Concurrent design of product family and supply chain network considering quality and price

We study the problem of concurrent design of a product family and its supply chain (SC) network. Inspired by a real-life case in computer industry, the impact of quality and price in SC demand is investigated. Two different models are proposed, the former maximizes the company’s profit with respect to customers’ priorities on quality and price; the latter is a bi-objective programming, which consider two extreme customer groups: for one group quality has the highest priority and for the other price; the intermediate groups falls between these two. The performance of the models is analyzed through a case problem.     

Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies

In this study, an approach to re-planning the multi-stage supply chain (SC) subject to disruptions is developed. We analyze seven proactive SC structures, compute recovery policies to re-direct material flows in the case of two disruption scenarios, and assess the performance impact for both service level and costs with the help of a SC (re)planning model containing elements of system dynamics and linear programming. In the result, an explicit connection of performance impact assessment and SC plan reconfiguration issues with consideration of the duration of disruptions and the costs of recovery has been achieved.     

Benders’ decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties

This paper attempts to design a reverse supply chain network (SCN), add it to an existing multi-product forward SCN and simultaneously redesign the existing forward supply chain (SC). The problem considers uncertainty on products demand and and also returned products in multi-period context. Benders’ decomposition is applied to solve the stochastic mixed-integer model to optimality. The scenarios are generated based on the demand distribution function using Cholesky’s factorization method to consider correlation among different products’ demands. To decrease the computational effort, the number of scenarios is reduced using k-means clustering algorithm. The method is tested on a cell phone SC.     

Lead time aggregation: A three-echelon supply chain model

In this paper, destructive effects of upstream aggregated stochastic lead times on the supply chain (SC) performance are analyzed. For this purpose, a three-echelon SC consisting of one producer, one distributor, and one retailer is modeled. Both the producer and distributor face stochastic lead times, which can be also aggregated to create a long unpredictable lead time. In order to scale down shortages at the retailer site, an incentive scheme is proposed to convince the upstream members to increase their reorder points. Applying the coordinated model considerably increases the total profit earned by the whole SC as well as all SC members.     

Robust supply chain strategies for recovering from unanticipated disasters

Recovering from unanticipated disasters is critical in today’s global market. This paper examines the effectiveness of popular recovery strategies used to address unpredictable disasters that derail supply chains. We create a formal model to portray dynamic operational performance among supply chain firms facing disruptions caused by natural and man-made disasters. Our analysis shows that a supply chain recovers best if member firms adopt a radical, rapid, costly recovery strategy that immediately resolves the disruption. This observation is robust to various resource consumption requirements. We apply our methodology in the case of Taiwan’s 2011 food contamination scandal and provide managerial insights.     

Analysis of traffic congestion costs in a competitive supply chain

We study a competitive facility location problem with identical suppliers competing in multiple markets subject to distribution network congestion. We first analyze the solution of a symmetric competitive location game and discuss the firms’ facility location and equilibrium market supply decisions. Then, we utilize the model to provide analytical characterization of the effects of traffic congestion costs on equilibrium distribution flows. These analytical results permit qualitative characterization of how changes in congestion levels and costs affect equilibrium location and distribution decisions. The results of extensive numerical studies serve to further illustrate the effects of traffic congestion costs on location, market supply quantity, and distribution decisions.     

Pricing strategies of a dual-channel supply chain with risk aversion

We investigated the effect of risk aversion on the optimal policies of a dual-channel supply chain under complete information and asymmetric information cases. We determined that the optimal value added only depends on the value-added cost. The optimal prices under a risk-averse case are lower than those in a risk-neutral case. Information asymmetry increases wholesale and retail prices but reduces direct sale price, and tends to engender inefficiency. The value of information increases with the mean of the manufacturer’s estimation about the retailer’s risk aversion.     

Retail supply chain network design under operational and disruption risks

Designing robust and resilient retail networks under operational and disruption risks can create substantial competitive advantage. In this paper, a deterministic multiple set-covering model is first proposed. Then, it is extended to a possibilistic scenario-based robust model by scenario generation and disruption profiling to design a robust and resilient retail network. The developed models are validated through randomly generated examples and a real case study in retailing. Numerical results demonstrate that designing retail chains without considering operational and disruption risks is really misleading. Also, multiple covering of retail stores as the measure of redundancy increases the network’s resilience significantly.     

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.     

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.     

Robust grain supply chain design considering post-harvest loss and harvest timing equilibrium

This paper presents a bi-level robust optimization model, where a food company maximizes its profit and minimizes post-harvest loss by optimally deploying grain processing/storage facilities and determining grain purchase price, while a group of spatially distributed non-cooperative farmers determine harvest time, shipment, storage, and market decisions under yield uncertainty and market equilibrium. The non-cooperative behavior of the food company and the farmers is represented by a bi-level Stackelberg leader follower’s game model with mixed-integer decision variables. The proposed model and solution approach are applied to case studies for Illinois and Brazil.     

