Integrated inventory valuation in multi-echelon production/distribution systems

The pressure to reduce inventory has increased as competition expands, product variety grows, and capital costs increase. This investigation addresses the problem of inventory quantification and distribution within multi-echelon supply chains under market uncertainty and management flexibility. This approach is based on an optimisation model emphasising demand uncertainty and the relevant dimensions of network design as number of echelons, lead time, service level, and cost of processing activities. Overstock quantification enables the understanding of inventory level sensitivity to market uncertainty. A comparison among production sites and storage facilities revealed that higher downstream overstock levels decrease upstream echelons of uncertainty exposition. The contribution of this study relies on management's ability to establish inventory targets for each stocking point according to risk exposure and to promote the optimisation of working capital. Overall, this investigation increases knowledge related to the treatment of demand uncertainty in flexible and integrated supply chains     

Multi-commodity warehouse location and distribution planning with inventory consideration

We consider the problem of designing a distribution network for a logistics provider that acquires products from multiple facilities and then delivers those products to many retail outlets. Potential locations for consolidation facilities that combine shipments for cost reduction and service improvements are considered. The problem is formulated with direct shipment and consolidation opportunities. A novel mathematical model is derived to solve a complex facility location problem determining: (i) the location and capacity level of warehouses to open; (ii) the distribution route from each production facility to each retailer outlet; and (iii) the quantity of products stocked at each warehouse and retailer. A genetic algorithm and a specific problem heuristic are designed, tested and compared on several realistic scenarios.     

Benefits of considering inventory in service parts logistics network design problems with time-based service constraints

We study the integrated logistics network design and inventory stocking problem as characterized by the interdependency of the design and stocking decisions in service parts logistics. These two sets of decisions are usually considered sequentially in practice, and the associated problems are tackled separately in the research literature. The overall problem is typically further complicated due to time-based service constraints that provide lower limits on the percentage of demand satisfied within specified time windows. We introduce an optimization model that explicitly captures the interdependency between network design (location of facilities, and allocation of demands to facilities) and inventory stocking decisions (stock levels and their corresponding stochastic fill rates), and present computational results from our extensive experiments that investigate the effects of several factors including demand levels, time-based service levels and costs. We show that the integrated approach can provide significant cost savings over the decoupled approach (solving the network design first and inventory stocking next), shifting the whole efficient frontier curve between cost and service level to superior regions. We also show that the decoupled and integrated approaches may generate totally different solutions, even in the number of located facilities and in their locations, magnifying the importance of considering inventory as part of the network design models.     

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.     

Multi-period channel coordination in vendor-managed inventory for deteriorating goods

This study examines the problem of optimally dynamic joint decisions, including replenishment scheduling/quantity, retail price, wholesale price, and revenue-sharing allocation, in a vertically decentralised single-manufacturer Stackelberg and single-retailer channel over a multi-period planning horizon, subject to deteriorating goods and multivariate demand function. This study uses a calculus-based formulation combined with dynamic programming techniques to solve the channel coordination decision problem. Additionally, three arrangements, namely price-only contract, revenue-sharing contract, and revenue-sharing plus linear rebate and side-payment contract for channel coordination, are developed under retailer-managed inventory (RMI) and vendor-managed inventory (VMI) systems, respectively. The analysis reveals that the proposed policy under the VMI system with the revenue-sharing plus linear rebate and side-payment contract tends to obtain low retail prices and large demand quantity, and results in near-perfect coordination, including greater system efficiency and Pareto improvements, for the vertically decentralised dynamic channel.     

Consignment and vendor managed inventory in single-vendor multiple buyers supply chains

In this paper we model a consignment (CS) and vendor-managed inventory (VMI) policy for a single vendor and multiple buyers supply chain with known demand. We study three vendor–buyers partnerships: (i) the vendor and the buyers act independently, (ii) the vendor enters in a vendor-managed inventory consignment (VMI&CS) partnership with the buyers and (iii) the vendor and the buyer belong to a vertically integrated firm where a single decision maker decides about the ordering policies. We use relationships (i) and (ii) to study the benefits of the VMI&CS agreement. We provide analytical and numerical results. We find that such an agreement is more beneficial when the vendor has a flexible capacity. It is also more attractive to buyers when they have significant order costs and the vendor's setup cost is not large. Finally we find that under VMI&CS the vendor will tend to make more frequent shipments with smaller lots.     

Roles of inventory and reserve capacity in mitigating supply chain disruption risk

This research focuses on managing disruption risk in supply chains using inventory and reserve capacity under stochastic demand. While inventory can be considered as a speculative risk mitigation lever, reserve capacity can be used in a reactive fashion when a disruption occurs. We determine optimal inventory levels and reserve capacity production rates for a firm that is exposed to supply chain disruption risk. We fully characterise four main risk mitigation strategies: inventory strategy, reserve capacity strategy, mixed strategy and passive acceptance. We illustrate how the optimal risk mitigation strategy depends on product characteristics (functional versus innovative) and supply chain characteristics (agile versus efficient). This work is inspired from a risk management problem of a leading pharmaceutical company.     

