scholarly journals System Dynamics Model for VMI&TPL Integrated Supply Chains

2013 ◽  
Vol 2013 ◽  
pp. 1-17 ◽  
Author(s):  
Guo Li ◽  
Xiaojing Wang ◽  
Zhaohua Wang
Keyword(s):  
Supply Chain ◽  
Risk Sharing ◽  
Operation Mode ◽  
Bullwhip Effect ◽  
Service Level ◽  
Inventory Level ◽  
Dynamics Model ◽  
Integrated Operation ◽  
Integrated Supply Chain

This paper establishes VMI-APIOBPCS II model by extending VMI-APIOBPCS model from serial supply chain to distribution supply chain. Then TPL is introduced to this VMI distribution supply chain, and operational framework and process of VMI&TPL integrated supply chain are analyzed deeply. On this basis VMI-APIOBPCS II model is then changed to VMI&TPL-APIOBPCS model and VMI&TPL integrated operation mode is simulated. Finally, compared with VMI-APIOBPCS model, the TPL’s important role of goods consolidation and risk sharing in VMI&TPL integrated supply chain is analyzed in detail from the aspects of bullwhip effect, inventory level, service level, and so on.

Comparative multi criteria analysis and dependent optimisation through integrated supply chain

2014 ◽  
Vol 63 (8) ◽  
pp. 1046-1069 ◽  
Author(s):  
Sanjay Sharma ◽  
Akshat Sisodia
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Service Level ◽  
Inventory Level ◽  
Inventory Policies ◽  
Inventory Cost ◽  
Content Type ◽  
Customer Service Level ◽  
Integrated Supply Chain ◽  
Different Levels

Purpose – The purpose of this paper is to compare various inventory policies and their effect on various performance metrics at different levels of a multi stage supply chain. Later the model is integrated to include optimization of entire supply chain through implementation of collaborative supply chain model. Design/methodology/approach – Alternative inventory policies have been developed at different echelons and a comparison reflecting the usability on various factors such as inventory level, inventory cost and service level is presented so as to support the decision-making process. Various inventory policies such as economic order quantity, periodic ordering (T, M) and stock to demand have been considered. Along with the basic assumptions; lead time, demand variability, variability in demand during lead time, stock out costs have also been included to make the model more applicable to practical situations. Findings – After the selection of most appropriate inventory policy at each level through a decision matrix, the total cost of operating such a supply chain is calculated along with other parameters such as service level and inventory turns. The approach is of aggregating the optimized value at each echelon referred to as aggregated supply chain in the paper. Then the concept of integrated supply chain is introduced which optimizes the supply chain as a whole, rather than aggregating local optima. The comparison is made between the two approaches that prove the integrated supply chain's superiority. Furthermore, dependent optimization is run as it is not practically possible for each echelon to optimize at the same time. Originality/value – Each echelon is allowed to optimize at a time and other echelons assume corresponding values. This final comparative multi criterion analysis is based on the three factors, i.e. inventory cost, customer service level and inventory turnover with different weights assigned to each factor at different levels of a supply chain. Finally a consolidation of results is made to reflect the overall preference which proves that an integrated supply chain best serves all the parameters combined together.

A PSO Weighted Estimating the Mean Downstream Demand to Mitigate the Bullwhip Effect in a Supply Chain

2011 ◽  
Vol 383-390 ◽  
pp. 4125-4129
Author(s):  
Ling Tzu Tseng
Keyword(s):  
Particle Swarm Optimization ◽  
Supply Chain ◽  
Particle Swarm ◽  
Bullwhip Effect ◽  
Pso Algorithm ◽  
Inventory Level ◽  
Inventory Cost ◽  
Swarm Optimization ◽  
Demand Information ◽  
Batch Ordering

Bullwhip Effect, Particle Swarm Optimization, Supply Chain, Demand Information Abstract. A deformation phenomenon occurring in business activity, called the bullwhip effect which comes from the demand information is not fully shared among the members of a supply chain, conducts the upstream manufacturer to excessively anticipate the demand capacity of the downstream retailer. The manufacturer improperly decides the amount of the products not only to raise the inventory cost on the way of poorly handling the actually downstream demand, but also to lose the chance of business deals due to its backordering. To cope with the bullwhip effect by taking into account the holding and backorder costs, an evolutionary method based on the Particle Swarm Optimization (PSO) algorithm to estimate the critical parameter, mean downstream demand, is proposed and computer validated in this paper such that the estimated inventory level could be close the really batch ordering of the manufacturer.

