Scientia Iranica
Volume:31 Issue: 3, Jan-Feb 2024

Food matters public daily lives, it is both practically and theoretically imperative to enhance the governance of food safety risks. In this paper, a three-tier supply chain model involving government regulatory authorities, food producers and customers is established for designing a risk governance mechanism of food safety based on a reputation updating model. Meanwhile, the study also explores the influence of reputation on product quality and sales price for food producers, as well as the accuracy in testing product quality of government and the effectiveness of governmental regulations. The results show that product price is positively correlated with the reputation, and negatively related the government's rewards and punishments. When the government improves accuracy of food sample testing and enhances rewards and strengthens punishments for food producers, product quality can be effectively controlled, sales prices can be balanced, and producer’s profits can be improved. Finally, this paper provides insight on the risk governance of food safety through many observations. It is found that a relatively slow process for producers to improve company reputation by improving its product quality, but issues with food quality and safety afford a devastating blow to the company reputation once this information is released.

This paper deals with the application of discriminant analysis in an electrical discharge machining (EDM) process to determine the comparative contribution of each of its input parameters on the measured responses. It also identifies the most significant EDM process parameters influencing those responses. For this process, voltage, current, pulse-on time and pulse-off time are considered as the input parameters, whereas, material removal rate, electrode wear rate and surface roughness are the responses. Based on the past and simulated experimental data, both simultaneous and step-wise estimations are carried out for each of the three responses showing the relationships between the EDM process parameters and the considered responses. It is observed that in both these estimations, pulse-off time, current and pulse-on time respectively evolve out as the most significant parameters for material removal rate, electrode wear rate and surface roughness. Step-wise estimation identifies voltage as the least significant input parameter for all these responses. The developed discriminant functions, which can also help in predicting the responses, are finally cross-validated.

Statistical process monitoring, maintenance policy, and production have commonly been studied separately in the literature, whereas their integration can lead to more favorable conditions for the entire production system. Among all studies on integrated models, the underlying process is assumed to generate independent data. However, there are practical examples in which this assumption is violated because of the extraction of correlation patterns. Autocorrelation causes numerous false alarms when the process is in the in-control state or makes the traditional control charts react slowly to the detection of an out-of-control state. The auto-regressive moving average (ARMA) control chart is selected as an effective tool for monitoring autocorrelated data. Therefore, an integrated model subject to some constraints is proposed to determine the optimal decision variables of the ARMA control chart, economic production quantity, and maintenance policy in the presence of autocorrelated data. Due to the complexity of the model, a particle swarm optimization (PSO) algorithm is applied to search for optimal decision variables. An industrial example and some comparisons are provided for more investigations. Moreover, sensitivity analysis is carried out to study the effects of model parameters on the solution of the economic-statistical design.

Industrial clusters are one of the most current development models. Aggregation of firms in a geographical area has many advantages, such as cost reduction, better supply, and knowledge emission with linkage together. The linkage result will be created the networks. The industrial clusters without co-operation networking will not be developed. That must be noticed to severe changes of business environment parameters. Therefore, this paper develops an uncertain mathematical model under sustainable and dynamic conditions. The model contains four objectives, namely profit, transportation cost, employment, and environment appraisal of the cluster. The outcome of this research is to find the best/optimal solution for firms’ arrangements with/within networks that maximize the profit, employment, and environment score and so minimize the transportation cost. The assignment patterns show horizontal and vertical cooperation with/within networks. The efficiency of model clustering in sub-clusters is followed by the neighbor clustering efficiency and the one’s clustering efficiency methods.

A multi-objective optimization problem (MOP) is a simultaneous optimization of more than one real-valued conflicting objective function subject to some constraints. Most MOP algorithms try to provide a set of Pareto optimal solutions which are equally good in terms of the objective functions. The set can be infinite, and hence, analysis and choice task of one or several solutions among the equally good solutions is hard for a decision maker (DM). In this paper, a new scalarization approach is proposed to select a Pareto optimal solution for convex MOPs such that the relative importance assigned to its objective functions is very close together. In addition, two decision-making methods are developed to analyze convex and non-convex MOPs based on evaluating a set of Pareto optimal solutions and the relative importance of the objective functions. These methods support the DM to rank the solutions and obtain one or several of them for real implementation without having any familiarity about MOPs.

This study presents a model for inventory control of deteriorating product in which both quantity and quality deterioration of the products are considered overtime. In this regard, for maximizing the profit, a new model is developed through two concepts: (1) establishing a decreasing pricing policy that depends on quality in order to prevent the decline in demand and product quality deterioration, and (2) investigating the level of investment in preservation technology as a significant solution in affecting the product deterioration rate. Consequently, it maintains the quality of products and increases their expiration date. In addition, the time value of money and inflation are well noticed in making the calculation of financial flows more accurate. To demonstrate the characteristics of the model, two comparative studies are conducted. The first one emphasizes the increase in the total profit of the inventory system caused by dynamic pricing policy, and another establishes the major impact of paying attention to the time value of money and inflation on making decisions.

At present, there are many subways being constructed in many cities.Constructing subways requires an appropriate scheme that can help to minimize costs while ensuring the quality of the project.....