Joint pricing and inventory strategies in a supply chain subject to inventory inaccuracy

This paper focuses on pricing strategies, inventory policies for a supply chain when Radio Frequency Identification (RFID) technology is adopted to cope with inventory inaccuracy. The supply chain consists of one supplier and one retailer, in which the RFID tag price is shared between the supplier and the retailer. We present and compare the performance differences between a wholesale price contract and a consignment contract when the retailer is the Stackelberg leader and the supplier is the follower. Based on the optimal pricing and inventory decisions, an interesting observation of contract selection is that there are two critical values of inventory available rate such that when the inventory availability is less than the lower value, both the supplier and the retailer prefer a consignment contract; when the inventory availability is greater than the upper value, a wholesale price contract is their best choice; when the inventory availability is between the two values, the supplier prefers a wholesale price contract and the retailer prefers a consignment contract. Additionally, there exist threshold values of RFID tag price and sharing rate to determine the contract preference for the retailer. Furthermore, the profits of both the supplier and the retailer are independent of the RFID tag price sharing rate in a wholesale price contract, and the supplier has the incentive to invest in RFID tag cost in a consignment contract.     

Optimization models for the dynamic facility location and allocation problem

The design of logistic distribution systems is one of the most critical and strategic issues in industrial facility management. The aim of this study is to develop and apply innovative mixed integer programming optimization models to design and manage dynamic (i.e. multi-period) multi-stage and multi-commodity location allocation problems (LAP). LAP belong to the NP-hard complexity class of decision problems, and the generic occurrence requires simultaneous determination of the number of logistic facilities (e.g. production plants, warehousing systems, distribution centres), their locations, and assignment of customer demand to them. The proposed models use a mixed integer linear programming solver to find solutions in complex industrial applications even when several entities are involved (production plants, distribution centres, customers, etc.). Lastly, the application of the proposed models to a significant case study is presented and discussed.     

Solving closed-loop supply chain problems using game theoretic particle swarm optimisation

In this paper, we propose a closed-loop supply chain network configuration model and a solution methodology that aim to address several research gaps in the literature. The proposed solution methodology employs a novel metaheuristic algorithm, along with the popular gradient descent search method, to aid location-allocation and pricing-inventory decisions in a two-stage process. In the first stage, we use an improved version of the particle swarm optimisation (PSO) algorithm, which we call improved PSO (IPSO), to solve the location-allocation problem (LAP). The IPSO algorithm is developed by introducing mutation to avoid premature convergence and embedding an evolutionary game-based procedure known as replicator dynamics to increase the rate of convergence. The results obtained through the application of IPSO are used as input in the second stage to solve the inventory-pricing problem. In this stage, we use the gradient descent search method to determine the selling price of new products and the buy-back price of returned products, as well as inventory cycle times for both product types. Numerical evaluations undertaken using problem instances of different scales confirm that the proposed IPSO algorithm performs better than the comparable traditional PSO, simulated annealing (SA) and genetic algorithm (GA) methods.     

A survey of semiconductor supply chain models Part II: demand planning,inventory management,and capacity planning

Part I of this three-part series described semiconductor supply chains from the decision-making and functional perspectives, using this as a framework to review the industrial engineering and operations research literature on the problems arising in these supply chains. Part I then reviewed the literature on Strategic Network Design, supply chain coordination, sustainability and simulation-based decision support. This paper, Part II, reviews the areas of Demand Planning, Inventory Management and Capacity Planning in semiconductor supply chains. Part III concludes the series by discussing models to support Master Planning, Production Planning and Demand Fulfilment in this industry.     

Location-inventory problem in supply chains: a modelling review

A location-inventory problem (LIP) aims to integrate strategic supply chain design decisions with tactical and operational inventory management decisions. This study provides an extensive review of the existing literature of LIP modelling. A mathematical model is presented for a basic LIP, which can be further developed to incorporate additional features for use in real-world scenarios. We also discuss the evolution of LIP modelling literature over the past three decades and provide summary tables outlining characteristics of the published works including key modelling attributes and objective function cost components. Additional classifications are completed based on the solution methods adopted and real-world applications investigated. Our observations provide important insights and identify potential directions for future research in the field.     

Designing a supply chain network for deteriorating inventory under preservation effort and trade credits

When designing a perishable goods supply chain network under trade credit arrangements, distribution companies must contend with deteriorating inventory and product preservation efforts to maximise profits. Key decisions include locating distribution centres (DCs), assigning retail stores to DCs, joint replenishment cycle time and investing in preservation technology. This paper addresses these factors from the position that as preservation effort increases, preservation technology cost increases and deterioration rate decreases. An algorithm based on piecewise nonlinear optimisation is provided for solving supply chain network design problems efficiently. In contrast to other studies that have used the approximation approach, the proposed approach solves the original problem accurately and efficiently. Numerical studies are conducted to demonstrate the solutions procedures and determine the effects of the parameters on decisions and profits. The results of this study and the proposed modelling approach are useful references for managerial decisions in designing a supply chain network the context of trade credit and inventory deterioration.     

