Integrated Supply Chain Network Design Research Articles

Integrated supply chain network design and superstructure optimization problem: A case study of microalgae biofuel supply chain

In recent years, several strategies have been developed and adopted in a bid to manage the biofuel supply chain. In this paper, a two-stage optimization model is proposed for integrated microalgae biofuel supply chain network design and superstructure optimization problems. In the first stage, the design of the carbon capture, utilization, and storage (CCUS) network is taken into account. A robust mixed integer linear programming (RMILP) model is proposed to optimize the strategic CCUS decisions, including the simultaneous selection of emission sources, capture facilitates, Carbon Dioxide (CO2) pipelines, intermediate transportation sites and storage sites, or microalgae cultivation sites. The second stage is dedicated to biorefinery superstructure optimization in order to determine the optimal/promising biorefinery configurations. The presented model is able to handle the inherent uncertainty of critical input parameters. Moreover, the results show that biodiesel production cost cannot compete with current diesel price, but it can be reduced significantly by improving biomass productivity.

A sustainable uncertain integrated supply chain network design and assembly line balancing problem with U-shaped assembly lines and multi-mode demand

A sustainable uncertain integrated supply chain network design and assembly line balancing problem with U-shaped assembly lines and multi-mode demand

A joint model of location, inventory and third-party logistics provider in supply chain network design

Integrated supply chain network design plays an increasingly important role in improving the operational efficiency of a company. This paper studies a novel joint supply chain network model that integrates location, inventory and third-party logistics provider decisions for consideration in a three-level supply chain involving manufacturers, distribution centers (DCs), and retailers. Different from traditional location-inventory problems, the proposed model not only determines the locations of manufacturers and DCs, and how to serve DCs and retailers by manufacturers and DCs, but also chooses potential third-party logistics providers to serve DCs and retailers. The goal is to design an efficient supply chain system to reduce the overall cost including facility cost, inventory cost, and transportation cost to meet the demands of retailers. A nonlinear integer programming model based on multigraph is proposed. To deal with the complex nonlinear terms, we reformulate a mixed-integer nonlinear programming model. Moreover, to deal with the difficulties caused by multigraph, a method based on the generalized Benders decomposition (GBD) is developed. Computational results clearly show the effectiveness of the proposed model and the GBD method. Comparative analysis shows the potential benefits of integrating the third-party logistics provider decisions into the location-inventory model.

A Capacitated Location-Inventory Model with Demand Selection

In this paper, we consider an integrated supply chain network design problem, which incorporates inventory and pricing decisions into the capacitated facility location model. We assume that each warehouse has a capacity limitation that limits the average demand flowing through the warehouse and that the supplier can choose whether to satisfy each potential retailer’s demand. We formulate the problem as a nonlinear integer programming model and solve the model via a Lagrangian relaxation based approach. We develop an efficient algorithm to solve the subproblem that arises from the Lagrangian relaxation procedure. Finally, we conduct extensive computational experiments to test the performance of the algorithms proposed in this paper and provide the managerial insights based on the computational results.

Type-II Fuzzy Multi-Product, Multi-Level, Multi-Period Location–Allocation, Production–Distribution Problem in Supply Chains: Modelling and Optimisation Approach

ABSTRACTIn this study, the application of type-II fuzzy sets is addressed to design a multi-product, multi-level, multi-period supply chain networks. The proposed model provides integrated approach to make optimal decisions such as location–allocation, production, procurement and distribution subject to operational and tactical constraints. In the context of fuzzy linear programming, this study involves type-II fuzzy numbers for the right-hand side of constraints regarding three sources of uncertainty: demand, manufacturing and supply. According to fuzzy components considered, a type-II fuzzy mixed-integer linear programming is converted into an equivalent auxiliary crisp model using linear fuzzy type-reducer models. The final models are linear and the global optimum solutions can be achieved using commercial OR softwares. The contributions of this study are three folds: (1) introducing a new integrated supply chain network design problem; (2) considering a solution procedure based on type-II fuzzy sets and (3) presenting a linear fuzzy type-II reducer. Finally, the proposed model and solution approach are illustrated through a numerical example to demonstrate the significance.

An accelerating Benders’ decomposition approach to the integrated supply chain network design with distributed generation

Distributed generation (DG) is one of the new trends in distribution networks under the effect of various policies, such as distribution loss reduction. It is important to find the position and determine the size of DGs in the existing distribution network. In this paper, we consider DGs for the integrated supply chain networks and obtain the optimal locations, sizing, and the service areas of DGs. First, a mixed integer programming model is proposed to formulate the problem. Then, an accelerating Benders’ decomposition approach with two valid cuts and Pareto-optimal cuts is described for this problem. Computational results show the efficiency of the our model and proposed algorithm.

Optimal trade credit and replenishment policies for supply chain network design

Classical supply chain models usually overlook the impact of financial factors on the overall supply chain performance. In practice, however, it has been demonstrated that financial flow, as one of the three major flows, significantly affects the operational decisions. When it is difficult to obtain funds from the financial institutes, trade credit is frequently adopted as an important financial tool that affects the firm’s ordering behavior. In this paper, with the consideration of trade credit, we propose an integrated supply chain network design model that simultaneously determines the location of warehouses, the assignments of retailers to warehouses, the policy of warehouse-retailer inventory management, and the deferred payment time allowed by the warehouses for each retailer to minimize the system-wise location, transportation, multi-echelon inventory, and financing costs. The impacts of trade credit on warehouse locations and warehouse-retailer assignments are examined analytically and numerically. Through numerical studies, we show that the optimal network will be more consolidated with higher financing costs and significant cost reduction can be achieved by considering financial decisions at the strategic supply chain design stage.

Supply Chain Network Design Considering RFID Adoption

This paper reports on the integrated supply chain network design with radio-frequency identification (RFID) technology. The proposed model seeks to maximize the total profits of a manufacturer, servicing multiple retailers through regional distribution centers (RDCs) by identifying the optimal area of influence and order quantity for each RDC using a two-phase approximation method. Simulation results indicate that when using RFID, increasing the order quantity leads to a decrease in the area of influence of each RDC. Our findings also show that RFID has a more pronounced influence on supply chains affected by inventory inaccuracy and demand distortion.

A Simulation-Based Optimization Method for Solving the Integrated Supply Chain Network Design and Inventory Control Problem under Uncertainty

A Simulation-Based Optimization Method for Solving the Integrated Supply Chain Network Design and Inventory Control Problem under Uncertainty

Objectives, products and demand requirements in integrated supply chain network design: a review

Supply chain network design plays an important role in supply chain management. In this paper, a literature review of supply chain network from 1997 until 2014 is given. We identified some important issues in this regard such as products, objectives and product requirements. There is also a short review on some of integration models on supply chain network. Furthermore, most recent approaches that have been used in this issue have been analysed. Finally, a list of future research directions is highlighted.

The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.

An integrated supply chain network design problem for bidirectional flows

Coordination among supply chains has elicited considerable attention in both academia and industry. This paper investigates an integrated supply chain network design problem that involves the determination of the locations for distribution centers and the assignment of customers and suppliers to the corresponding distribution centers. The problem simultaneously involves the distribution of products from the manufacturer to the customers and the collection of components from the suppliers to the manufacturer via cross-docking at distribution centers. The co-location of different types of distribution centers and coordinated transportation are introduced to achieve cost savings. A Lagrangian relaxation-based algorithm is then developed. Extensive computational experiments show that the proposed algorithm has stable performance and outperforms CPLEX for large-scale problems. An industrial case study is considered and sensitivity analysis is conducted to explore managerial insights. Finally, conclusions are drawn, and future research directions are outlined.