Tripti Chakrabarti

Bio: Tripti Chakrabarti is an academic researcher from Techno India University. The author has contributed to research in topics: Supply chain & Systems modeling. The author has an hindex of 3, co-authored 5 publications receiving 18 citations.

Two-echelon Supply Chain Model for Deteriorating Items in an Imperfect Production System with Advertisement and Stock Dependent Demand under Trade Credit

Abstract: This article presents a two-echelon supply chain model for deteriorating items, consisting of a single manufacturer and a single retailer, where the customer's demand to the retailer depends on advertisement and the displayed stock level of the retailer. Due to the imperfect production system, the manufacturer produces a certain quantity of defective items with the perfect products. The manufacturer inspects all the products immediately after production and sells the ideal quality items to the retailer. To entice the retailer to purchase more products, the manufacturer offers the retailer a trade-credit policy so that the retailer can get a chance to settle his account before the payment for the products. We have developed a cost function of this model. Numerical examples have been presented to clarify the applicability of this model and the sensitivity analysis with respect to different parameters involved with the model has been performed to study the effect of the parameter change on the decision variables.

A supply chain model under return policy considering refurbishment, learning effect and inspection error

Abstract: This article presents a three-echelon supply chain model consisting of a supplier, manufacturer, and a retailer, considering the return contract between the manufacturer and the retailer. Here, the manufacturer has two adjacent production units - the main production unit and a refurbishment unit. The main production unit of the manufacturer is imperfect, which produces an admixture of perfect and defective items. He inspects all the products immediately after production and sells good quality items to the retailer. The retailer receives a proportion of faulty products from him due to his erroneous inspection process, which he returns after inspection. The manufacturer sends all the defective products received from the retailer and the main production unit to the refurbishment unit for reworking. Moreover, the learning effect of the employees on the production cost is considered. Under these circumstances, the cost functions of each of the supply chain players have been derived. Finally, the applicability of the proposed model has been shown using a numerical example. The sensitivity analysis has been presented to study the effect of the parameters on the optimum decision variables.

A Multi-Storehouse Supply Chain Considering Systems’ Reliability and Free Shipping

Abstract: This paper aims to frame a two-player supply chain model with a production system's reliability influenced products’ defection rate. Upon generating and inspecting the products, the producer reworks the defectives and sells the perfect and reworked items to a retailer providing him free products' delivery. The retailer stores both types of commodities in the respective showrooms of finite capacities and keeps the excess conforming products in a leased warehouse. Eventually, the formulation of these two partners' profit functions performed, and a numerical illustration demonstrates this model's applicability. Results shows, hiring a storehouse is profitable for the retailer and the deterioration of the production system’s reliability impacts adversely on the manufacturer's profit.

Cost Minimization Policy for Manufacturer in a Supply Chain Management System with Two Rates of Production under Inflationary Condition

Abstract: This article presents a production inventory model for deteriorating goods with two different rates of production. Here, the manufacturer starts manufacturing the items at a lower rate to avoid a huge investment at the initial stage and to reduce the holding cost of the products. But, when the stock level reaches a prefixed level, he switches on to a higher rate of production to avoid shortage caused by an insufficient stock of the items. Moreover, the impact of inflation and the time value of money on the manufacturing system’s cost is considered here, which harm any business by reducing the value of an investment with time. We determined the optimum production times at both the low and high production rates by minimizing the total cost of the system. Numerical examples presented here illustrate the applicability of this proposed model and sensitivity analysis studies the effect of changes in the parameters associated with this model on the optimal decision variables. This numerical experiment was done in LINGO 18.0 software. Results show the production strategy taken by the manufacturer helpful in reducing his total cost.

Two-Echelon Supply Chain Model in an Imperfect Production with Stochastic Demand Considering the Rework of the Defective Items.

Abstract: This article presents a two-echelon supply chain model consisting of a single manufacturer and a single retailer. Here, the manufacturer’s production system is imperfect and produces a certain proportion of defective products with the perfect products. The manufacturer starts reworking the defective products at the end of the main production. It is assumed that the customer’s demand to the retailer is stochastic in nature and the retailer’s demand to the manufacturer depends on the customer’s demand for the product to the retailer. Finally, we have derived a cost function of the system. Numerical examples have been presented to clarify the applicability of the proposed model and sensitivity analysis has been presented to study the effect of the change of the parameters on the optimal decision variables.

