Controllable Lead Time Research Articles

Periodic inventory model with controllable lead time and back order discount for decaying items

Periodic inventory model with controllable lead time and back order discount for decaying items

Safety stock management in a two-stage supply chain with controllable lead time and batch shipments: A technical note

Safety stock management in a two-stage supply chain with controllable lead time and batch shipments: A technical note

Optimizing production-inventory replenishment and lead time decisions under a fill rate constraint in a two-echelon sustainable supply chain with quality issues

This paper considers a single vendor-single buyer coordinated supply chain under stochastic demand. GHG emissions arise from the vendor's production process. A carbon tax and penalties for exceeding multiple emissions limits are considered. A random number of defectives characterises the batch received by the buyer, who performs an inspection activity. Setup and transportation times are controllable through a capital investment, whose outcome is uncertain. An optimisation problem is formulated under the minimax distribution-free approach. The objective is to find the production-inventory replenishment policy and the length of setup and transportation times that minimise the long-run expected total system cost rate considering a fill rate constraint. Several properties of the cost function are demonstrated, and an optimisation method is developed. Finally, numerical experiments are carried out to draw insights on the effect of the model parameters, including different legislation schemes concerning GHG emissions, on the optimal system performance. The novelty of the paper consists into investigating the effect of a controllable lead time on coordinated supply chain decisions in presence of GHG emissions and quality issues, in a stochastic environment. A major finding is that controlling lead time enhances both the overall cost efficiency and the environmental sustainability of the system.

Coordination supply chain management in flexible production system and service level constraint: A Nash bargaining model

The interest conflicts significantly impact the supply chain (SC) functioning. Hence, it is imperative to establish a suitable coordination mechanism to eliminate the SC conflicts. This paper focuses on coordination in a two-member SC with a flexible production system under buyer’s service level constraint and stochastic demand. The study adopts a multiple inspection policy and utilizes a discrete investment function for setup cost reductions. Bargaining is the fundamental subject of any business presently within the SC players to profit from a cooperative centralized model. The authors develop three SC models, a buyer Stackelberg model, a centralized decision model, and a Nash bargaining model. The cost allocation ratio with different bargaining powers gives a better representation of the cost-sharing scenario—Study attempt to associate bargaining with centralization and decentralization. Discrete investment helps to reduce the total cost further in the presence of a cost allocation ratio. A controllable lead time is used to relate the cost allocation ratio within the SC model. The model is solved analytically by a game-theoretic approach. Numerical example and sensitivity analysis are included to validate the proposed models. The results show the centralized cooperative model based on Nash bargaining significantly improves the overall profit of the SC. Therefore, when vendor and buyer cooperate to form a centralized SC, the SC can be optimized to achieve the dual objectives of increasing profit and improving customers’ service.

Research on Inventory Simulation of Pulse Supply Chain Based on Controllable Lead Time

In the e-commerce environment, how supply chain enterprises respond to surge demands has become an urgent issue to address. This article takes into consideration the overall interests of the supply chain system, aiming to maximize the supply chain profit. By applying system dynamics theory, an in-depth analysis is conducted on a two-tier supply chain consisting of a single manufacturer and a single retailer with controllable lead times. A system dynamics model is constructed using Vensim simulation software as the modeling platform, and simulation analyses are performed for both single and multiple surge demands. The findings reveal that in both single and multiple surge demand scenarios, implementing a controllable retailer lead time strategy leads to higher profits compared to normal lead time and random lead time strategies. Moreover, as the lead time is compressed, the profit exhibits an increasing-to-decreasing trend. Additionally, when both the manufacturer and retailer lead times are controllable, the profit of the entire supply chain surpasses that of the normal lead time and random lead time strategies.

Two-echelon production inventory model with imperfect quality items with ordering cost reduction depending on controllable lead time

Two-echelon production inventory model with imperfect quality items with ordering cost reduction depending on controllable lead time

Intelligent servicing strategy for an online-to-offline (O2O) supply chain under demand variability and controllable lead time

With the advancement of technologies, industries tries to adopt the advantages of the technology. Customers are busy in their daily life, and the online platform is the best option for retail, whereas traditional customers still prefer to visit the retail shop. Few customers choose the product online but buy it offline or vice-versa. Owing to all those circumstances, current study focuses on an intelligent dual channel (online-to-offline) strategy in industry to arrange the optimal services for customers. The selling price of the product vary with different channel, which helps to determine the demand of product for entire supply chain. Two important factors, backorder and lead-time are examined precisely through marginal value which helps to arrange optimal service and calculate the exact profit. The profit for a centralized and decentralized case are computed for both the players. Some propositions are developed to prove the global optimality. Numerical results prove that a centralized case provides 7.77% better profit than a decentralized case due to bonding between the players.