Integrated workforce capacity and inventory management under labour supply uncertainty

In a manufacturing environment with volatile demand, inventory management can be coupled with dynamic capacity adjustments for handling the fluctuations more effectively. In this study, we consider the problem of integrated capacity and inventory management under non-stationary stochastic demand and capacity uncertainty. The capacity planning problem is investigated from the workforce planning perspective where the capacity can be temporarily increased by utilising contingent workers from an external labour supply agency. The contingent capacity received from the agency is subject to an uncertainty, but the supply of a certain number of workers can be guaranteed through contracts. There may also be uncertainty in the availability of the permanent and contracted workers due to factors such as absenteeism and fatigue. We formulate a dynamic programming model to make the optimal capacity decisions at a tactical level (permanent workforce size and contracted number of workers) as well as the operational level (number of workers to be requested from the external labour supply agency in each period), integrated with the optimal operational decision of how much to produce in each period. We analyse the characteristics of the optimal policies and we conduct an extensive numerical analysis that helps us provide several managerial insights.     

Multi-echelon service models for inventory systems under different rationing policies

In this paper we model the service performance of two-echelon divergent production networks consisting of one central stock-point feeding a number of end stock-points where the external demand is realized. The systems we consider allow all stock-points to hold inventory and use periodic review ordering policies at all levels. Whenever the lower echelon has insufficient inventory to cover all upper echelon requisitions some policy to ration the available material is needed. Concentrating on one push and one pull rationing policy, we explore the system dynamics and develop models for three popular measures of the system service performance. All models make use of non-dimensional ratios which drastically reduce the number of parameters involved. Although these models are only approximate, numerical and simulation results demonstrate the adequacy of the approximations involved.     

A supply chain model with vendor-managed inventory,consignment, and quality inspection errors

This paper considers the integration between quality control and production inventory control in supply chain management. Specifically, we study the effect of inspection errors on the costs incurred in a supply chain system with a single vendor and multiple buyers. In this system, the vendor enters into a vendor-managed inventory (VMI) and a consignment stock (CS) partnership with several buyers. We assume that the items made by the vendor are not in perfect quality, but they contain a given proportion of defective units. We also assume that quality inspection of these items by the buyers is subject to sampling errors. Three cases indicating to different levels of supply integration are considered: VMI–CS system, traditional system and integrated system. For each case, a mathematical model is formulated, an optimum solution is developed, and a numerical example is solved.     

Integrated design of supply chain networks with three echelons, multiple commodities and technology selection

We consider a strategic supply chain design problem with three echelons, multiple commodities and technology selection. We model the problem as a tri-echelon, capacitated facility location problem that decides on the location of plants and warehouses, their capacity and technology planning, the assignment of commodities to plants and the flow of commodities to warehouses and customer zones. We use a mixed-integer programming formulation strengthened by valid but redundant constraints and apply Lagrangean relaxation to decompose the problem by echelon. Lagrangean relaxation provides a lower bound that is calculated using an interior-point cutting plane method. Feasible solutions are generated using a primal heuristic that uses the solution of the subproblems. Unlike common practice in the literature, the decomposition does not aim at getting easy subproblems, but rather at getting subproblems that preserve most of the characteristics of the original problem. Not only does this provide a sharp lower bound but also leads to a simple and efficient primal heuristic. We can afford to have relatively difficult subproblems because the interior-point cutting plane method used to solve the Lagrangean dual makes clever and selective choices of the Lagrangean multipliers leading to fewer calls to the subproblems. Computational results indicate the efficiency of the approach in providing a sharp bound and in generating feasible solutions that are of high quality.     

基于供应链技术的铜盘管季节性库存问题研究

总结铜盘管市场特点,详细分析季节性库存过程中存在的库存产品积压风险、库存产品质量风险、铜价波动风险以及资金短缺风险,提出利用供应链库存管理技术、延迟化策略、套期保值、融通仓等现代供应链管理理论来降低季节性库存所面临的各种风险。     

Supply chain design to guarantee quoted lead time and inventory replenishment: model and insights

Do lead time constraints only lead to re-think and re-optimise the inventory positioning along the supply chain or can they impact on the design of the supply chain itself? To answer such a question, we integrate the lead time constraints in a multi-echelon supply chain design model and challenge the difficulty of combining in the same model the long-term decisions (facility location, supplier selection) with the midterm decisions (inventory placement and replenishment, delivery lead time). The model guarantees the respect of the quoted lead time associated with each customer order and the replenishment of the different stocks (raw materials, intermediate and final products) in the different stages of the supply chain between any pair of consecutive orders. We use the model to investigate the impact of the quoted lead time and customer’s order frequency on supply chain design decisions and costs. Some of our results indicate that the lead time constraints can lead to bringing the sites of manufacturing and distribution close to the demand zone and to select local suppliers in spite of their higher 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.