Three-echelon Supply Chain System Research Articles

Adaptive continuous barrier function-based super-twisting global sliding mode stabilizer for chaotic supply chain systems

Supply chains face various uncertainties due to the dynamic and unstable nature of today's worldwide market. Introducing these uncertainties to both the upstream and downstream elements of supply chains adds complexity and nonlinearity to them. This paper investigates the dynamic behavior of a chaotic three-echelon supply chain system and designs a finite-time global nonlinear super-twisting sliding mode controller based on an adaptive continuous barrier function technique for stabilizing the defined system under external disturbances and model uncertainties. This method dynamically adapts the controller parameters according to the system's current state using parameter adaptation algorithms. The adaptive barrier function is used to ensure the system's stability, while the super-twisting algorithm is used to speed up the convergence rate and robustness of the system. Moreover, the genetic optimization algorithm has been employed to attain the optimal values of parameters, thereby enhancing the performance of the designed controller. Ultimately, the effectiveness of this research's proposed approach has been evaluated through simulation in the MATLAB-Simulink environment and experimental testing using the Baseline Real-Time Speedgoat test platform. These analyses are paramount and helpful for strategic decision-makers because they allow visualization and control of the states/dynamics of the entire supply chain. The internal parameters of the supply chain are used as control parameters, and different significant states are discovered to achieve synchronization.

An optimal strategy for forecasting demand in a three-echelon supply chain system via metaheuristic optimization

An optimal strategy for forecasting demand in a three-echelon supply chain system via metaheuristic optimization

Differential decision of low-carbon supply chain based on market preferences with fairness concerns

<p style='text-indent:20px;'>Under the dual background of energy economy and environmental protection, expanding the optimal decision-making of the low-carbon supply chain is significant to the energy manufacturing industry. This paper discusses the impact of low-carbon preference, price elasticity, and low-carbon research and development investment (LR & DI) on equilibrium decisions of a three-echelon supply chain system under the scenarios of market segments and fairness concerns. Firstly, it is found that the optimal price and yield are positively correlated with the counterparty's demand elasticity coefficient and sensitivity coefficient, and the supply chain profit is better under the decentralized decision of the retailer's fairness concerns. Secondly, there is a positive correlation between each member's interests and the degree of the manufacturer's fairness concern. While considering the retailer, the manufacturer is responsible for the supply chain income loss. Finally, because the optimal pricing and yield are positively correlated with consumers' low-carbon preference and LR & DI, manufacturers may optimize profits by raising LR & DI within a tolerable range. In addition, it is verified that the Stackelberg game optimizes the traditional model by a numerical example, providing theoretical support for decision-making in different scenarios.</p>

Dynamical Investigation, Electronic Circuit Realization and Emulation of a Fractional-Order Chaotic Three-Echelon Supply Chain System

This study is concerned with dynamical investigation, electrical circuit realization, and emulation of a fractional three-echelon supply chain system. In the financial realm, long-term memory effects play important roles. On the other hand, most financial systems are uncertain with unknown nonlinear dynamics. However, most studies on nonlinear supply chains neither consider the fractional calculus nor take advantage of state-of-the-art emulation methods. These issues motivated the current study. A fractional-order chaotic three-echelon supply chain system is studied. At first, the system’s dynamic is studied through Lyapunov exponent and bifurcation diagrams. It is shown that a slight deferent in some parameters of the system can dramatically change the behavior of the system. Then, a real-time analog circuit is designed and implemented to investigate the system’s chaotic behavior. This way, the system’s chaotic attractors are empirically demonstrated. Finally, emulation and interpolation of the fractional-order chaotic system using the Gaussian process have been studied, and its luminous results have been presented.

Fuzzy adaptive control technique for a new fractional-order supply chain system

The current study presents a new fractional-order three-echelon supply chain model. The chaotic behaviour of the proposed model is demonstrated, and after its synchronization is studied. To this end, a new control technique is offered for the proposed fractional-order system. In the design of the controller, it is assumed that all parameters of the model are unknown. Hence, the proposed sliding mode controller is equipped with an adaptive mechanism, which estimates all unknown parameters of the controller. On the basis of the Lyapunov stability theorem and Barbalat’s lemma, the stability of the system is proven. In order to enhance the performance of the proposed controller and prevent the probable chattering phenomenon which could occur due to the discontinuous function in the sliding mode controller, a fuzzy controller is proposed along with the main controller. Not only is the offered controller robust against uncertainties, but also it is able to estimate parameters of the systems and avoids chattering in the system. Finally, the proposed controller’s excellent performance for synchronization of the fractional-order three-echelon supply chain system is demonstrated through numerical results.

