Supply chain finance for ameliorating and deteriorating products: a systematic literature review

Ameliorating and deteriorating products, or, more generally, items that change value over time, present a high sensitiveness to the surrounding environment (e.g., temperature, humidity, and light intensity). For this reason, they should be properly stored along the supply chain to guarantee the desired quality to the consumers. Specifically, ameliorating items face an increase in value if there are stored for longer periods, which can lead to higher selling price. At the same time, the costumers’ demand is sensitive to the price (i.e., the higher the selling price the lower the final demand), sensitiveness that is related to the quality of the products (i.e., lower sensitiveness for high-quality products). On the contrary, deteriorating items lose quality and value over time which result in revenue losses due to lost sales or reduced selling price. Since these products need to be properly stored (i.e., usually in temperature- and humidity-controlled warehouses) the holding costs, which comprise also the energy costs, may be particularly relevant impacting on the economic, environmental, and social sustainability of the supply chain. Furthermore, due to the recent economic crisis, companies (especially, small and medium enterprises) face payment difficulties of customers and high volatility of resources prices. This increases the risk of insolvency and on the other hand the financing needs. In this context, supply chain finance emerged as a mean for efficiency by coordinating the financial flow and providing a set of financial schemes aiming at optimizing accounts payable and receivable along the supply chain. The aim of the present study is thus to investigate through a systematic literature review the two main themes presented (i.e., inventory management models for products that change value over time, and financial techniques and strategies to support companies in inventory management) to understand if any financial technique has been studied for supporting the management of this class of products and to verify the existing literature gap

Optimal policy for multi-item systems with stochastic demands, backlogged shortages and limited storage capacity

Producción CientíficaIn this paper, an inventory model for multiple products with stochastic demands is developed. The scheduling period or inventory cycle is known and prescribed. Demands are independent random variables and they follow power patterns throughout the inventory cycle. For each product, an aggregate cycle demand is realized first and then the demand is released to the inventory system gradually according to power patterns within a cycle. These demand patterns express different ways of drawing units from inventory and can be a good approach to modelling customer demands in inventory systems. Shortages are allowed and they are fully backlogged. It is assumed that the warehouse where the items are stored has a limited capacity. For this inventory system, we determine the inventory policy that maximizes the expected profit per unit time. An efficient algorithmic approach is proposed to calculate the optimal inventory levels at the beginning of the inventory cycle and to obtain the maximum expected profit per unit time. This inventory model is applicable to on-line sales of a wide variety of products. In this type of sales, customers do not receive the products at the time of purchase, but sellers deliver goods a few days later. Also, this model can be used to represent inventories of products for in-shop sales when the withdrawal of items from the inventory is not at the purchasing time, but occurs in a period after the sale of the products. This inventory model extends various inventory systems studied by other authors. Numerical examples are introduced to illustrate the theoretical results presented in this work.Ministerio de Ciencia, Innovación y Universidades - Fondo Europeo de Desarrollo Regional (project MTM2017-84150-P

A Fuzzy Two-warehouse Inventory Model for Single Deteriorating Item with Selling-Price-Dependent Demand and Shortage under Partial-Backlogged condition

In this paper we have developed an inventory model for a single deteriorating item with two separate storage facilities (one is owned warehouse (OW) and the other a rented warehouse (RW)) and in which demand is selling- price dependent. Shortage is allowed and is partially backlogged with a rate dependent on the duration of waiting time up to the arrival of next lot. It is assumed that the holding cost of the rented warehouse is higher than that of owned warehouse. As demand, selling- price, holding- cost, shortage, lost- sale, deterioration- rate are uncertain in nature, we consider them as triangular fuzzy numbers and developed the model for fuzzy total cost function and is defuzzified by using Signed Distance and Centroid methods. In order to validate the proposed model, we compare the results of crisp and fuzzy models through a numerical example and based on the example the effect of different parameters have been rigorously studied by sensitivity analysis taking one parameter at a time keeping the other parameters unchanged