Fault tolerance modeling for an e-waste recycling supply chain

This paper applies a fault-tolerant method that addresses the problem of steady fulfillment in an e-waste recycling supply chain. Due to the double-ended fluctuations in this supply chain, conventional, optimization based, model predictive control cannot be applied without proper improvement. This paper contributes to the e-waste management literature in the initiation of prudent demand management. The inventory management problem is investigated for a double-ended fluctuation for the e-waste recycling supply chain. It is found that the risk-sensitive predictive control method allows all members to retain a constant inventory level, for which the control target is unclear and the demand fluctuation is high.     

Bioethanol supply chain system planning under supply and demand uncertainties

A mixed integer stochastic programming model is established to support strategic planning of bioenergy supply chain systems and optimal feedstock resource allocation in an uncertain decision environment. The two-stage stochastic programming model, together with a Lagrange relaxation based decomposition solution algorithm, was implemented in a real-world case study in California to explore the potential of waste-based bioethanol production. The model results show that biowaste-based ethanol can be a viable part of sustainable energy solution for the future.     

Incorporating location,routing and inventory decisions in supply chain network design

This paper for the first time presents a novel model to simultaneously optimize location, allocation, capacity, inventory, and routing decisions in a stochastic supply chain system. Each customer’s demand is uncertain and follows a normal distribution, and each distribution center maintains a certain amount of safety stock. To solve the model, first we present an exact solution method by casting the problem as a mixed integer convex program, and then we establish a heuristic method based on a hybridization of Tabu Search and Simulated Annealing. The results show that the proposed heuristic is considerably efficient and effective for a broad range of problem sizes.     

An integrated production-inventory system in a multi-stage multi-firm supply chain

We first generalize a number of integrated models with/without lot streaming and with/without complete backorders under the integer–multiplier coordination mechanism, and then individually derive the optimal solution to the three- and four-stage model, using algebraic methods of complete squares and perfect squares. We subsequently deduce optimal expressions for some well-known models. For our model, we check that the optimal solution, which is algebraically derived, is a global one. We present three numerical examples for illustrative purposes. We finally suggest some future research work involving extension or modification of the generalized model.     

Inventory control for returnable transport items in a closed-loop supply chain

An inventory control model for returnable transport items (RTI) where the manager selects the optimal length for inspection, repair, and purchase cycles is described. Repaired and newly obtained RTI are used in combination to satisfy current production requirements. Uncertain returns are incorporated into the model by determining a satisfactory safety stock level to buffer the inventory of used and repairable containers. The minimum cost solution is obtained when inspection and repair runs begin simultaneously. Cycle times are a function of the expected return rate and repairable percentage, while variability in these random assumptions affects the required safety stock.     

Price promotion with reference price effects in supply chain

We consider the price promotion in a supply chain comprising one manufacturer and one retailer, who take into account the reference price effects of consumers. The problem is analyzed as a manufacturer-lead Stackelberg game. The results indicate that reference price effects could mitigate “double marginalization” effects, and improve the channel efficiency. We also show that the optimal price promotion benefits the manufacturer, retailer and consumers in consumer promotion model. Furthermore, we provide the conditions under which the retailer has an interest in offering price promotion to consumers. Finally, we employ numerical analysis to demonstrate more managerial insights.     

Coordination in a single-vendor multi-buyer supply chain by synchronizing delivery and production cycles

This paper proposes a coordinated single-vendor multi-buyer supply chain model by synchronizing delivery and production cycles. The synchronization is achieved by scheduling the actual delivery days of the buyers and coordinating them with the vendor’s production cycle whilst allowing the buyers to choose their own lot sizes and order cycles. A mathematical model for our proposed coordination is developed and analyzed. The results of our three numerical examples show that the synchronized cycles policy works better than independent optimization as well as restricting buyers to adopt a common order cycle.     

A supply chain network equilibrium model

In this paper, an equilibrium model of a competitive supply chain network is developed. Such a model is sufficiently general to handle many decision-makers and their independent behaviors. The network structure of the supply chain is identified and equilibrium conditions are derived. A finite-dimensional variational inequality formulation is established. Qualitative properties of the equilibrium model and numerical examples are given.     

Optimizing inventory decisions in a multi-stage multi-customer supply chain

Most supply chain models focus on two-stage chains in which vendors supply material to one customer. In this paper, we formulate a three-stage supply chain model where a firm can supply many customers. We deal with three inventory coordination mechanisms between chain members and solve a cost minimization model for each. We show that some of the coordination mechanisms can result in a significantly lower total cost than matching production and delivery along the chain. We provide some insights into when the added complexity of the second and third coordination mechanisms lead to significant cost reductions.