Showing 27 results for Inventory
H. Teimory, H. Mirzahosseinian, A. Kaboli,
Volume 19, Issue 4 (12-2008)
Abstract
The advent of e-commerce has prompted many manufacturers to redesign their traditional channel structure by engaging in direct sales. In this paper, we present a dual channel inventory model based on queuing theory in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel which stocks are kept in both upper and lower echelon. The system receives stochastic demand from the both channel which each channel has an independent demand arrival rate. A lost-sales model which no backorder is allowed is supposed. The replenishment lead times are assumed independent exponential random variables for both warehouse and the retail store. Under the replenishment inventory policy, the inventory position is kept constant at a base-stock level. To analyze the chain performance, an objective function included holding and lost sales costs is defined. At the end, a proposed algorithm named, Best Neighborhood (BN) is used to find a good solution for inventory and the results are compared with Simulated Annealing (SA) solutions.
Mona Ahmadi Rad, Mohammadjafar Tarokh, Farid Khoshalhan ,
Volume 22, Issue 1 (3-2011)
Abstract
This article investigates integrated production-inventory models with backorder. A single supplier and a single buyer are considered and shortage as backorder is allowed for the buyer. The proposed models determine optimal order quantity, optimal backorder quantity and optimal number of deliveries on the joint total cost for both buyer and supplier. Two cases are discussed: single-setup-single-delivery (SSSD) case and single-setup-multiple-deliveries (SSMD) case. Two algorithms are applied for optimizing SSMD case: Gradient search and particle swarm optimization (PSO) algorithms. Finally, numerical example and sensitivity analysis are provided to compare the total cost of the SSSD and SSMD cases and effectiveness of the considered algorithms. Findings show that the policy of frequent shipments in small lot sizes results in less total cost than single shipment policy .
Mona Ahmadi Rad , Farid Khoshalhan,
Volume 22, Issue 2 (6-2011)
Abstract
inventory model, backorder buyer , vendor, lot for lot policy |
In this paper, an inventory model for two-stage supply chain is investigated. A supply chain with single vendor and single buyer is considered. We assume that shortage as a backorder is allowed for the buyer and the vendor makes the production set up every time the buyer places an order and supplies on a lot for lot basis. With these assumptions, the joint economic lot size model is introduced and the minimum joint total relevant cost and optimal order quantity and optimal shortage quantity are obtained for both the buyer and the vendor at the same time. Numerical example is given and then Sensitivity analysis is performed to study the effects of changes in the parameters on optimum joint total relevant cost and optimal order quantity and optimal shortage quantity .
E. Teimoury, I.g. Khondabi , M. Fathi ,
Volume 22, Issue 3 (9-2011)
Abstract
Discrete facility location, Distribution center, Logistics, Inventory policy, Queueing theory, Markov processes, |
The distribution center location problem is a crucial question for logistics decision makers. The optimization of these decisions needs careful attention to the fixed facility costs, inventory costs, transportation costs and customer responsiveness. In this paper we study the location selection of a distribution center which satisfies demands with a M/M/1 finite queueing system plus balking and reneging. The distribution center uses one for one inventory policy, where each arrival demand orders a unit of product to the distribution center and the distribution center refers this demand to its supplier. The matrix geometric method is applied to model the queueing system in order to obtain the steady-state probabilities and evaluate some performance measures. A cost model is developed to determine the best location for the distribution center and its optimal storage capacity and a numerical example is presented to determine the computability of the results derived in this study .
Mostafa Setak, Samaneh Sharifi,
Volume 22, Issue 4 (12-2011)
Abstract
In recent years, Supplier evaluation and selection, an important element in supply chain management, has been gaining attention in both academic literature and industrial practice. The Mixed integer multi-Objective non-Linear programming model (MIMONLP) presented in this paper aimed to evaluate and select the appropriate set of suppliers considering quantitative and qualitative criteria and in addition to selecting the first layer's suppliers which relate directly to the organization, analyses the characteristics of second-layers suppliers, and design a network to determine the flow rate of products and materials between buyers and best suppliers in both layers. Another important feature of this model is considering holding costs of different products over the planning horizon and quantity discounts for the first layer's suppliers at the same time. Finally, the model is solved by using goal programming approach and numerical examples are presented to test the performance of proposed model.
