Journal of Advances in Industrial Engineering
Volume:57 Issue: 1, Winter and Spring 2023

One of the most challenging tasks in the perishable products industry is to control the inventory of products and find the optimum location to store them. This paper tries to respond to these challenges in a way that is close to reality. In this paper, a location-inventory model has been studied for a supply chain with perishable products, considering the dependence of demand to price. The investigated multi-product and multi-period supply chain includes manufacturers, distributors, retailers and customers. Products and centers of this chain are equipped with Radio Frequency Identification (RFID) technology. The location-inventory model, by simultaneously capturing strategic, tactical and operational decisions, can be very effective in increasing the supply chain efficiency. For this purpose, a mixed integer nonlinear programming model is presented. The purpose of the model is to maximize the profitability of the supply chain, which is achieved by the simultaneous decision-making of location, inventory, pricing and demand. Finally, in order to show the efficiency of the proposed model, numerous examples with various parameters are solved and sensitivity analysis is done. The results show that as the dependence of customer demands on price increases, it is inevitable that the supply chain sells the product to customers at a lower price and lower profit, and this causes an extreme decrease in supply chain profit. The lower dependence on the supply chain results in higher profit.

In the two last decades, the analysis of the agriculture supply chain (ASC) has been paid attention by academics and practitioners. However, the issue of coordinating ASC is not considered so much where weak collaborations make lower profits and efficiencies. In this research, the distribution of profits and coordination of a three-level ASC including a gardener, a major buyer, and a retailer are investigated. The problem has been developed for both centralized and decentralized models. The optimal strategies of ASC are obtained for both models. In this study, the wholesale price contractual mechanism is investigated where the buyer’s and retailers’ wholesale price and the farm size are decision variables to find win-win situations under coordination. The proposed models were solved and sufficient propositions were developed. The numerical study is illustrated. The results show that with increasing farm area, the optimal harvest amount per unit area decreases for the centralized model. Furthermore, with increasing farm size, the gardener harvest amount per unit area and the supply amount increase where the retail selling price is almost constant for both cases. At the same level, with increasing farm size, the supply chain profit increases. In decentralized analysis with a wholesale price contract, the gardener's harvest amount per unit area and the supply amount increase by increasing the gardener's wholesale price. Moreover, by increasing the gardener’s wholesale price, its profit increases, and the profit of the buyer and the retailer decreases. For future studies, analyzing and comparing other coordinating contracts, such as revenue sharing and traditional ASCs contracts is proposed.

The high popularity and profitability of gift cards encourage many sellers to use them to sell their goods. Retailers have also been encouraged to use independent third parties to sell their gift cards for increasing their sales channel and taking advantage of it. This paper develops a two-echelon supply chain for gift card incentive policy, with a third party and retailer at the first level and a supplier at the second one. The most important research questions are as follows: order amount of chain members to maximize their own and the whole chain profit, gift card prices by the retailer to its customers, gift card prices by the retailer to third party, and gift card prices by the third party to customers. Stackelberg's approach is used to solve the model, assuming that the third party is the follower and the retailer is the leader. In addition, by proving the concavity of the objective function, obtaining the closed-form solution for variables, and proving the resulting solutions, an algorithm has been developed to achieve the optimal answer. Findings showed that the use of cards in the case of economic order models increases the demand for retail and on the other hand attracts more customers and better brand expansion. A numerical example as well as a sensitivity analysis are performed to describe the model. Finally, conclusions as well as suggestions for future research are provided.

Airlines try to reduce costs by improving the quality of their operational schedules. However, numerous uncontrollable factors make disruptions inevitable. A flight delay or cancellation caused by disruption may spread throughout the network and increase the operational costs by affecting the schedule of other flights, including aircraft, crew, and passengers’ itineraries. While previous researchers have focused on one of these aspects or sequential approaches, the resulted solutions cannot lead to a reliable operational solution due to the complex relationships between these factors in practice. Therefore, integrated recovery approaches are highly essential. The main objective of this research is to provide a fully integrated recovery model that contains various recovery scenarios to tackle the disruption and delay propagation with more flexibility and acceptable solution time. So, an integrated model for crew, aircraft, and passenger recovery problem is proposed in this paper. The proposed model is formulated as MILP, based on individual flight legs to achieve a more accurate schedule with better recovery solution. Options such as aircraft reassignment, crew swapping, reassignment of passengers, and ticket refunds are considered as alternatives to face disruption. Moreover, the considerations related to crew rest-time and maintenance requirements are also included in the model. Due to the NP-Hard nature of the problem, the Genetic algorithm is used as the solution approach successfully for the real-world data to limit delay propagation on various random flights.

This study aims to examine the adaptation level of the reference point, the dynamic level of this point, and the intensity of investors' reaction to gains and losses based on prospect theory. The basis of the study is the adaptation of the reference point based on the received stimuli and considering the disposition effect. In this regard, a sample of 103,937 firm-year observations of the firms listed on the Tehran Stock Exchange (TSE) during the years 2008 to 2020 and an integrated panel data approach was used to examine the research hypotheses. The results show that, because investors act on the stimuli they receive to correct their reference point, the reference point cannot be fixed. Five variables (stimuli) – gain (loss) amount, gain (loss) duration, simultaneous effect of amount and duration of gain (loss), positive (negative) EPS adjustment, and positive (negative) coverage percentage of EPS – have a significant effect on trading volume and reference point adaptation level, and they can be mentioned as adaptation determinant factors of the reference point. The results show that the intensity of investors' reaction to gains and losses is not the same. In most studies, the reference point is assumed to be fixed and static. The reference point does not appear to be static and varies according to the conditions and stimuli received. In this research, the researchers intend to identify the factors affecting the reference point, to provide a dynamic model that can explain how investors' reference point is adapted.

One of the most important factors of socio-economic development in any country is the quality of electricity sources. Considering the sensitivity of electronic devices and the dependence of most activities on electricity, providing sustainable energy in the urban system is very important. Therefore, a comprehensive view of the factors causing disturbances in the electricity distribution network is very valuable in order to prevent any electricity losses. The goal of the current research is to identify, evaluate and prioritize operational risks in the aerial electricity distribution network. Any operational risk is a potential cause of the incident that leads to an unplanned outage. In this study, by reviewing the research literature, incidents recorded in the electricity distribution network incident registration system (known as the 121 system), and conducting interviews, 21 operational risk cases have been listed and approved by experts. On the other hand, to solve the limitations of the FMEA method, by combining the BWM method and using the knowledge of experts (completion of the questionnaire), evaluation and prioritization were done with more differentiation. The results showed that from the point of view of experts, the intensity index is critical (0.475). Also, three operational risks with high priority in the electricity distribution network of Yazd province include; Failure in concrete foundations, the impact of foreign objects, and failure in transformers. Statistics emphasize that high-priority risks are responsible for 27% of unplanned outages in the last ten years. Operators and managers of electricity distribution companies can consider high-priority risks and provide solutions to reduce, eliminate or transfer risks. In this case, in addition to minimizing unplanned outages in the network and selling more electricity, customer satisfaction is achieved.