Cellular manufacturing design and replenishment strategy in a capacitated supply chain system: A simulation-based analysis

This paper studies the integration of design and control phases in a three-echelon supply chain system of a blood sugar strip manufacturer. The first step is manufacturing system design based on layered Cellular Manufacturing System (CMS) for which a mixed-integer linear programming approach is proposed in order to minimize the required number of cells. The novelty of the proposed model is in incorporating shifts into layered CMS design. In the second step of the design phase inventory parameters in different levels of the supply chain are estimated based on the continuous review, fixed order quantity (Q,r) model. Control phase is triggered by releasing customer order for multiple types of products and includes replenishments in the three echelons of the supply chain and scheduling in the layered CMS. In order to evaluate the system cost, the capacitated supply chain system is simulated in Simio software package. In the first phase of the simulation, cost components are obtained based on the inventory parameters estimated in the design phase. Next, simulation based on OptQuest feature is performed to improve total cost and estimate the inventory parameters and expected cell utilization. Comparing system cost and the parameters from the design phase to the results of the OptQuest approach evaluates the manufacturing system design and the replenishment policy proposed in the design phase. Sensitivity analysis is performed to analyze the effect of shortage penalty and inventory carrying rate on the total cost of the system. Finally, statistical analysis result indicate Re-Order Point (ROP) values obtained by the OptQuest have significantly changed compared with ROP values estimated in the design phase; however, the same conclusion is not applicable for order quantity values.

Adaptive Synchronization of Supply Chain System using Sliding Mode Control

This paper addresses a chaos synchronisation problem in a three-echelon supply chain system. A parameter adaptation law is designed to deal with the influence of unknown parameters and system perturbations for the supply chain system. Based on Lyapunov stability theory, the sliding mode control synthesis with parameter update law provides its ability on driving the trajectories of supply chain system to the master system. The simulation results show that the adaptive sliding mode controller enables to synchronise the supply chain system with master system asymptotically and how information and materials flow between business entities and processes. The active supply chain management using control theory makes business organisation more flexible, and all participants in business enterprises can certainly adjust to new market trends and easily cope with market instabilities.

A heuristic method for location-inventory-routing problem in a three-echelon supply chain system

Abstract Location-inventory-routing problem belongs to the class of NP-hard problems. It needs a heuristic method to solve the problem in large scales so it can be applied in a real system case. This paper develops a heuristic method for location-inventory-routing problem in a three-echelon supply chain system where inventory decisions are made in the three involved entities. The involved entities in the system are single supplier, multi depots, and multi retailers. The demand of the retailers is probabilistic, single product, and following a normal distribution. The heuristic method consists of two stages, which are constructive stage and improvement stage. At the improvement stage, there are three phases developed to improve solution iteratively. The phases are location phase, inventory phase, and routing phase. SA (simulated annealing) is used at the improvement stage to improve the solution. The heuristic method is evaluated using instances and the solutions are compared to the MINLP (mixed integer nonlinear programming) model. Average gap between the heuristic method and the MINLP model is 0.55% in terms of total cost. The proposed heuristic is applied in a real system case which is food supply chain system of DKI Jakarta to design a new supply chain system that can increase availability. The new design can increase the availability from 76% to 95%.

Coordinating a three-echelon fresh agricultural products supply chain considering freshness-keeping effort with asymmetric information

This paper studies the coordination problem of a three-echelon supply chain system consisting of one supplier, third-party logistics service providers (TPLSP) and one retailer that provides seasonal fresh agricultural products to customers. The market demand for the retailer is assumed to be influenced by the retail price, the product's freshness and other random variables. Both quantity and quality losses are viewed as endogenous variables of the freshness-keeping effort, which is decided by the TPLSP. Dynamic game models for both the decentralized decision mode and the centralized decision mode are developed, and asymmetric demand information is considered in the decentralized decision mode. The analysis shows that decentralized decision making could result in the distortion of the order quantity and selling price and could ultimately result in a loss of supply chain profit. The TPLSP is motivated to exaggerate the demand, which could seriously damage the supplier's interests. Based on an analysis of the major influencing factors in the supply chain system, a coordination contract based on cost and revenue sharing (RS) is designed for the two transaction processes in the three-echelon supply chain system. We illustrate the proposed models with a numerical study and conduct a sensitivity analysis of some of the key parameters in the models. It is proven that with the designed contract, the sales volume can be significantly expanded, all the supply chain members can benefit from Pareto improvement, and both the retailer and the TPLSP have no incentive to exaggerate the market demand.

Coordinating a multi-echelon supply chain under production disruption and price-sensitive stochastic demand

This paper considers a three-echelon supply chain system with one raw-material supplier, one manufacturer and one retailer in which both the manufacturer and the raw-material supplier are exposed to the risk of production disruptions. The market demand is assumed to be uncertain but sensitive to the retail price. The objective is to determine the optimal lot sizes of the supplier and the manufacturer, and the selling price of the retailer when the wholesale prices of the upstream entities are prescribed and the retailer's order quantity is chosen before the actual demand is realized. As the benchmark case, the expected total profit of the centralized channel is maximized. The decentralized supply chain is coordinated under pairwise and spanning revenue sharing mechanisms. Numerical study shows that disruptions have remarkable impact on supply chain decisions.