scholarly journals Analysis of Variance Amplification and Service Level in a Supply Chain with Correlated Demand

2020 ◽  
Vol 12 (16) ◽  
pp. 6470 ◽  
Author(s):  
Ahmed Shaban ◽  
Mohamed A. Shalaby ◽  
Giulio Di Gravio ◽  
Riccardo Patriarca
Keyword(s):  
Supply Chain ◽  
Performance Measures ◽  
Bullwhip Effect ◽  
Service Level ◽  
Operating Conditions ◽  
Supply Chain Performance ◽  
Chain Model ◽  
Ordering Policy ◽  
Smoothing Parameters ◽  
The Impact

The bullwhip effect reflects the variance amplification of demand as they are moving upstream in a supply chain, and leading to the distortion of demand information that hinders supply chain performance sustainability. Extensive research has been undertaken to model, measure, and analyze the bullwhip effect while assuming stationary independent and identically distributed (i.i.d) demand, employing the classical order-up-to (OUT) policy and allowing return orders. On the contrary, correlated demand where a period’s demand is related to previous periods’ demands is evident in several real-life situations, such as demand patterns that exhibit trends or seasonality. This paper assumes correlated demand and aims to investigate the order variance ratio (OVR), net stock amplification ratio (NSA), and average fill rate/service level (AFR). Moreover, the impact of correlated demand on the supply chain performance under various operational parameters, such as lead-time, forecasting parameter, and ordering policy parameters, is analyzed. A simulation modeling approach is adopted to analyze the response of a single-echelon supply chain model that restricts return orders and faces a first order autoregressive demand process AR(1). A generalized order-up-to policy that allows order smoothing through the proper tuning of its smoothing parameters is applied. The characterization results confirm that the correlated demand affects the three performance measures and interacts with the operating conditions. The results also indicate that the generalized OUT inventory policy should be adopted with the correlated demand, as its smoothing parameters can be adapted to utilize the demand characteristics such that OVR and NSA can be reduced without affecting the service level (AFR), implying sustainable supply chain operations. Furthermore, the results of a factorial design have confirmed that the ordering policy parameters and their interactions have the largest impact on the three performance measures. Based on the above characterization, the paper provides management with means to sustain good performance of a supply chain whenever a correlated demand pattern is realized through selecting the control parameters that decrease the bullwhip effect.

Two-Echelon Inventory Stochastic Model of Supply Chain Based on Service Level Constraints

2014 ◽  
Vol 971-973 ◽  
pp. 2448-2451
Author(s):  
Da Li Jiang ◽  
Guang Fu Zhu ◽  
De Li
Keyword(s):  
Supply Chain ◽  
Stochastic Model ◽  
Service Level ◽  
Inventory Model ◽  
Inventory Level ◽  
Effective Algorithm ◽  
Inventory Cost ◽  
Total Inventory

The study on multi-echelon inventory of supply chain is becoming more and more important in E-business era. This paper proposes a two-echelon inventory model with one supplier and several retailers, in which a certain service level has to be satisfied and the goal is to minimize the total inventory cost. In addtion it puts forward an effective algorithm for this model to obtain the optimal replenishment period and inventory level of each supply chain node.

A neoteric approach to geometric shipment policy in an integrated supply chain with setup cost reduction and freight cost using service level constraint

2020 ◽  
Vol 54 (3) ◽  
pp. 653-673
Author(s):  
Selvaraj Hemapriya ◽  
Ramasamy Uthayakumar
Keyword(s):  
Supply Chain ◽  
Cost Reduction ◽  
Transportation Cost ◽  
Service Level ◽  
Setup Cost ◽  
Transportation Modes ◽  
Controllable Lead Time ◽  
Integrated Supply Chain ◽  
The Impact ◽  
Setup Cost Reduction

