Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.     

A strategic model for exact supply chain network design and its application to a global manufacturer

This paper presents a comprehensive model that captures significant strategic decisions involved in designing or redesigning high-performance supply chains from the perspective of the manufacturer. The problem considers deterministic demand by multiple clients, for multiple products, over the periods of a long-term horizon. The design decisions involve selection of suppliers, establishment or resizing of production facilities and distribution centres, possible subcontracting of related activities, and selection of transportation modes and routes. The problem is formulated by a Mixed Integer Linear Programming model. Its objective is to minimise the overall costs associated with procurement, production, inventory, warehousing, and transportation over the design horizon. Appropriate constraints model the complex relationships among the links of the supply chain. The proposed model has been applied to a large case study of a global manufacturing firm, providing valuable insights into the transformation of the firm’s current supply chain network, as well as into the potential of the proposed approach.     

Mitigating supply chain disruptions through interconnected logistics services in the Physical Internet

This paper investigates the resilience of inventory models using interconnected logistics services in the Physical Internet (PI). With traditional supply chain network design, companies define and optimise their own logistics networks, resulting in current logistics systems being a set of independent heterogeneous logistics networks. The concept of PI aims to integrate independent logistics networks into a global, open, interconnected system. Prior research has shown that new inventory models enabled by and applied to PI could help reduce inventory levels thanks to its high flexibility. Continuing along these lines, this paper examines how inventory models applying PI deal with disruptions at hubs and plants. To attain this, a single product inventory problem with uncertain demands and stochastic supply disruptions is studied. A simulation-based optimisation model is proposed to determine inventory control decisions. The results suggest that the PI inventory model, with greater agility and flexibility, outperforms the current classic inventory models in terms of resilience. Moreover, the difference in performance increases when the product value, penalty costs and disruption frequency increases. This paper indicates a novel approach to build a resilient supply network.     

双层延期支付及价格折扣条件下零售商的最优库存策略

研究了在双层延期支付及价格折扣条件下零售商的库存策略。假设零售商在供应链中占据决策的主导地位,即零售商从供应商处得到延期支付及相应的现金折扣,而零售商仅为其顾客提供延期支付。建立了以零售商利润最大化为目标的EOQ（经济订购批量）模型,对模型分析求解,得到零售商的最优订货周期,并且通过一个简易算法,使得模型更容易运用于实践。通过数值算例验证了结论,并为企业物流管理实践提供了建议。     

An integrated inventory optimization model for facility location-allocation problem

This paper presents an integrated inventory distribution optimisation model for multiple products in a multi-echelon supply chain environment. Inventory, transportation and location decisions are considered. The objective is to offer practical guideline to the steel retail supply chain practitioners in choosing the correct distribution centre, finding out inventory level at individual inventory keeping points (retailers and distribution centres) point thereby helping them in reducing overall distribution cost. The framework presented endorses systems approach and suggests near-optimal approach to calculating inventory for an individual distributor and his retailers. Two algorithms are used to solve this problem, a novel hybrid Multi-objective Self-learning particle swarm optimiser and Non-dominated sorting genetic algorithm-II. The model and solution methods are tested on real data-sets obtained from organisations in the steel retail environment. The actual data on inventory holding, ordering and transportation costs of distributors and retailers are used as inputs. The decisions like choosing correct set of Distribution centres, keeping optimal regular and safety stock inventory levels are arrived at by applying practical constraints in the supply chain. Model developed assists in effective and efficient distribution of the products manufactured from the optimal location at minimal cost.     

Modelling and solving spare parts supply chain network design problems

Spare parts are key operational assets in order to minimise unexpected equipment downtimes that may significantly impact a company’s results. The spare parts supply chain network supports the entire spare parts operations management and it is essential to achieve the planned goals. However, most of the traditional literature on spare parts management has not focused on the underlying supply chain network. Thus, this paper studies the integration of supply chain network design and control with traditional spare parts management. In particular, a generic network optimisation modelling structure is proposed, with simultaneous optimisation of warehouse locations and inventory control decisions, allowing minimising the total costs associated with the spare parts supply chain network. The generic model is specified based on three inventory control policies widely employed in the industry, which are suitable for managing a great variety of spare parts, i.e. (s, Q), (R, s, S) and (S-1, S). Furthermore, a solution approach is proposed based on Generalised Benders Decomposition. Finally, numerical results from a real-world application case in the process industry are shown and discussed.     