Maghsoud Amiri, Mehdi Seif Barghy, Laaya Olfat, Seyed Hossein Razavi Hajiagha ,
Volume 23, Issue 1 (3-2012)
Abstract
Inventory control is one of the most important issues in supply chain management. In this paper, a three-echelon production, distribution, inventory system composed of one producer, a set of wholesalers and retailers is considered. Costumers' demands can be approximated by a normal distribution and the inventory policy is a kind of continuous review (R, Q). In this paper, a model based on standard cost structure of inventory systems is developed and a heuristic algorithm is designed to optimize the developed model. The application of model is examined in a series of designed experiments that are compared with simulation results. These comparisons verify the validity of the model. Regarding to real complexities in three-echelon systems analysis, the proposed method can have a wide application in practical problems with the same considerations and assumptions. In addition, this method can be used to approximate those systems that follow a Poisson demand.
Mostafa Hajiaghaei-Keshteli, Majid Aminnayeri,
Volume 23, Issue 4 (11-2012)
Abstract
In this paper, the cost function for a three-echelon inventory system with two warehouses is derived. Transportation times are constant and retailers face independent Poisson demand. Replenishments are one-for-one. The lead time of a retailer is determined not only by the constant transportation time but also by the random delay incurred due to the availability of stock at the warehouses. We consider two warehouses in the second echelon which may leads to having more delays which were incurred in the warehouses and facing different behaviors of independent Poisson demands. Because the replenishment policy is base stock, the obtained function can also be used in different ordering policies to compute the inventory holding and shortage costs.
Masoud Mahootchi, Taher Ahmadi, Kumaraswamy Ponnambalam,
Volume 23, Issue 4 (11-2012)
Abstract
This paper presents a new formulation for warehouse inventory management in a stochastic situation. The primary source of this formulation is derived from FP model, which has been proposed by Fletcher and Ponnambalam for reservoir management. The new proposed mathematical model is based on the first and the second moments of storage as a stochastic variable. Using this model, the expected value of storage, the variance of storage, and the optimal ordering policies are determined. Moreover, the probability of within containment, surplus, and shortage are computable without adding any new variables. To validate the optimization model, a Monte Carlo simulation is used. Furthermore, to evaluate the performance of the optimal FP policy, It is compared to (s*,S*) policy, as a very popular policy used in the literature, in terms of the expected total annual cost and the service level. It is also demonstrated that the FP policy has a superior performances than (s*,S*) policy.
M. Ameli, A. Mirzazadeh, M. Shirazi,
Volume 24, Issue 1 (2-2013)
Abstract
It was suggested in 2004 by some researchers that it might be possible to improve production systems performance by applying the first and second laws of thermodynamics to reduce system entropy. Then these laws were used to modify the economic order quantity (EOQ) model to derive an equivalent entropic order quantity (EnOQ). Moreover the political instability or uncertainty of a country (as well as the whole world) leads to a much more unstable situation in the present world economy. Thus, changes in inflation take place, and it is needed to consider uncertain inflation rate. In this paper we extend the EnoQ model by considering deteriorating items with imperfect quality and price dependent demand. We also assume fuzzy inflation and discount rates. A mathematical model is developed to determine the number of cycles that maximizes the present value of total revenue in a finite planning horizon. The fuzzified model for inflation and discount rate is formulated and solved by two methods: signed distance and fuzzy numbers ranking. Numerical examples are presented and results are discussed. Results show that the number of cycles decreases in fuzzy inflationary conditions. They also illustrate that defuzzification method results in more cycles than fuzzy method.
Sanchita Sarkar, Tripti Tripti Chakrabarti,
Volume 24, Issue 4 (12-2013)
Abstract
In the fundamental production inventory model, in order to solve the economic production quantity (EPQ) we always fix both the demand quantity and the production quantity per day. But, in the real situation, both of them probably will have little disturbances every day. Therefore, we should fuzzify both of them to solve the economic production quantity (q*) per cycle. Using α-cut for defuzzification the total variable cost per unit time is derived. Therefore the problem is reduced to crisp annual costs. The multi-objective model is solved by Global Criteria Method with the help of GRG (Generalized Reduced Gradient) Technique. In this model shortages are permitted and fully backordered. The purpose of this paper is to investigate a computing schema for the EPQ in the fuzzy sense. We find that, after defuzzification, the total cost in fuzzy model is less than in the crisp model. So it permits better use of the EPQ model in the fuzzy sense arising with little disturbances in the production, and demand.
