Design of international assembly systems and their supply chains under NAFTA

The purpose of this paper is to provide a decision support aid for the strategic design of an assembly system in the international business environment created by NAFTA. The strategic design problem is to prescribe a set of facilities, including their locations, technologies, and capacities, as well as strategic aspects of the supply chain, selecting suppliers; locating distribution centers; planning transportation modes; and allocating target levels (i.e., amounts) for production, assembly, and distribution. The objective is to maximize after-tax profits. This paper presents a mixed integer programming model that represents the complexities of the international design problem as well as relevant enterprise-wide decisions in the US–Mexico business environment under NAFTA. It deals with a broad set of design issues (e.g., bill-of-material restrictions, international financial considerations, and material flow through the entire supply chain) using effective modeling devices (e.g., linearizing non-linearities that arise in modeling transfer prices and allocating transportation charges). Examples demonstrate how managers might use the model as a decision support aid.     

Sourcing decisions under risks of catastrophic event disruptions

In this paper, a supplier selection problem is studied under risks of supplier failure due to the catastrophic events disruption. An analytical model is developed to determine the optimal number of suppliers considering different failure probability, capacity, and compensation. An algorithm is designed to find the optimal solution and numerical study is carried out to illustrate the model. Results of numerical study and sensitivity analysis provide useful guidelines for managers to select the optimal number of suppliers under the risks of supply disruption.     

An integrated modeling framework for design of logistics networks with expedited shipment services

This paper studied an integrated logistics network problem that determines optimal supplier locations, assignments of these suppliers to terminal facilities, expedited shipment configurations, and inventory management strategies in an uncertain environment. We studied the problem structure and proposed mathematical models to determine the optimal network design that minimizes the expected total system cost. We developed a customized solution approach based on Lagrangian relaxation that can solve these models efficiently and accurately. Numerical examples are conducted to draw managerial insights into how problem settings and key parameter values affect the optimal design results.     

A supporting station model for reliable infrastructure location design under interdependent disruptions

This paper proposes a new modeling method that equivalently transforms interdependent and correlated facility failures in an infrastructure system into only i.i.d. disruptions in a supporting structure. The properties of this structure are examined and a mathematical model is created to solve reliable facility location design problems under correlated facility failure risks. This model is formulated into a compact integer linear program and can be efficiently solved by state-of-the-art solvers. A set of experiments and case studies are conducted to demonstrate the applicability of the proposed model and to draw managerial insights into the optimal system design.     

Diversification strategy with random yield suppliers for a mean–variance risk-sensitive manufacturer

We consider the diversification strategy for a mean–variance risk-sensitive manufacturer with unreliable suppliers. We first analyze the linear model and find that the suppliers are selected according to the descending order of their contributed marginal expected profit, and increasing the manufacturer’s risk-averseness leads to a more even allocation of demand across the suppliers. Then, we study the general newsvendor model. By approximating the leftover inventory with a normal distribution, we establish the general properties of the active supplier set and show that the supplier selection rule is similar to that under the risk-neutral setting when the demand uncertainty is large. Moreover, we conjecture that the selection rule also applies when the demand uncertainty is low, which we verify with an extensive numerical study. Our paper makes two contributions: First, we establish the properties of the optimal diversification strategy and develop corresponding insights into the trade off between cost and reliability under the mean–variance framework. Second, we perform comparative statics on the optimal solution, with a particular emphasis on investigating how changes in the supplier’s cost or reliability affect the risk-averse manufacturer’s ordering decisions and customer service level.     

Multi-objective supplier selection and order allocation under disruption risk

We formulate a multi-objective MILP model to find the optimal choice of suppliers and their order quantity allocation under disruption risk. Suppliers are evaluated and ranked, based on the preference values obtained using a hybrid fuzzy AHP-fuzzy PROMETHEE. Multi-objective Particle Swarm Optimization is then applied to yield a set of Pareto-optimal solutions for the choice of suppliers and their order allocation. Numerical experimentation suggests that the supplier failure probability affects the expected total cost more than supplier flexibility and loss cost. Sensitivity analysis is performed on the failure probability, the output flexibility, and loss cost of the suppliers.     