ONE-TIME ORDER INVENTORY MODEL FOR DETERIORATING AND SHORT MARKET LIFE ITEMS WITH TRAPEZOIDAL TYPE DEMAND RATE

Determining the end of the sales period for a one-time order inventory policy for technology products that see rapid innovation and improvement, such as smartphones, is a vital decision. While the market life cycle is short, with long lead times and expensive deliveries. Such situations can force the number of orders to be few or even only once. Products with the latest technology consist of many components that allow for deterioration from the start. This study discusses the effect of the market life cycle, as indicated by the trapezoidal demand rate, on deteriorating item inventory policies. This study will provide new insights into inventory policy. Mathematical models with a non-linear generalized reduced gradient approach can find the optimal end of the selling period and the order size to achieve maximum profit. A sensitivity analysis showed several findings that provide insight for management

A partial backlogging inventory model for deteriorating items with time-varying demand and holding cost: An interval number approach

This paper proposes a differential equation inventory model that incorporates partial backlogging and deterioration. Holding cost and demand rate are time dependent. Shortages are allowed and assumed to be partially backlogged. Two versions are presented, the first one with deterministic values of the parameters and the second one taking into the account the interval uncertainty of the parameters. In the crisp case, Taylor’s series expansion is used, and graphically shown that the cost function is convex. While, in the case of intervals, the interval arithmetic is used and then the problem is transformed into a multi-objective non-linear optimization problem and an interval objective function. To solve this problem, the weighted-sum method is used. The proposed procedure is validated with the help of a numerical example. Sensitivity analysis on various parameters has also been carried out

A note on optimal ordering policy for deteriorating items with uncertain maximum lifetime

As in case of deteriorating items, expiration plays a major role in management of inventory. In addition, maximum lifetime is not available certainly for items like food stuffs, packaged food, electronic items, etc. To incorporate uncertainty, a Fuzzy Economic Ordering Policy is formulated to minimize total cost of an inventory system. We consider triangular fuzzy maximum lifetime and triangular fuzzy costs under crisp ordering policy, in order to extent traditional optimal ordering policy to the fuzzy environment. We use function principle as arithmetic operations of Fuzzy Total Inventory Cost (FTIC), and Graded Mean Integration Representation is used to defuzzify the FTIC. Formulation is illustrated through numerical example. Sensitivity is carried out with respect to different parameters

Trade Credit Policies for Supplier, Manufacturer, and Retailer: An Imperfect Production-Inventory System with Rework

In this study, we developed a trade credit policy for a three-layer supply chain consisting of a supplier, a manufacturer and a retailer. We propose an optimal production rate and selling price for the manufacturer and the retailer under an imperfect production system. The suggested coordination policy optimizes the profit of each supply chain member. Two models were formulated for two real-life strategies respectively. The first one is a collaborative (integrated) system and the second one is a Stackelberg leadership system. Both strategies were analyzed for various credit periods, respectively offered by the supplier to the manufacturer, by the manufacturer to the retailer, and by the retailer to the customers, by considering price-sensitive demand and a certain replenishment rate. Finally, we concluded which strategy will be better for inventory management under the given restrictions in the form of propositions. The concavity property for the net profit function was established with respect to the selling price and the production rate, which was also described graphically and analyzed by numerical examples

A Partial Backlogging Inventory Model for Deteriorating Item under Fuzzy Inflation and Discounting over Random Planning Horizon: A Fuzzy Genetic Algorithm Approach