Seyed Mohammad Seyedhosseini, Mohammad Mahdavi Mazdeh, Dr. Ahmad Makui, Seyed Mohammad Ghoreyshi,
Volume 27, Issue 1 (3-2016)
Abstract
In any supply chain, distribution planning of products is of great importance to managers. With effective and flexible distribution planning, mangers can increase the efficiency of time, place, and delivery utility of whole supply chain. In this paper, inventory routing problem (IRP) is applied to distribution planning of perishable products in a supply chain. The studied supply chain is composed of two levels a supplier and customers. Customers’ locations are geographically around the supplier location and their demands are uncertain and follow an independent probability distribution functions. The product has pre-determined fixed life and is to be distributed among customers via a fleet of homogenous vehicles. The supplier uses direct routes for delivering products to customers. The objective is to determine when to deliver to each customer, how much to deliver to them, and how to assign them to vehicle and routes. The mentioned problem is formulated and solved using a stochastic dynamic programming approach. Also, a numerical example is given to illustrate the applicability of proposed approach.
Ramin Sadeghian,
Volume 27, Issue 2 (6-2016)
Abstract
Generally ordering policies are done by two methods, including fix order quantity (FOQ) and fix order period (FOP). These methods are static and either the quantity of ordering or the procedure of ordering is fixing in throughout time horizon. In real environments, demand is varying in any period and may be considered as uncertainty. When demand is variable in any period, the traditional and static ordering policies with fix re-order points cannot be efficient. On the other hand, sometimes in real environments some costs may not be well-known or precise. Some costs such as holding cost, ordering cost and so on. Therefore, using the cost based inventory models may not be helpful. In this paper, a model is developed which can be used in the cases of stochastic and irregular demand, and also unknown costs. Also some attributes consisting of expected positive inventory level, expected negative inventory level and inventory confidence level are considered as objective functions instead the objective function of total inventory cost. A numerical example is also presented for more explanation.
Nita Shah, Chetan Vaghela,
Volume 28, Issue 2 (6-2017)
Abstract
Abstract
In this research, an integrated inventory model for non-instantaneous deteriorating items is analyzed when demand is sensitive to changes in price. The price used in this research is a time-dependent function of the initial selling price and the discount rate. To control the deterioration rate of items at the storage facility, investment in preservation technology is incorporated. To provide a general framework to the model, an arbitrary holding cost rate is used. Toward the end of the paper, a numerical case is given to approve the model and the impacts of the key parameters of the model are studied by sensitivity analysis to deduce managerial insights.
Mahdi Bashiri, Elaheh Ghasemi,
Volume 29, Issue 2 (6-2018)
Abstract
Supplying of blood and blood products is one of the most challenging issues in the healthcare system since blood is as extremely perishable and vital good and donation of blood is a voluntary work. In this paper, we propose a two-stage stochastic selective-covering-inventory-routing (SCIR) model to supply whole blood under uncertainty. Here, set of discrete scenarios are used to display uncertainty in stochastic parameters. Both of the fixed blood center and bloodmobile facilities are considered in this study. We suppose that the number of bloodmobiles is indicated in the first stage before knowing which scenario is occurred. To verify the validation of the presented SCIR model to supply whole blood, we examine the impact of parameters variation on the model outputs and cost function using the CPLEX solver. Also the results of comparison between the stochastic approach and expected value approach are discussed.
Seyyed-Mahdi Hosseini-Motlagh, Mina Nouri-Harzvili, Roza Zirakpourdehkordi,
Volume 30, Issue 3 (9-2019)
Abstract
Parviz Fattahi, Mehdi Tanhatalab, Joerin Motavallian, Mehdi Karimi,
Volume 31, Issue 2 (6-2020)
Abstract
The present work addresses inventory-routing rescheduling problem (IRRP) that is needed when some minor changes happen in the time of execution of pre-planned scheduling of an inventory-routing problem (IRP). Due to the complexity of the process of departing from one pre-planned scheduling IRP to a rescheduling IRP, here a decision-support tool is devised to help the decision-maker. This complexity comes from the issue that changes in an agreed schedule including the used capacity of the vehicle, total distance and other factors that need a re-agreements negotiation which directly relates to the agreed costs especially when a carrier contractor is responsible for the distribution of goods between customers. From one side he wants to stick to the pre-planned scheduling and from the other side, changes in predicted data of problem at the time of execution need a new optimized solution. The proposed approached applies mathematical modeling for optimizing the rescheduled problem and offers a sensitivity analysis to study the influence of the different adjustment of variables (carried load, distance, …).