The design of an agent for modelling supply chain network dynamics

A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.     

Synchronization,cross-docking,and decoupling in supply chain networks

At any distribution centre (DC), the decision of whether to synchronise inbound and outbound flows for cross-docking, or to decouple these flows by maintaining inventory, has a significant impact on supply chain performance. Key drivers of this decision, in turn, are the sizes of the discrete lots that comprise the flows. Thus, we formulate an original optimisation model that determines order lot-sizing decisions to minimise, for given constant arc flows, the sum of ordering cost and pipeline inventory cost on arcs and buffer inventory at DCs. The model employs an average throughput as a surrogate to estimate buffer inventory at facilities at which synchronisation is not economical and therefore serves to decouple inbound and outbound flows. Perfect lot-for-lot matching of shipments would impose very restrictive constraints on supply chain operations, but equality of average throughput indicates an innovative, relaxed mode of synchronisation. This mode is practicable for cross-docking by means of bulk-breaking or consolidation of shipments. A heuristic approach based on the Lagrangian relaxation and subgradient optimisation is developed for the non-linear mixed-general integer optimisation model, which is illustrated by numerical examples and tested using a benchmark data set.     

Supply chain coordination under trade credit and retailer effort

In this paper, we study the role of trade credit in coordinating a Capital Constrained Supply Chain in the presence of retailer Effort (CCSCE), essentially because of the impact of its related default risks on the relationship between the chain’s members. We consider a CCSCE consisting of a supplier and a retailer where the retailer may exert costly promotional efforts to increase the market demand but has limited capital and no access to bank financing due to low credit rating. Conversely, the supplier has adequate funds to offer trade credit to the retailer without borrowing from external channels. We then examine whether the existing coordination contracts can still coordinate the CCSCE under trade credit. Our result shows that these contracts can achieve coordination of the supply chain when the interest rate of trade credit is competitively priced. Nevertheless, this position cannot always be reached. That’s why we propose a generalised contract based on risk compensation to coordinate the CCSCE. Using our proposed coordinating contract, the supplier perfectly coordinates the retailer’s decisions for the largest joint profit, and arbitrarily allocates the maximised joint profit among supply chain members. Finally, the numerical study allows to verify this finding. From managerial insights, our results provide the supply chain managers with novel insights on how to combine trade credit with the existing coordination contracts in order to improve the profitability of the entire supply chain as well as the individual member.     

Supply chain optimisation with assembly line balancing

Supply chain management operates at three levels, strategic, tactical and operational. While the strategic approach generally pertains to the optimisation of network resources such as designing networks, location and determination of the number of facilities, etc., tactical decisions deal with the mid-term, including production levels at all plants, assembly policy, inventory levels and lot sizes, and operational decisions are related to how to make the tactical decisions happen in the short term, such as production planning and scheduling. This paper mainly discusses and explores how to realise the optimisation of strategic and tactical decisions together in the supply chain. Thus, a supply chain network (SCN) design problem is considered as a strategic decision and the assembly line balancing problem is handled as a tactical decision. The aim of this study is to optimise and design the SCN, including manufacturers, assemblers and customers, that minimises the transportation costs for determined periods while balancing the assembly lines in assemblers, which minimises the total fixed costs of stations, simultaneously. A nonlinear mixed-integer model is developed to minimise the total costs and the number of assembly stations while minimising the total fixed costs. For illustrative purposes, a numerical example is given, the results and the scenarios that are obtained under various conditions are discussed, and a sensitivity analysis is performed based on performance measures of the system, such as total cost, number of stations, cycle times and distribution amounts.     

Multi-item inventory model with variable backorder and price discount under trade credit policy in stochastic demand

In this paper, a two echelon supply chain with one manufacturer and one retailer is developed for multi products. The retailer faced with the uncertain demand for all products which follows a normal distribution. The production process is assumed to be imperfect, and the defectiveness is assumed to follow a beta distribution. The manufacturer produces and delivers the products in a number of equal-sized batches to the manufacturer's warehouse, and thereby it is delivers in a number of equal batches to the retailer's warehouse. Shortages are allowed to occur, at the retailer side, and it is backordered partially. The retailer offers a price discount for backordered items to his customers. Both the lead time crashing cost and the partial backorder ratio are considered as the inverse function of lead time. Under these assumptions, there are three inventory models proposed in this paper, one with non-integrated approach, the other with an integrated approach without trade credit and finally an integrated approach with trade credit. A new iterative algorithmic procedure has been developed to minimise the total cost. Finally, numerical examples are given to illustrate the models and the sensitivity analysis is conducted over various model parameters.     