Stochastic optimization of sustainable hybrid generation bioethanol supply chains

This paper focuses on designing a hybrid generation bioethanol supply chain (HGBSC) that will account for economic, environmental and social aspects of sustainability under various uncertainties. A stochastic mixed integer linear programming model is proposed to design an optimal HGBSC. A case study set in the state of North Dakota in the United States is used as an application of the proposed model. The results suggest that the designs of optimal HGBSC change when different sustainability standards are applied. In addition, sensitivity analysis is conducted to provide deeper understanding of the proposed model.     

The capacitated plant location problem with customers and suppliers matching

This paper introduces a new problem called the capacitated plant location problem with customer and supplier matching (CLCSM). The product distribution from plants to customers and the material supply from suppliers to plants are considered together. We merge a distribution trip and a supply trip into one triangular trip for saving allocation cost. Vehicles from plants visit a customer and a supplier for each trip. We provide a heuristic solution procedure based on Lagrangian relaxation. Computational results indicate that the proposed heuristic solution procedure is shown to be efficient yielding optimal or near-optimal solutions for randomly generated instances.     

A three-level supply chain network design model with risk-pooling and lead times

This paper considers a single-sourcing network design problem for a three-level supply chain consisting of suppliers, distribution centers (DC’s) and retailers, where risk-pooling strategy and DC-to-supplier dependent lead times are considered. The objective is to determine the number and locations of suppliers and DC’s, the assignment of each location-fixed DC to a supplier and that of each retailer to a DC, which minimizes the system-wide location, transportation, and inventory costs. The problem is formulated as a nonlinear integer programming model, for which a two-phase heuristic solution algorithm is derived based on the Lagrangian relaxation approach. Numerical experiments show that the proposed heuristic is effective and also efficient.     

Coordinating pricing and inventory decisions in a multi-level supply chain: A game-theoretic approach

This paper concerns coordination of enterprise decisions such as suppliers and components selection, pricing and inventory in a multi-level supply chain composed of multiple suppliers, a single manufacturer and multiple retailers. The problem is modeled as a three-level dynamic non-cooperative game. Analytical and computational methods are developed to determine the Nash equilibrium of the game. Finally, a numerical study in computer industry is conducted to understand the influence of the market scale parameter and the components selection strategy on the optimal decisions and profits of the supply chain as well as its constituent members. Several research findings have been obtained.     

基VMI的供应链利润模型研究

研究了供应链管理环境下新的库存策略。建立了基于VMI的有初始库存、允许库存短缺、缺货需补充、补充具有延时的供应链利润模型，并对该模型进行了供应链总的库存相关成本及供应商的库存相关成本分析。     

Robust optimization for United States Department of Agriculture food aid bid allocations

The U.S. Department of Agriculture (USDA) currently uses a bidding system to determine carriers and suppliers that would partner in providing food aid annually in response to global emergencies and famine. We mimic the USDA approach via a robust optimization model featuring box and ellipsoid uncertainty frameworks to account for uncertainties in demand, supplier and carrier bid prices. Through a case study utilizing historical invoice data, we demonstrate our model applicability in improving ocean carrier and food supplier bid pricing strategy and similar supply chain network optimization problems. Through a validation algorithm we demonstrate the value of our robust models.     

The equilibrium of closed-loop supply chain supernetwork with time-dependent parameters

In this paper, we develop a closed-loop supply chain supernetwork model including suppliers, manufacturers, retailers and consumers at demand market, in which the demand for product is seasonal (t), and the sensitivity (w) of demand to price is another key factor which effects consumers’ demand. Moreover, the manufacturers invest the reverse distribution channel for incenting consumers to return more used products. Based on the Evolutionary Variational Inequalities (EVI) theory and Projected Dynamical Systems (PDS), the equilibrium condition of closed-loop supply chain is formulated, and the model is verified reasonably by numerical example.     