This paper explores a neoteric approach to geometric shipment policy and concerns the impact of controllable lead time, setup cost reduction, lost sales caused by stock-out and freight cost within an integrated vendor–buyer supply chain configuration using service-level constraint. In particular, the transportation cost is a function of shipping weight, distance and transportation modes. In other words, truckload (TL) and less-than-truckload (LTL) shipments. A heuristic model is developed to minimize the joint expected total cost (JETC), when the mode of transportation is limited to TL and LTL shipments. Numerical examples including the sensitivity analysis with some managerial insights of system parameters is implemented to endorse the outcome of the supply chain models.

scholarly journals A Conceptual Frame Work of Supply Chain Integration for Competitive Advantage

2014 ◽  
Vol 13 (4) ◽  
pp. 63-81
Author(s):  
Venkat Ramesh ◽  
Y Vijaya Kumar ◽  
Sindhu Sindhu
Keyword(s):  
Supply Chain ◽  
Competitive Advantage ◽  
Organizational Performance ◽  
Service Level ◽  
Supply Chain Integration ◽  
Active Management ◽  
Conceptual Frame ◽  
Frame Work ◽  
And Performance ◽  
Integrated Supply Chain

Growth as one of the key preconditions to survive in the market is forcing companies to compete on international markets and at the same time defend domestic market share from international competitors. The result of that is increased complexity of supply chains, pressure to decrease cost and improve service level. To cope with the complexity and increased customer requirements, active management of the supply chain is a prerequisite. As supply chain is a network of three or more entities directly involved in the upstream and downstream flows of products, services, finance and information from a source to a customer, management of it is a complex task. There is significant evidence from literature that the effective implementation of integrated supply chain management (SCM) has the potential to generate significant improvements in the performance of firms. The higher levels of SCM practice can lead to enhanced competitive advantage and improved organizational performance. In order to achieve efficient supply chain integration for the processes or activities; the organizations should recognize and understand all the integration challenges of supply chain. The aim of this paper is to investigate previous research studying the relationship between supply chain integration and performance and understand the importance of supply chain integration for competitive position of organization. Address the challenges encountered in integration of supply chain. Propose a conceptual frame work to reap the potential benefits of effective supply chain integration.

Exploring a Downstream Demand Inference Strategy in a Decentralized Two-Level Supply Chain

2021 ◽  
pp. 1-65
Author(s):  
Youssef Tliche ◽  
Atour Taghipour ◽  
Béatrice Canel-Depitre
Keyword(s):  
Supply Chain ◽  
Mean Squared Error ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Inventory Level ◽  
Squared Error ◽  
Forecasting Method ◽  
Demand Information ◽  
The Mean ◽  
Inference Strategy

A coordination approach for forecast operations, known as downstream demand inference, enables an upstream actor to infer the demand information at his formal downstream actor without the need for information sharing. This approach was validated if the downstream actor uses the simple moving average (SMA) forecasting method. To answer an investigative question through other forecasting methods, the authors use the weighted moving average (WMA) method, whose weights are determined in this work thanks to the Newton's optimization of the upstream average inventory level. Starting from a two-level supply chain, the simulation results confirm the ability of the approach to reduce the mean squared error and the average inventory level, compared to a decentralized approach. However, the bullwhip effect is only improved after a certain threshold of the parameter of the forecasting method. Still within the framework of the investigation, they carry out a comparison study between the adoption of the SMA method and the WMA method. Finally, they generalize their results for a multi-level supply chain.

Revision of the Bullwhip Effect

2011 ◽  
pp. 1381-1387
Author(s):  
David de la Fuente
Keyword(s):  
Supply Chain ◽  
Consumer Demand ◽  
Bullwhip Effect ◽  
Classic Method ◽  
The Sixties

A supply chain is composed of all the stakeholders and processes involved in satisfying consumer demand: wholesaler, retailer, warehousing, transport and so on. A classic method to understand the internal workings of a supply chain is the much-used beer distribution game that came out of MIT during the sixties. In this game, each player takes on the role of one of the members of the chain (consumer, retailer, wholesaler and manufacturer). The aim is for each of them to coordinate their actions in such a way as to satisfy the demands of the upstream member of the chain at the least possible cost. Sterman (1989) provided evidence of an effect that had already been described by Forrester (1961) whereby initial consumer demand is distorted and amplified as it passes along the chain. This increment is known as the Forrester or Bullwhip effect.

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