A two-period model for selection of resilient multi-tier supply portfolio

A two-period decision-making model is developed for selection of resilient supply portfolio in a multi-tier supply chain under disruption risks. The planning horizon is divided into two aggregate periods: before and after the disruption. The resilience of the supply chain is achieved by selection ahead of time primary supply portfolio and by pre-positioning of risk mitigation inventory of parts at different tiers that will hedge against all disruption scenarios. Simultaneously, recovery and transshipment portfolios are determined for each disruption scenario and decisions on usage the pre-positioned inventory are made to minimise expected cost or maximise expected service level. Some properties of optimal solutions, derived from the proposed model provide additional managerial insights. The findings also indicate that the developed portfolio approach with an embedded network flow structure leads to computationally efficient stochastic mixed integer program with a strong LP relaxation.     

A blockchain-based approach for a multi-echelon sustainable supply chain

Blockchain technology is destined to revolutionise supply chain processes. At the same time, governmental and regulatory policies are forcing firms to adjust their supply chains in response to environmental concerns. The objective of this study is therefore to develop a distributed ledger-based blockchain approach for monitoring supply chain performance and optimising both emission levels and operational costs in a synchronised fashion, producing a better outcome for the supply chain. We propose the blockchain approach for different production allocation problems within a multi-echelon supply chain (MESC) under a carbon taxation policy. As such, we couple recent advances in digitalisation of operations with increasingly stringent regulatory environmental policies. Specifically, with lead time considerations under emission rate constraints (imposed by a carbon taxation policy), we simultaneously consider the production, distribution and inventory control decisions in a production allocation-based MESC problem. The problem is then formulated as a Mixed Integer Non-Linear Programming (MINLP) model. We show that the distributed ledger-based blockchain approach minimises both total cost and carbon emissions. We then validate the feasibility of the proposed approach by comparing the results with a non-dominated sorting genetic algorithm (NSGA-II). The findings provide support for policymakers and supply chain executives alike.     

A location-routing-inventory model for designing multisource distribution networks

This article studies a ternary-integration problem that incorporates location, inventory and routing decisions in designing a multisource distribution network. The objective of the problem is to minimize the total cost of location, routing and inventory. A mixed-integer programming formulation is first presented, and then a three-phase heuristic is developed to solve large-sized instances of the problem. The numerical study indicates that the proposed heuristic is both effective and efficient.     

Supply chain relationship quality and performance in technological turbulence: an artificial neural network approach

A well-functioning supply chain management relationship cannot only develop seamless coordination with valuable members, but also improve operational efficiency to secure greater market share, increased profits and reduced costs. An accurate decision-making system considering multifactor relationship quality is highly desired. This study offers an alternative perspective and characterisation of the supply chain relationship quality and performance. A decision-making model is proposed with an artificial neural network approach for supply chain continuous performance improvement. Supply chain performance is analysed via a supervised learning back-propagation neural network. An ‘inverse’ neural network model is proposed to predict the supply chain relationship quality conditions. Optimal performance parameters can be obtained using the proposed neural network scheme, providing significant advantages in terms of improved relationship quality. This study demonstrates a new solution with the combination of qualitative and quantitative methods for performance improvement. The overall accuracy rate of the decision-making model is 88.703%. The results indicated that trust has the greatest influence on the supply chain performance. Relationship quality among supply chain partners impacts performance positively as the pace of technological turbulence increases.     

Multi-item distribution network design problems under volume discount on transportation cost

This study considers the distribution network design problems of multi-echelon, multi-item supply chains under volume (weight) discounts on transportation costs. Minimising the total network cost requires determining the following: (1) the service area of distribution centres (DCs); (2) the assignment of retail stores to DCs; and (3) the inventory volume at DCs. This study compares various replenishment policies and discusses the effects of such policies on distribution network design. In general, the results show that single-cluster replenishment is superior to joint cluster replenishment. However, joint cluster replenishment may be superior to single-cluster replenishment under volume (weight) discounts on transportation costs. The results additionally show that single-item replenishment is inferior to multi-item replenishment under volume (weight) discounts on transportation costs. All the problems are formulated as piecewise non-linear programming models with multiple variables. Algorithms are proposed for solving these piecewise non-linear programming problems. Several numerical studies demonstrate the solution procedures and the effects of changing parameters on decision-making.     