Mohammad Hasan Esmaili, Seyed Meysam Mousavi,
Volume 31, Issue 2 (6-2020)
Abstract
To demonstrate the importance of customer satisfaction can mention numbers of the service providers that attempt to differentiate themselves by satisfied their customers, witnessed high growth. In this paper, some factors that increase retailers and customers’ satisfaction, such as driver consistent services and delivering fresh products, are considered in a perishable inventory routing problem (PIRP) under possibility and necessity class of fuzzy uncertainty measures. In a typical inventory routing problem (IRP), a distribution center delivers products to a set of customers through a limited time horizon, and simultaneously makes a decision about inventory and routing to minimize the total cost. The proposed model is formulated as mixed-integer programming. Two types of consistent driver services are regarded for different kinds of customers, including particular and typical customers. To investigate the validity of the model, the problem is solved for two values of possibility and necessity measures.
Tahere Hashemi, Ebrahim Teimoury, Farnaz Barzinpour,
Volume 31, Issue 3 (9-2020)
Abstract
Retailers selling fresh products often encounter unsold inventory remains at the end of each period. The leftover product has a lower perceived quality than the new product. Therefore, retailers try to influence consumers’ preferences through price differentiation that leads to an internal competition based on product age and prices. This paper addresses the pricing and inventory control problem for fresh products to capture the influence of this competition on the supply chain members’ decisions and profits. A new coordination model based on a return policy with the revenue and cost-sharing contract is developed to improve the profits of independent supply chain members. The supply chain consists of one supplier and one retailer, where consumers are sensitive to the product’s retail price and freshness degree. Firstly, the retailer’s optimal decisions are derived in a decentralized decision-making structure. Then a centralized approach is used to optimize the supply chain decisions from the whole supply chain viewpoint. Eventually, a new coordination contract is designed to convince the members to participate in the coordination model. Numerical examples are carried out to compare the performance of different decision-making approaches. Our findings indicate that the proposed contract can coordinate the supply chain effectively. Furthermore, the coordinated decision-making model is more profitable and beneficial for the whole supply chain compared to the decentralized one. The results also demonstrate that when consumers are more sensitive to freshness, the simultaneous sale of multiple-aged products at different prices is more profitable.
Hadi Mokhtari, Aliakbar Hasani, Ali Fallahi,
Volume 32, Issue 2 (6-2021)
Abstract
One of the basic assumptions of classical production-inventory models is that all products are of perfect quality. However, in real manufacturing situations, the production of defective items is inevitable, and a fraction of the items produced may be naturally imperfect. In fact, items may be damaged due to production and/or transportation conditions in the manufacturing process. On the other hand, some reworkable items exist among imperfect items that can be made perfect by additional processing. In addition, the classical production-inventory models assume that there is only one product in the system and that there is an unlimited amount of resources. However, in many practical situations, several products are produced and there are some constraints related to various factors such as machine capacity, storage space, available budget, number of allowable setups, etc. Therefore, we propose new constrained production-inventory models for multiple products where the manufacturing process is defective and produces a fraction of imperfect items. A percentage of defective items can be reworked, and these products go through the rework process to become perfect and return to the consumption cycle. The goal is to determine economic production quantities to minimize the total cost of the system. The analytical solutions are each derived separately by Lagrangian relaxation method, and a numerical example is presented to illustrate and discuss the procedure. A sensitivity analysis is performed to investigate how the variation in the inputs of the models affects the total cost of the inventory system. Finally, some research directions for future works are discussed.
Rahul S Mor, Arvind Bhardwaj, Vishal Kharka, Manjeet Kharub,
Volume 32, Issue 2 (6-2021)
Abstract
Inventory management plays a vital role in attaining the desired service level and prevents excess capital from being tied up in the form of dead stock. This paper presents a framework to effectively determine the items subject to obsolescence in an automotive spare parts warehouse. The inventory management techniques are applied to minimize the costs and a framework is proposed based on ABC-XYZ and FSN analysis to prioritize the spare parts based on their criticality. Further, the importance of items in the warehouse is carried out to eliminate the dead stock. The ABC classification findings reveal that A-class items accounted for 10.39% and hold the highest inventory value grouping. XYZ classification concludes that much priority should be given to the management of 52.7% of items under the Z category as the demand trend of these items is highly fluctuating. The N category items have no demand in recent times and need immediate attention, thereby preventing further unnecessary procurement. Thus, based on the ABC-XYZ and FSN analysis, the non-critical items, i.e., the non-moving items having fluctuating demand, are sorted out.