In this paper, it was an attempt to be present a practical perishability inventory model. The proposed model adds using spoilage of products and variable prices within a time period to a recently published locationinventory-routing model in order to make it more realistic. Aforementioned model by integration of strategic, tactical and operational level decisions produces better results for supply chains. Due to the NPhard nature of this model, a genetic algorithm with unique chromosome representation is used to achieve the optimal solution and reasonable time. Finally, the analysis is carried out to verify the effectiveness of the algorithm with and without considering the cost of spoiled products.

Blood is a vital substance for human life. A blood unit goes through various stages from its donation by the donor until its reception by the person in need of blood. This process can be explored the context of supply chain management. For this purpose, a mathematical model is developed in this study to design a blood supply chain network. The noticeable feature of this network is the inclusion of the shortage and perishability of blood products as two important indicators. The mathematical model proposed in this regard has the two objective functions of minimizing the blood supply chain costs and, at the same time, maximizing the average amount of blood sent from blood centers to hospitals. The model examines the problem in the case of a single product. The modified weighted Chebyshev, the improved version of ε,-constraint (AUGEMCON2), and unscaled goal programming are used to solve the mathematical model. Then, to evaluate and compare the proposed solution methods and select the best one, the statistical hypothesis test and the VIKOR technique are used respectively. Also, to investigate the reaction of the objective functions to the changes in the model parameters, several sensitivity analyses are performed. The results show that the model proposed for the blood supply chain is efficient and acceptable,hence, it can be of benefit in different types of blood supply chains where the shortage and perishability of blood products are taken into account.

Hamedan province is known as the center of potato production in the country, however, despite the appropriate production conditions, the market of this product does not experience favorable conditions and the difference between farmers 'incomes and consumers' final payment is one of the challenges in the market. Therefore, in this article, the structure of potato market in Hamedan province, as the core production area in Iran, was analyzed and evaluated. For this purpose, the statistics of monthly prices were scrutinized at different levels of the market in the period from April 2006 to April 2019. A significant and growing gap was observed in the market margins of this product. Then, the mechanism of price transfer and transmission were estimated and investigated. All of the results showed an inefficient structure in this market, which has stabilized the farmers in cobweb pattern and wholesalers in the position of monopoly. The results of the research indicated that four specific features of this market including low product elasticity, high perishability rate, lack of export schedules, low storage capacity and the high construction cost of warehouses have created this imperfect structure and should be given special attention in future policies.

In this study, we discuss a location-inventory-pricing model considering the capacity constraints of the warehouses, disruption, and multiple perishable products. We extend a model that assumes that warehouses may face disruption, failed warehouses cannot cover any service, and their customers are assigned to other warehouses. To decrease the risk of disruption, we examine the efficiency of markup pricing strategy and support services. The objective function of this MINLP is to maximize the total profit of warehouses. To solve this model, Genetic Algorithm (GA) and Grasshopper Optimization Algorithm (GOA) are used. To evaluate the recommended model, several sensitivity analyses are proposed. Finally, the results of numerical experiments implicate the high-performance of GOA in dealing with problems and achieving better results. According to the results, backup services and markup pricing strategies are very effective in reducing the damage caused by the disruption.

In this study, we discuss a location-inventory-pricing model considering the capacity constraints of the warehouses, disruption, and multiple perishable products. We extend a model that assumes that warehouses may face disruption, failed warehouses cannot cover any service, and their customers are assigned to other warehouses. To decrease the risk of disruption, we examine the efficiency of markup pricing strategy and support services. The objective function of this MINLP is to maximize the total profit of warehouses. To solve this model, Genetic Algorithm (GA) and Grasshopper Optimization Algorithm (GOA) are used. To evaluate the recommended model, several sensitivity analyses are proposed. Finally, the results of numerical experiments implicate the high-performance of GOA in dealing with problems and achieving better results. According to the results, backup services and markup pricing strategies are very effective in reducing the damage caused by the disruption.