A Multi-Storehouse Supply Chain Considering Systems’ Reliability and Free Shipping

Abstract: This paper aims to frame a two-player supply chain model with a production system's reliability influenced products’ defection rate. Upon generating and inspecting the products, the producer reworks the defectives and sells the perfect and reworked items to a retailer providing him free products' delivery. The retailer stores both types of commodities in the respective showrooms of finite capacities and keeps the excess conforming products in a leased warehouse. Eventually, the formulation of these two partners' profit functions performed, and a numerical illustration demonstrates this model's applicability. Results shows, hiring a storehouse is profitable for the retailer and the deterioration of the production system’s reliability impacts adversely on the manufacturer's profit.

A combined continuous-time Markov chain and queueing-inventory model for a blood transfusion network considering ABO/Rh substitution priority and unreliable screening laboratory

Abstract: The uncertain nature of blood supply and demand in a blood supply chain network (BSCN) makes it impossible completely meet the blood demands on time. That’s why there is a vital need to develop a comprehensive model for optimally managing blood networks considering all challenges they face with. Although many researches have studied blood inventory management (BIM) in BSCNs, there is still a lack of models simultaneously considering blood inventory levels in hospital blood banks (HBBs) and blood centers (BCs) as a stochastic process. Also, most models have not evaluated the impact of false positive (FP) and false negative (FN) errors in the screening laboratories (SLs) of BCs. Moreover, no study has modeled the HBB demands as a queueing-inventory model with multiple blood types according to ABO/Rh substitution priority. To fill these gaps, this paper develops a two-echelon blood bank network considering ABO/Rh factors and substitution priority in which inventory levels of all red blood cell (RBC) types in an HBB and BC are simultaneously modeled as eight dependent continuous-time Markov chains (CTMCs). An unobservable M/M/m queueing-inventory system with infected RBCs and (r,Q) policy in the HBB is proposed. The blood requests arrive at the requests queueing system in the HBB, and after processing and departing from the queue, they leave the HBB with exactly-one RBC unit with the same ABO and Rh (Rhesus) groups or compatible with other types of RBC. Lost sales occur if all possible types of RBC for transfusion are unavailable. HBB continuously checks each RBC type's inventory level and places an order to the BC once the inventory level of each one of them reaches a predetermined reorder point. Due to transfusion-transmissible infections (TTIs), an SL conducts a 100 % quality-assured screening in the BC modeled as an M/M/m queueing system. Due to unreliable inspectors, FP and FN errors are considered in the SL. The stationary distribution of the number of requests at the HBB, the number of RBCs in the SL, and joint stationary distributions of inventory level of all RBC types in the HBB and BC are derived. Afterward, each RBC type's waiting-time distribution in the HBB is obtained. Some performance measures and the long-run total cost are extended, and a mixed integer nonlinear programming model (MINLP) is presented. Then, we propose the grasshopper optimization algorithm (GOA) to solve the complicated model. Also, this model is implemented in a case study in Tehran. Results show RBCs types O+ and A+ have the most lost sales, and the management should absorb more donors with these blood groups. Afterward, an approximation method to deal with multiple HBBs is suggested. Finally, several remarkable managerial and practical implications are presented.

Coordination and competition in a duopoly with two-manufacturer and two-retailer with wholesale-price contract and demand uncertainty

Abstract: This study analyzes a supply chain involving two competing manufacturers that sell their products through two common competing retailers. The manufacturers’ products are the same, yet come out with different brands in the market. The retailers face stochastic demand where demand is the decreasing function of price with an additive uncertain part. Manufacturers compete on supplying orders where retailers compete on selling price. Each manufacturer sets a wholesale price contract with retailers similarly. In this study, the supply chain coordination with the wholesale price contract under competition and demand uncertainty is examined. The analytical results show that, under coordinated conditions, manufacturers do not obtain any positive profit and, consequently, the retailers intend to increase wholesale prices. On the other hand, manufacturers can increase wholesale prices until the retailers’ profit becomes zero. Hence, with a numerical study for actual cases, it is found that changing demand sensitivity and competition intensity affects the optimal ordering and pricing decisions. Moreover, increasing competition sensitivity increases supply chains’ efficiency, stocking level, and selling price. The concluding remarks show that further investigations are required for exploring the possibility of coordination under competition by other contractual mechanisms.