Impact of carbon emission reduction on supply chain model with manufacturing decisions and dynamic lead time under uncertain demand

Consignment stock policy plays a crucial role in stock management to accomplish more significant benefits for supply chain players. Accordingly, in this research, we developed an inventory model based on the vendor managed inventory and consignment stock agreement by delivering a single item from the single vendor to a single buyer under controllable lead time. Manufacturing industries are a major source of worldwide greenhouse gas emissions. Consumption of larger energy through non-renewable sources increases the use of fossils and coal. Though, this produces more waste and has a negative impact on the environment. In contrast to earlier research, logarithmic investment is employed to control the amount of carbon generated throughout the manufacturing process. The demand rate is treated as a pentagonal fuzzy number to account for the uncertainty. The primary goal of this study is to maximize gross profit with various realistic factors and reduce carbon emissions from the production process. Five numerical experiments, comparison and sensitivity analysis are performed to validate the proposed model. Finally, the benefits of variable pricing and investing in carbon reduction will assist industry managers in effectively managing pricing and inventory strategies to adopt a sustainable supply chain in an uncertain environment.

Optimization on dual-channel supply chain model with pricing decision and trapezoidal fuzzy demand under a controllable lead time

This paper considers a dual-channel supply chain with one vendor and multiple buyers in which (1) one channel is an offline channel where standard products are produced and shipped to the buyers and (2) the second channel is an online channel with the flow of customized products between the vendor and the online buyers/consumers. The first channel follows a vendor managed inventory with consignment stock (VMI-CS) agreement between the vendor and buyers. The supply lead time between the vendor and the buyer is considered controllable, at a cost. Two models are analyzed: (1) in the first model, the standard and customized product’s demand rate is assumed to be price and lead time-sensitive, and (2) in the second model, the demands are uncertain or ambiguous and are treated as a trapezoidal fuzzy number. It is reasonably complex to obtain analytical solutions. Hence, two algorithms are proposed to obtain the numerical solution with the objective of maximizing total profit. Numerical examples, sensitivity analysis, and managerial insights are given to test the model. Finally, conclusions and directions for future research are provided.

A sustainable inventory model for setup and ordering cost reduction under a controllable lead time

A sustainable inventory model for setup and ordering cost reduction under a controllable lead time

A sustainable supply chain model with two inspection errors and carbon emissions under uncertain demand

This study analyzes a two-level sustainable supply chain model using the meta-heuristic evolutionary algorithm. Defective items are exposed due to malfunctions in the equipment during the manufacturing process. The buyer undergoes a quality inspection process to identify defective products. When inspecting the product quality, the quality checker falsely certifies the good quality item as defective or defective item as non-defective. Moreover, in such an environment, there may be uncertainty in product demand. Therefore, this paper analyzes the ambiguous supply chain model under controllable lead time with two types of inspection errors. Furthermore, in this paper, the demand for the product is addressed as a pentagonal fuzzy number and the defuzzification process follows a graded mean integration method. In addition, energy consumption for various factors and carbon emission are incorporated. The objective of this research is to examine the best optimal solutions via a genetic algorithm with the minimum expected total cost of the supply chain under uncertain demand. In order to validate the proposed model, two numerical examples and their discussion are included. At last, sensitivity analysis, managerial insights, conclusion and future directions are given.

Managing a sustainable integrated inventory model for imperfect production process with type one and type two errors

Unlike previous research, this study develops an integrated inventory model for controllable lead time with defective items, errors in inspection, and variable lead time considering sustainability. The research investigates the effect of controlling lead time and capital investment in the setup cost. We assume that the buyer receives a lot size that may contain some defective items with a known defective probability. The buyer’s inspector conducts a 100% quality inspection and may incorrectly classify a non-defective item as a defective item (type one (I) error) or incorrectly classify a defective item as a non-defective item (type two (II) error). The mathematical inventory model considering carbon emission cost is developed, and the solution procedure is designed using the heuristic algorithm to derive the optimal or near optimal solution. Finally, numerical examples and sensitivity analysis are given to illustrate the results. The results show that the defective rate, and type I type II inspection errors, have a significant impact on the shipment lot. This leads to the changes in the total cost, lead time, and the carbon emissions. Our study provides cost savings of 4.39% and carbon emission savings of 28.44%.Graphic abstract

A single-consignor multi-consignee multi-item model with permissible payment delay, delayed shipment and variable lead time under consignment stock policy

This article proposes a two-level fuzzy supply chain inventory model, in which a single consignor delivers multiple items to the multiple consignees with the consignment stock agreement. The lead time is incorporated into the model and is considered a variable for obtaining optimal replenishment decisions. In addition, crashing cost is employed to reduce the lead time duration. This article investigates four different cases under controllable lead time to analyze the best strategy, focusing on two delays such as delay-in-payments and delay-in-shipment. In all four cases, all associated inventory costs are treated as a trapezoidal fuzzy number, and a signed distance method is employed to defuzzify the fuzzy inventory cost. An efficient optimization technique is adopted to find the optimal solution for the supply chain. Four numerical experiments are conducted to illustrate the four cases. Any one of these experimental results will provide the best solution for the ideal performance of the business under controllable lead time in the consignment stock policy. Finally, the managerial insights, conclusion and future direction of this model are provided.

Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management

The concept of controllable lead time and variance is critical issues for the smart supply chain management. This study concerns about variable lead time and variance under controllable production rate and advertise-dependent demand. Managers of any supply chain always improve their performance by reducing lead time and its variance. This paper explores and quantifies these benefits of such lead time reduction for commonly used lot size quantity, production rate, safety factor, reorder point, advertisement cost, vendor’s setup cost. Instead of expected total cost equations, this study provides an exact total cost equation built on an inherent relationship between on-hand inventory and backorder. The marginal value analysis on lead time and its variance achieve more accurate results. The analytical results show that the total supply chain cost is a convex function of both lead time and variance. In other words, the cost savings on both lead time and its variance reduction decrease when lead time becomes larger. Two continuous investments are implied to reduce setup costs and improve the reliability of the production process. The expected backorder and inventory for the buyer uniformly distributed throughout reorder point. Moreover, a smart production process is developed under stochastic demand and flexible production rates. The global optimality of the cost function and decision variables are validated through classical optimization. The numerical examples confirm analytical results and sensitivity analysis is provided for different parameters. Some special cases along with graphical representations are given to validate the model.

A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand

Every industry always tries to provide the best service to its consumers. To provide better service to the consumer and optimize profit, a sustainable online-to-offline retailing strategy is proposed in this current study. Both online and offline systems are considered here, i.e., to provide the best service, the industry sells its products online and offline. Due to the consideration of online and offline systems, the selling price of the products is also different for different modes, and the demand for a particular product is the combined demand of online demand and offline demand, which depend on the selling price of the product. Moreover, the exact lead time and exact backorder are calculated to obtain the system’s exact cost or profit, which directly improves the system’s service. Different investments are incorporated to optimize the total system profit. A distribution-free approach is utilized to solve this model. Numerical examples are provided to prove the applicability of the model in reality. Sensitivity analysis is performed based on critical parameters. Special cases and graphical representations also prove the global optimality of the current study.

A Sustainable Inventory Model for Setup and Ordering Cost Reduction under a Controllable Lead Time

A Sustainable Inventory Model for Setup and Ordering Cost Reduction under a Controllable Lead Time

Optimal ordering policy in a two-echelon supply chain model with variable backorder and demand uncertainty

The paper investigates a two-echelon production-delivery supply chain model for products with stochastic demand and backorder-lost sales mixture under trade-credit financing. The manufacturer delivers the retailer’s order quantity in a number of equal-sized shipments. The replenishment lead-time is such that it can be crashed to a minimum duration at an additional cost that can be treated as an investment. Shortages in the retailer’s inventory are allowed to occur and are partially backlogged with a backlogging rate dependent on customer’s waiting time. Moreover, the manufacturer offers the retailer a credit period which is less than the reorder interval. The model is formulated to find the optimal solutions for order quantity, safety factor, lead time, and the number of shipments from the manufacturer to the retailer in light of both distribution-free and known distribution functions. Two solution algorithms are provided to obtain the optimal decisions for the integrated system. The effects of controllable lead time, backorder rate and trade-credit financing on optimal decisions are illustrated through numerical examples.

An integrated vendor–buyer supply chain model for backorder price discount and price-dependent demand using service level constraints and carbon emission cost

This paper derives a single-vendor single-buyer supply chain model with setup cost reduction, controllable lead time and backorder price discounts using service level constraints. The customer's demand is assumed to be selling-price dependent and the lead time demand follows a normal distribution. This integrated model is used to optimise the total number of shipments, order quantity, safety factor, setup cost and backorder price discount. An algorithm is developed to obtain the numerical results and to demonstrate the applications and performance of the proposed methodology.

A periodic review policy for a coordinated single vendor-multiple buyers supply chain with controllable lead time and distribution-free approach

In this paper, we study a single vendor-multiple buyer integrated inventory model with controllable lead time and backorders-lost sales mixture. Each buyer adopts a periodic review policy in which the review period is an integer fraction of the production cycle time of the vendor. To reflect the practical circumstance characterized by the lack of complete information about the demand distribution, we assume that only the first two moments of the demand during the protection interval are known. The long-run expected total cost per time unit is derived, which includes stockout costs. The problem is to determine the length of the inventory cycle of the vendor, the produce-up-to level for the vendor, the replenishment policy of each buyer, and the length of lead times that minimize the cost function under the minimax distribution-free approach. Two alternative heuristics are proposed. Numerical experiments have been carried out to investigate the performance of the heuristics and to study the sensitivity of the model.

A novel approach to safety stock management in an integrated supply chain with controllable lead time and ordering cost reduction using present value

This paper presents a novel approach to safety stock management and investigates the impact of lead time reduction within an integrated vendor–buyer supply chain framework using present value where lead time and ordering cost reductions act dependently. In particular, the cost of the safety stock is determined by adopting a logistic approximation to the standard normal cumulative distribution. The service level is formulated in relation to the dimension of the single shipment, to the average demand of the buyer and to the number of admissible stockouts. We first discuss the case where the lead time and ordering cost reductions with linear function, and then consider the logarithmic functional relationship. Numerical examples including the sensitivity analysis with some managerial insights of system parameters is provided to validate the results of the supply chain models. The main contribution of this paper is introducing various types of ordering cost reduction in Bragliaet al.(Appl. Stoc. Mod. Bus. Ind.32(2016) 99–112) by handling a new approach.