Optimal process mean and quality improvement in a supply chain model with two-part trade credit based on Taguchi loss function

The two-part trade credit policy is developed to accelerate cash inflow that can avoid bad debt risk in the earlier economic order quantity (EOQ) models allowing only one period of time for delay in payment. Taguchi loss function has proved to be a more realistic function for fitting the actual quality loss cost in economic product quantity (EPQ) model. To minimise quality loss, optimal process mean setting shifts process mean to balance the cost outside the specification limits, quality improvement applies investment to reduce process variation. Supply chain integration has been proved that it can be used to minimise the entire cost more effectively than independent EOQ or EPQ models. This paper improves the earlier studies by incorporating the above research topics that have not been simultaneously discussed before, develops a supply chain model based on the Taguchi loss function, which combines the trade strategy from the retailer’s perspective and the quality adjustments from the supplier’s perspective to maximise total supply chain profit. We find that the trade credit terms definitely affect suppliers and retailers’ optimal decisions, and numerical examples can provide decision references for supply chain managers to set a trade credit policy and control quality.     

Using simulation-based system dynamics and genetic algorithms to reduce the cash flow bullwhip in the supply chain

The bullwhip effect (BWE) is a phenomenon, which is caused by ineffective inventory decisions made by supply chain members. In addition to known inefficiencies caused by the bullwhip effect within a supply chain product flow, such as excessive inventory, it can also lead to inefficiencies in cash flow such as the cash flow bullwhip (CFB). The CFB reduces the efficiency of the supply chain (SC) through heterogeneous distribution of cash among supply chain members. This paper aims to decrease both the BWE and the CFB across a SC through applying a simulation-based optimisation approach, which integrates system dynamics (SD) simulation and genetic algorithms. For this purpose, cash flow modelling is incorporated into the SD structure of the beer distribution game (BG) to develop the CFB function. A multi objective optimisation model is then integrated with the SD-BG simulation model. Finally, a genetic algorithm (GA) is applied to determine the optimal values for the inventory, supply line, and financial decision parameters. Results show that the proposed integrated framework leads to efficient liquidity management in the SC in addition to cost management.     

Equilibrium analysis of distribution channel structures under power imbalance and asymmetric information

This paper investigates the problem of channel choice game in two power-imbalanced supply chains consisting of the leader supply chain and the follower supply chain. We assume that there exists symmetric and asymmetric cost information between the two supply chains, and that the two chains as well as the two members in each chain follow the Stackelberg game setting. We analyse four competition scenarios: both chains are decentralised, where individual members of both supply chains maximise their own profits by independently selecting their price policies; both chains are integrated, where manufacturers and retailers coordinate their decisions to maximise supply chain profits; the leader chain is decentralised and the follower integrated; the leader is integrated and the follower decentralised. The primary objective of this paper is to investigate the influence of power imbalance, information asymmetries, and the degree of product substitutability under channel choice equilibrium. We find that, in contrast to earlier literature where all manufacturers share equal or balanced decision-making power, an integrated distribution channel is the dominant strategy for the leader under symmetric and asymmetric information Stackelberg game. As the degree of product substitutability increases, the follower will gradually switch from integrated distribution channel to decentralised distribution channel; the follower can gain from constructing a decentralised distribution channel as the prediction accuracy of the leader increases.     

Supply chain optimisation with U-type assembly line balancing

In supply chain optimisation problems, determining the location and number of facilities is considered at a strategic level, while mid-term and short-term decisions such as those concerning assembly policy, inventory levels, lot sizes and scheduling are handled at the tactical and operational levels. However, considering these decisions simultaneously is almost always ignored during the optimisation of distribution/production processes. The aim of the study is to optimise the supply chain network (strategic level), including manufacturers, assemblers and customers, while simultaneously balancing the U-type assembly lines (tactical level) in assemblers. A nonlinear mixed integer mathematical model is proposed to minimise the total costs and the number of assembly stations while minimising the total fixed costs of stations. To show the validity and usefulness of the proposed model, a numerical example with different scenarios and sensitivity analyses is given and discussed.