Improving service rate for a tree-type three-echelon supply chain system with backorders at retailer's level

This research deals with a distributive or tree-type three-echelon production-distribution supply chain system with allowable backorder. Allowing backorder could reduce the total of a production-distribution system by reducing holding cost due to the lower average inventory, even though backorders carry some cost and lower a company's goodwill. The main purpose of this research is to develop replenishment policies for a tree-type three-echelon supply chain system with allowable backorder. The supply chain network is composed of a producer, multiple distributors, and multiple retailers. This research attempts to improve service rate by reducing the backorder at the retailer level. The distributors are allowed to ship product to retailer quicker in order to reduce backorder. The total cost function of the proposed model is developed. Since the total cost function contains some integer variables, differentiating the function with respect to the variables could not be used as a basis to solve for the optimal solutions. A branching search process was utilized to find the integer solutions. A numerical example is used to demonstrate improvement in service rate and total cost using the model.

Research on TPL Service Level and Pricing Models in Supply Chain Coordination and Benefits Allocation

Research on the method to strengthen the cooperation among members to achieve win-win result is an important subject in SCM. Nevertheless, most studies to date on supply chain pricing have only assumed that the market demand is only influenced by retail price but not by logistics service level. That is why our work is concerned with logistics service and product pricing strategies in supply chain consisting of the manufacturer, the retailer and the TPL provider. For three-echelon supply chain system with TPL service level, use game theory to analyze its pricing, production, service levels and profit allocation. Three different models are discussed which are based on Stackelberg games and cooperative game. We find that the whole supply chain profit brought by collaborative decision-making is much higher than it independent decision-making brings based on the research. And it can increase the whole profit through reasonable setting of allocation proportion of profit. The study proposes multiple effective distribution methods of supply chain profit and takes an example to perform empirical analysis on the results to proof effectiveness.

Design and Distribution Strategies for a Three-Echelon Supply Chain System

Design and Distribution Strategies for a Three-Echelon Supply Chain System

Production control and supplier selection under demand disruptions

This paper investigates the effects of demand disruptions on production control and supplier selection in a three-echelon supply chain system. The customer demand is modeled as a jump-diffusion process in a continuous-time setting. A two-number production-inventory policy is implemented in the production control model for the manufacturer. The objective is to minimize the long-term average total cost consisting of backlog cost, holding cost, switching cost, and ordering cost. The simulated annealing method is applied to search the optimal critical switching values. Furthermore, an improved analytical hierarchy process (AHP) is proposed to select the best supplier, based on quantitative factors such as the optimal long-term total cost obtained through the simulated annealing method under demand disruptions and qualitative factors such as quality and service. Numerical studies are conducted to demonstrate the effects of demand disruptions in the face of various risk scenarios. Managerial insights from simulation results are provided as well. Our approaches can be implemented as the “stress test” for companies in front of various supply chain disruption scenarios.

Information sharing and profit allotment based on supply chain cooperation

To maximize customer value created by a supply chain system as a whole, one of the key issues in supply chain management is how to have profit and benefit properly shared between partners in an effective manner of the supply chain integration. In this regard, information sharing between partners plays a rather important role in business process and management integration of the supply chain. The paper focuses on analyzing the value created from information sharing by decreasing inventory level and on investigating the collaborative mechanism of providing incentive to retailer by upstream partner via sharing profit gained information sharing in the context of three-echelon supply chain system. The issue of dealing with the interest conflict between the supply chain as a whole and individual partners is addressed based on information sharing analysis by means of cooperative game approach, a graphic model with three-dimensions is developed to depict the possible cooperative solutions of profit allotment between partners, and a problem solving method addressing how the profit allotment between partners can effectively motivate the partners to be cooperative with each other is presented as well.

Incorporating lateral transfers of vehicles and inventory into an integrated replenishment and routing plan for a three-echelon supply chain

This paper focuses on developing an integrated replenishment and routing plan that takes into account lateral transfers of both vehicles and inventory for a three-echelon supply chain system including a single plant, multiple distribution centers and multiple retailers. A mixed integer programming model to the overall system is formulated first, and then an optimization-based heuristic consisting of three major components is proposed. The purpose of the first component is to assign retailers to distribution centers, and determine routing schedules for each distribution center. And the remaining two components are corresponding to two smaller optimization models – a variant of the classical transportation problem modeled for determining vehicle transfer between distribution centers, and a variant of the conventional minimum cost network flow problem modeled for determining inventory replenishment and transfer. Experimental results reveal that the proposed algorithm is rather computational effectiveness, and the pooling strategy that considers both vehicles and inventory transfers is a worthy option in designing supply chain operations.

Hierarchical supply chain planning architecture for integrated analysis of stability and performance

In this paper, a novel architecture that allows a multi-scale federation of interwoven simulations and decision models to support integrated analysis of stability and performance in hierarchical production planning for supply chain networks is proposed. The proposed scheme is divided into four stages: plan stability analysis, plan optimisation, schedule optimisation and concurrent decision evaluation. The plans are more robust against future disturbances and more feasible for implementation than those from the conventional methods. Detailed functional and process models of the proposed system are specified using formal IDEF tools. The proposed approach is demonstrated using a realistic three-echelon supply chain system.