Simulation optimization of an inventory control model for a reverse logistics system

Nowadays, companies are recognizing their primordial roles and responsibilities towards the protection of the environment and save the natural resources. They are focusing on some contemporary activities such as Reverse Logistics which is economically and environmentally viable. However, the integration of such an initiative needs flows restructuring and supply chain management in order to increase sustainability and maximize profits. Under this background, this paper addresses an inventory control model for a reverse logistics system that deals with two separated types of demand, for new products and remanufactured products, with different selling prices. The model consists of a single shared machine between production and remanufacturing operations, while the machine is subject to random failures and repairs. Three stock points respectively for returns, new products and remanufactured products are investigated. Meanwhile, in this paper, a modeling of the problem with Discrete-Event simulation using Arena® was conducted. Regarding the purpose of finding, a near-optimal inventory control policy that minimizes the total cost, an optimization of the model based on Tabu Search and Genetic Algorithms was established. Computational examples and sensitivity analysis were performed in order to compare the results and the robustness of each proposed algorithm. Then the results of the two methods were compared with those of OptQuest® optimization tool.

Responding to the Impact of the COVID-19 on Food Value Chains – Case of Industry Practice

Supply chain operations in food value chains includes all logistics activities that enable the flow of agriculture inputs, outputs, and agriculture-related services, such as transportation, warehousing, procurement, packaging and inventory management. The efficacy of logistics is critical for the agri-food sector, in particular in times of crisis. Disruptions can cause adverse impacts on the quality of food, freshness, its safety, and can impede access to markets and affordability. The COVID-19 pandemic caused that the governments around the world implemented different measures, including a reduction in the transportation of goods (ground, ocean freight and air freight), as well as migration of labour domestically and internationally. In order to stop the transmission of the disease workers are less available in transportation systems because restrictions across borders. These issues induce disruptions in the logistics of the food supply chains. The contemporary business environment in COVID-19 pandemic environment imposes an increased need for the development of decision-support tools. The Shadow IT solution will be described on the example of the inventory control model for frozen fruit wholesale, implemented as a spreadsheet application.

ANALYSIS OF INVENTORY MANAGEMENT FOR AGRO AND ORGANIC PRODUCT SATISFYING CUSTOMER WITH MAXIMUM PROFIT USING EOQ MODEL

Inventory management of agro-based industry (dairy product) is a challenging tax because due to its perishable nature.EOQ model has its importance & role for proper management of this category of Inventory. The success of many businesses is related to their ability to provide goods and services at right time and in right place. Different organization adopt different inventory control methods to manage their inventory to avoid stock-out and overstock. This paper analyses possible parameters of existing literature, concentration, description of characteristics and of EOQ inventory control model that have been developed and can solve the Problem in this field & will provide the customer satisfaction with profit maximization.

Research on Multi-Echelon Inventory Optimization for Fresh Products in Supply Chains

Fresh products are perishable and fragile, which easily leads to higher inventory costs and requires reasonable planning of inventory management. Therefore, it is very important for fresh product supply chain systems to have multi-echelon inventory control. However, in past studies, few control models of the multi-echelon inventory considered the deterioration rate of perishable products as the variable factor. In this paper, on the basis of considering the perishable characteristics of fresh products, combining the deterioration rate with the inventory control model, a multi-echelon inventory control model for fresh products is designed and optimized, and the optimal solution from the whole supply chain is obtained through the optimal fitness function by genetic algorithm. Finally, Flexsim is used to simulate the two inventory strategies before and after optimization. After simulation comparison and analysis, it is verified that the optimized inventory control strategy has lower costs. The research results can help supply chain managers of fresh products to make inventory management decisions and save costs, which is of practical significance.

Forecast Methods and Periodic Review Inventory Model for Supply Planning to Reduce Food Waste

Food waste is an important economic and resource problem in all countries around the world. Particularly, the restaurant sector highly contributes to food waste and limited efforts or studies have been performed to overcome this problem. In this context, the present study addresses an alternative to improve the supply planning for perishable products in the restaurant sector through the application of specific forecasting methods and a stochastic inventory control model. For this purpose, a real enterprise within this economic sector was considered. Our findings support that monthly forecasts can be more appropriate for accurate demand estimation and supply planning of perishable products, which is important to reduce unnecessary products. Also, the periodic review inventory control model can lead to a more appropriate supply scheme to reduce the waste of surplus food. These findings and the proposed techniques can be used for other economic entities to reduce product waste due to poor supply planning.

Modelling Sustainable Development Aspects within Inventory Supply Strategies

Nowadays, inventory management is a tool that must be extended to cover all aspects of the supply chain (SC). One of these aspects is Sustainable Development (SD) which emphasizes the balance between economic well-being, natural resources, and society. As inventory involves the use of natural and economic resources, the integration of SD criteria is important for a more efficient and sustainable SC. In this work, the most important SD variables associated with inventory management were identified. These variables were integrated as cost elements within a nondeterministic inventory control model to include SD criteria within inventory supply strategies. Through the assessment of the proposed integrated model, it was determined that, although SD practices involve additional investments, specific practices such as reuse/recycling and government incentives can increase revenue and profits. This is important for the development of government and business strategies to perform sustainable practices.

Modeling the Hidden Risk of Polyethylene Contaminants within the Supply Chain

Inventory management is very important to support the supply chain of the manufacturing and service industries. All inventories involve warehousing; however, most of the products and packages are associated to plastic which is the main generator of polyethylene (phthalate) pollution in the air and water resources. In fact, phthalate has been identified as the cause of serious health conditions and its impact within the operation of logistic processes has not been studied. In this work, we perform research on the generation of phthalate as the control on these emissions is important to adjust the supply strategy to reduce the human risk exposure and contamination of the environment. For this purpose, generation of phthalate is modeled through the use of artificial neural networks (ANNs) and its impact on the supply strategy is assessed through its integration within a stochastic inventory control model. As presented, it is possible to adjust the supply strategy to reduce the cumulative generation of phthalate within the warehouse and thus reduce its impact on human health and environment sustainability.