A Two-Warehouse Model for Deteriorating Items with Holding Cost under Particle Swarm Optimization

A deterministic inventory model has been developed for deteriorating items and Particle Swarm Optimization (PSO) having a ramp type demands with the effects of inflation with two-warehouse facilities. The owned warehouse (OW) has a fixed capacity of W units; the rented warehouse (RW) has unlimited capacity. Here, we assumed that the inventory holding cost in RW is higher than those in OW. Shortages in inventory are allowed and partially backlogged and Particle Swarm Optimization (PSO) it is assumed that the inventory deteriorates over time at a variable deterioration rate. The effect of inflation has also been considered for various costs associated with the inventory system and Particle Swarm Optimization (PSO). Numerical example is also used to study the behaviour of the model. Cost minimization technique is used to get the expressions for total cost and other parameters

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

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

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 high-tech 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

Optimalisasi dan Pemodelan Inventory dengan Dua Gudang Penyimpanan untuk Barang yang Mengalami Penyusutan dengan Backlog Shortage dan Waktu Tunggu (Lead Time) Fuzzy

Adanya kebijakan optimalisasi inventory yang diambil sebuah perusahaan atau retailer untuk barang yang mengalami penyusutan dengan ketidakpastian waktu tunggu (lead time) sampai barang selesai diproduksi atau pesanan datang, adanya backlog shortage sebagian atau penuh, dan tingkat permintaan bergantung harga dikembangkan dalam sistem dua gudang yang masing‐masing sebagai gudang penjualan (display) atau tempat transaksi barang dan gudang tempat penyimpanan jika barang yang diproduksi atau dibeli tidak cukup ditempatkan di gudang penjualan. Tujuan perusahaan atau retailer mempunyai dua gudang penyimpanan adalah untuk mengoptimalkan keuntungan rata‐rata jika memproduksi atau membeli barang dalam jumlah besar. Perusahaan atau retailer mempunyai satu gudang dengan kapasitas terbatas yang letaknya di lokasi strategis sebagai tempat penjualan, yang disebut sebagai gudang milik (own warehouse, OW) dan gudang yang lain dengan kapasitas cukup luas disesuaikan dengan kebutuhan yang lokasinya berbeda dengan tempat penjualan atau transaksi, yang disebut sebagai gudang sewa (rented warehouse, RW). Biaya penyimpanan barang di RW menurun dengan bertambahnya jarak dari RW ke OW. Hal ini disebabkan oleh biaya sewa gudang dan upah tenaga kerja yang lebih murah dibandingkan di lokasi OW. Barang dikirim dari RW ke OW dalam jumlah yang telah ditentukan (fixed) berdasarkan pola tertentu. Dalam penelitian ini dikembangkan dua model inventory yaitu model inventory dengan backlog shortage sebagian dan model inventory dengan backlog shortage penuh. Untuk memperoleh penyelesaian akan digunakan metode pendekatan interval terdekat untuk fungsi single objektif yang memaksimalkan keuntungan rata‐rata dalam fuzzy (defuzzified) dan ditransformasikan dalam fungsi multi objektif crisp yang selanjutnya akan diselesaikan dengan metode kriteria global (global criterion method) untuk memperoleh solusi optimal Pareto. Kata kunci : Dua Gudang Penyimpanan, Backlog Shortage, Waktu Tunggu Fuzzy

Volume flexible multi items inventory system with imprecise environment

This paper addresses a multi items volume flexible system for time dependent decaying items with the concept of machine breakdown and imprecise environment. In this study, partially backlogged shortages have been discussed. All the costs are fuzzified with signed distance method. Numerical examples are given to illustrate the theoretical results and sensitivity analysis is given to validate the results for various parameters

A New Multi-objective Inventory Model under Stochastic Conditions with Considering Perishable Costs

This paper presents a new multiple objectives model for the optimal production for an inventory control system. The stocked items may be deteriorates and the systems costs will be change over the time. In the real situation, some but not all customers will wait for backlogged items during a shortage period and therefore, the model incorporates partial backlogging. The demand rate can be a function of inflation and time value of money where the inflation and time horizon i.e., period of business, both are random in nature. The objectives of the problem are: (1) Minimization of the total expected present value of costs over time horizon (consists of the deterioration cost, production cost, inventory holding cost, backordering cost, lost sale cost and ordering cost) and (2) Decreasing the total quantity of goods in the warehouse over time horizon. We propose the ideal point approach to formulate the model. The numerical example has been provided for evaluation and validation of the theoretical results

A Sustainable Bi-Objective Inventory Model with Source-Based Emissions and Plan-Based Green Investments under Inflation and the Present Value of Money

The paper develops a finite-horizon inventory model with source-based emissions, plan-based green investments under inflation, and the present value of money. The cap-and-trade policy is used as the carbon policy. The model is solved in a bi-objective scenario where the two objectives are maximization of the present value of net profit and minimization of the total emission. We find the Pareto optimal solutions represented by a Pareto front using the ε-constraint method. A flowchart is provided to find the non-dominated solutions. Pareto solutions for three special cases (no inflation, carbon tax, and no green investments) are also derived. In our sensitivity analyses, we observe that the carbon quota does not affect the optimal policy. It only affects the optimum profit. Our model shows that green investment is beneficial for the polluting firm and also for the environment. (original abstract