Dual sourced supply chains: the discount supplier option

In this paper, we examine the dynamics of a supply chain that has the option of using two suppliers – one reliable, and the other unreliable. We characterize the unreliable supplier with long lead-time mean and variance. Although the use of the unreliable supplier might potentially warrant higher inventory and transportation costs, it is attractive because of the willingness of the supplier to provide a discount on the purchase price. We analyze the cost economics of two suppliers in a broader inventory-logistics framework, one that includes in-transit inventories and transportation costs. In this broader perspective, we provide a simple heuristic and sample exchange curves to determine: (i) if the order should be split between the suppliers; and (ii) if the order is split, the amount of discount and the fraction ordered to the secondary supplier to make order-splitting a worth-while policy. ©     

Dynamics and equilibria of ecological predator-prey networks as nature’s supply chains

In this paper, we develop a dynamic network model of ecological food webs and prove that the set of stationary points of the projected dynamical system coincides with the set of solutions of a variational inequality governing the equilibrium of predator-prey networks. We also establish the equivalence between the ecological models and supply chain network equilibrium models and highlight the connections to spatial price equilibrium problems. We propose an algorithmic scheme, provide convergence results, and apply it to a food web drawn from a fisheries application.This paper is a contribution to the interdisciplinary supply chain network literature.     

Integrating the warehousing and transportation functions of the supply chain

Electronic commerce and associated business-to-business transaction capabilities have changed the way in which supply chains operate. The Internet has enabled information exchange on an unprecedented scale, often at a pace too fast for normal consumption. Companies are not equipped to make effective use of data from warehouse management systems––which contain information on supplier/customer warehouse inventory levels and key customer ordering patterns––and transportation management systems––within which information pertaining to the location of important supply chain assets such as products or vehicles is typically stored. These systems are key factors in integrating the physical flow of goods along the supply chain. The integration of these systems leads to global inventory visibility, which, in turn, leads to reduced costs and improved customer service by decreasing shipping and receiving cycle times, increasing shipment and inventory accuracy, and decreasing lead-time variability. This paper examines the total cost benefits that can be achieved by suppliers and warehouses through the increased global visibility provided by an integrated system. We develop a discrete event simulation model of a multi-product supply chain to examine the potential benefits to be gained from global inventory visibility and trailer yard dispatching and sequencing techniques. Experimental results demonstrate the potential for this integrated paradigm to improve customer service through improved efficiencies, reduced costs, and reduced lead-time variability.     

The optimization of the closed-loop supply chain network

This paper develops a model of a general closed-loop supply chain network, which includes raw material suppliers, manufacturers, retailers, consumers and recovery centers. The objective of this paper is to formulate and optimize the equilibrium state of the network by using the theory of variational inequalities. Several examples and figures are used to describe the effects of parameters (the return ratio, the transformation rate of raw materials, and the transformation rate of recyclable products) on the equilibrium shipments and net revenues.     

基于MTO的制造商供应链优化模型

针对基于MTO经营策略的供应链优化模型对运输环节考虑不足的问题,依据运输商、运输方式、线路类型、车型、货物、运送的起始地和终止地等因素对运输费用的共同作用,构建了基于MTO的制造商分阶段线性优化模型,以实现对制造商生产经营活动的优化,并对模型的应用举例说明。     

A resource-based view of green supply management

Companies are being increasingly pressured to consider environmental concerns in their manufacturing activities and, more recently, with regard to their supply bases. Despite the broad range of literature that links performance to both green manufacturing capabilities such as pollution prevention and green supply management (GSM), managers are having difficulties developing a greener supply chain. The objective of this paper is to provide a model for development of GSM capabilities. Using the resource-based view of the firm (RBV) as the theoretical background, we postulate that plant resources are positively related to green manufacturing capabilities, which in turn are positively related to GSM capabilities. The data from a survey of a sample of manufacturing plants indicates that a managerial philosophy that includes external knowledge exchange directly supports both greener process management and environmental collaboration with suppliers. However, this managerial philosophy is only indirectly related to supplier selection and monitoring. The managerial implications of these findings are twofold: managers seeking to implement GSM need to view internal investment in green process management as a step toward environmental management of their external supply chains. They also must realize that green process management requires the support of other resources, such as environmental investments and top management commitment.     

Strategic design and operational management optimization of a multi stage physical distribution system

Design and management of logistic networks is one of the most critical issues in supply chain management. However, the literature does not contain any effective models, methods, and applications that simultaneously support management decisions in the strategic design of the distribution system, in the operational planning and organization of vehicles, and in container trips organization adopting different modes of transportation. The aim of this paper is to illustrate an original framework for the design and optimization of a multi echelon and multi level production/distribution system that combines mixed-integer linear programming modeling with cluster analysis, heuristic algorithms, and optimal transportation rules. A significant case study is illustrated revealing the effectiveness of the approach and tools proposed.