An inventory model for deteriorating item is considered in a random planning horizon under inflation and time value money. The model is described in two different environments: random and fuzzy random. The proposed model allows stock-dependent consumption rate and shortages with partial backlogging. In the fuzzy stochastic model, possibility chance constraints are used for defuzzification of imprecise expected total profit. Finally, genetic algorithm (GA) and fuzzy simulation-based genetic algorithm (FSGA) are used to make decisions for the above inventory models. The models are illustrated with some numerical data. Sensitivity analysis on expected profit function is also presented. Scope and Purpose. The traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However, to keep sales higher, the inventory level would need to remain high. Of course, this would also result in higher holding or procurement cost. Also, in many real situations, during a longer-shortage period some of the customers may refuse the management. For instance, for fashionable commodities and hightech products with short product life cycle, the willingness for a customer to wait for backlogging is diminishing with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But in the past, the economic situation of most of the countries has changed to such an extent due to large-scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any more. The purpose of this paper is to maximize the expected profit in the random planning horizon

Optimizing lot sizing model for perishable bread products using genetic algorithm

This research addresses order planning challenges related to perishable products, using bread products as a case study. The problem is how to effi­ci­ently manage the various bread products ordered by diverse customers, which requires distributors to determine the optimal number of products to order from suppliers. This study aims to formulate the problem as a lot-sizing model, considering various factors, including customer demand, in­ven­tory constraints, ordering capacity, return rate, and defect rate, to achieve a near or optimal solution, Therefore determining the optimal order quantity to reduce the total ordering cost becomes a challenge in this study. However, most lot sizing problems are combinatorial and difficult to solve. Thus, this study uses the Genetic Algorithm (GA) as the main method to solve the lot sizing model and determine the optimal number of bread products to order. With GA, experiments have been conducted by combining the values of population, crossover, mutation, and generation parameters to maximize the feasibility value that represents the minimal total cost. The results obtained from the application of GA demonstrate its effectiveness in generating near or optimal solutions while also showing fast computational performance. By utilizing GA, distributors can effectively minimize wastage arising from expired or perishable products while simultaneously meeting customer demand more efficiently. As such, this research makes a significant contri­bution to the development of more effective and intelligent decision-making strategies in the domain of perishable products in bread distribution.Penelitian ini berfokus untuk mengatasi tantangan perencanaan pemesanan yang berkaitan dengan produk yang mudah rusak, dengan menggunakan produk roti sebagai studi kasus. Permasalahan yang dihadapi adalah bagaimana mengelola berbagai produk roti yang dipesan oleh pelanggan yang beragam secara efisien, yang mengharuskan distributor untuk menentukan jumlah produk yang optimal untuk dipesan dari pemasok. Untuk mencapai solusi yang optimal, penelitian ini bertujuan untuk memformulasikan masalah tersebut sebagai model lot-sizing, dengan mempertimbangkan berbagai faktor, termasuk permintaan pelanggan, kendala persediaan, kapasitas pemesanan, tingkat pengembalian, dan tingkat cacat. Oleh karena itu, menentukan jumlah pemesanan yang optimal untuk mengurangi total biaya pemesanan menjadi tantangan dalam penelitian ini. Namun, sebagian besar masalah lot sizing bersifat kombinatorial dan sulit untuk dipecahkan, oleh karena itu, penelitian ini menggunakan Genetic Algorithm (GA) sebagai metode utama untuk menyelesaikan model lot sizing dan menentukan jumlah produk roti yang optimal untuk dipesan. Dengan GA, telah dilakukan percobaan dengan mengkombinasikan nilai parameter populasi, crossover, mutasi, dan generasi untuk memaksimalkan nilai kelayakan yang merepresentasikan total biaya yang minimal. Hasil yang diperoleh dari penerapan GA menunjukkan keefektifannya dalam menghasilkan solusi yang optimal, selain itu juga menunjukkan kinerja komputasi yang cepat. Dengan menggunakan GA, distributor dapat secara efektif meminimalkan pemborosan yang timbul akibat produk yang kadaluarsa atau mudah rusak, sekaligus memenuhi permintaan pelanggan dengan lebih efisien. Dengan demikian, penelitian ini memberikan kontribusi yang signifikan terhadap pengembangan strategi pengambilan keputusan yang lebih efektif dan cerdas dalam domain produk yang mudah rusak dalam distribusi roti