) sellers’ effects on their buyers. These effects are the main factors that the companies tend to take into consideration when determining the optimal marketing and pricing policies. Applying differential game theory makes it possible to receive the companies' market share, advertising, and pricing strategy.

To understand how industrial designers, take into account "HFE" in the early design phase, wesurveyed in more than 50 companies. We analyzed their design work and evaluate if they need touse a new structured method. On the one hand, to provide a real image to understand what is goingin the companies, what they do, use and how they answer this problem. On the other, in to studythe applicability of the proposed method. The answers show us that there are no systematic methodsand tools that integrate "HFE" in the early design phase. Hence the importance of such a method.22 companies want to work with us to improve their methods.

An insufficient amount of capital conservation buffer would cause a financial institution to be unable to withstand fluctuations in the economic cycle; while an excessive amount would reduce the financial institution’s available funds, which would lead to a loss of the capital available for investment. In order to address this issue in an effective manner, the business loan default prediction model is established in this study by integrating survival analysis with logistic regression. In the section of case validation, the reliability of the proposed approach is validated with the information of businesses that have been granted loans by financial institutions in Taiwan, and the proposed approach was also compared with the Cox proportional hazards model approach, which is frequently applied by financial institutions. The empirical results demonstrate that the approach proposed in this study could predict a business loan default state closer to the actual default trend, and provide prediction results superior to that of the Cox proportional hazards model, thus, providing financial institutions with effective and reliable information for reference, which will allow them to prepare an appropriate amount of capital conservation buffer, and improve the capital flexibility of the financial institution.

In this paper, a novel two-stage multi-period stochastic model is developed to obtain a comprehensive plan. This plan aims to manage the assets and liabilities such that all legal and budget constraints are satisfied. Assets in the model include short- and long-term loans with reasonable interest rates, investments in the stock market, varied bonds with different expirations, investments in other banks, and the legal budget in the Central Bank. However, liabilities encompass all types of sight and investment deposits with different maturities. In the model, each type of deposit's amount is considered a decision variable, while its total amount is assumed to be stochastic. The mathematical model is constructed in an innovative way such that all previous loans and bonds with possible transactions in the planning horizon could be considered initial parameters. Real data for a commercial bank in Tehran, the Islamic Republic of Iran capital, are used to construct and check the optimization model. The total revenues obtained through the mathematical model and one achieved based on the experiences of financial experts in the commercial bank for four years are compared.

This study presents a fuzzy mathematical programming model to optimize regional wheat hub center in Iran with the aim of achieving sustainable self-sufficiency, swap and export of wheat to neighboring countries. The proposed model is developed for a 10-year planning horizon with real-world assumptions under uncertainty. By the proposed model, the optimal decisions are made on the amount of wheat cultivation areas in different provinces, capacity of silos, amount of import, swap and export of wheat, transportation mode and storage amount of wheat in different periods. Two objective functions including economic and environmental goals are optimized by the proposed model. The proposed model is examined under uncertainty conditions and the possibilistic programming approach is used to deal with the uncertainty of parameters. Finally, the presented model is validated through investigating a real case study in Iran. The results show the efficiency of the model for making optimal strategic and tactical decisions in wheat supply chains.