Purpose: The purpose of this research is to design a perishable crops supply chain network. Furthermore, the disruption risk in the production sector and the protection strategy are considered to increase the reliability of the network. The goal of the proposed model is to maximize the total profit of the supply chain while considering the time to send the products to the consumers. Methodology: In this research, a mixed-integer non-linear programming model is proposed to optimize crops supply chain network design. Moreover, a real case study has been implemented in Iran to prove the applicability of the addressed model. Findings: The results and sensitivity analysis of the mathematical model indicate that by planning the planting and harvesting While optimizing the chain's profit, it is possible to respond well to society's product demand. Moreover, considering the disruptions and protection of products brings us closer to real-world conditions and reduces the amount of waste and related adverse environmental effects. Originality/Value: Agriculture is one of the most important and influential sectors in the economy of any country, it plays a vital role in its political and economic independence. The growing global demand to provide food for the human population has caused a significant increase in cultivation. However, the amount and time of production should be consistent with the amount of product demand and avoid a shortage or excess of products. Considering that there is currently no comprehensive planning for the production of perishable crops in the country, the necessity of studying supply chain models in the agricultural sector and specifically the production and distribution of perishable crops is created. In this connection, the design of the supply chain network of the mentioned products from planting to distribution is presented in this study.

Recently, market globalization and competition have forced companies to find alternative means to boost sales and revenue. The use of the cash flow is increasingly becoming a viable alternative for managers to improve their company’ s profitability in a supply chain. In today’ s business transactions, a supplier usually asks a manufacturer to pay via the advance-cash-credit (ACC) payment scheme if the number of goods procured is high. Additionally, product perishability has been considered in an economic production quantity (EPQ) model since it is a real phenomenon. The present work develops an EPQ model for perishable products under the ACC payment scheme. The objective of the proposed model is to determine the optimal selling price and cycle time while maximizing profit under the ACC payment scheme using a discounted cash flow analysis. A nonlinear optimization algorithm is also proposed to solve the problem. In addition, some numerical examples are employed to illustrate the solution approach and show the concavity of the present value of the total annual profit in terms of both selling price and cycle time. The numerical results show that our proposal algorithm could be applied well to solve the problems. In addition, a sensitivity analysis is conducted to obtain some managerial insights. For example, if the impact of advance payment on procurement cost is relatively smaller than that of cash payment, then it is more profitable for the manufacturer to ask for a cash payment than to receive an advance payment and vice versa.

There are issues such as limitation of blood resources, perishability, special preservation conditions of blood products and high wastage and shortage costs of blood products, make management of blood products consumption as one of the most complex issues in healthcare systems. This paper proposes a linear mathematical model to optimize consumption of the blood products in hospitals. In the proposed model, in addition to distribution of blood products between hospitals by blood center, possibility of lateral transshipments between hospitals considered as a strategy to deal with demand uncertainty. Furthermore, factor of blood freshness and the need of some surgeries for fresh blood considered in this model as real conditions. Finally, to validate the proposed model, a case related to one blood center and eight hospitals in Tehran city presented and its results discussed.

Following the need for joint optimization of decisions in supply chains, this paper newly provides an integrated framework to efficiently fulfill a production-planning-routing problem (PPRP). In such integrated scheme, a set of perishable family-products are manufactured on a single batch-processing machine. These products are dispatched to the customers by a third-party logistics service provider with only two types of licensed eco-friendly transportation facilities. In order to efficiently deliver the manufactured products before they become unusable, we propose a combined shipment structure. To accomplish this, we formulate the problem in the context of a MILP model. In particular, we aim to establish two manufacturing policies based on both increasing and decreasing rates of production and also two delivery policies expressing distinct preferences in fulfilling the customers’ demands. In this regards, we investigate the cost structures obtained from the established integrated planning and the resulting distribution configurations as well. Further, four heuristic algorithms are developed for solving the problem with respect to each hybrid production/distribution scheme derived from the former policies. Finally, to compare the mentioned procedures, it is conducted a numerical study illustrating the preferable efficiency of the plan gained according to the hybrid of the increasing-production-rate and decreasing-delivery-distance policies.

location-inventory problem (LIP) is a significant issue in supply chain management (SCM), aiming to reduce and integrate the costs of inventory and location. Perishable-LIP (PLIP) includes products, particularly those with a short expiration date, also known as perishable items. This feature necessitates the supply chain to maintain high reliability and resilience to minimize costs faced with disruption risks. Implementing reliability and resilience in PLIP (R2-PLIP) requires methods such as lateral transshipment. These methods not only enhance the reliability and resiliency of the SC but also mitigate the risks associated with supply disruptions and demand fluctuations. Demand for perishable products is influenced by their expiration dates. By incorporating lateral transshipment, companies can ensure a more balanced inventory distribution. This study investigates the role of lateral transshipment in enhancing supply chain robustness. A multi-objective optimization model is developed, focusing on minimizing costs while maximizing resilience and service levels. The project aims to optimize the overall system efficiency. Additionally, the sensitivity analysis conducted in the research indicates that the shortage cost and the DC capacity each had the greatest variations in one of the objective functions. This research provides practical insights for designing resilient perishable supply chains.