Production and delivery policies for enhanced supply chain partnerships

Recent research on supply chain management has highlighted the importance of building strong customer–supplier relationships in order to gain competitive advantage. This paper examines the benefits of buyer–supplier partnerships over lot-for-lot, i.e. single setup single delivery (SSSD) systems and suggests two policies that the supplier can pursue in order to meet customers’ needs: (1) Single setup multiple delivery (SSMD), and (2) Multiple setup multiple delivery (MSMD). If its fixed setup cost is relatively high, the supplier would prefer to implement SSMD and produce an entire order with one setup. However, if the supplier can reduce the setup cost and the supplier's capacity is greater than the threshold level (P?=?2D), it is more beneficial for the supplier to implement the multiple setups and multiple deliveries (MSMD) policy, even though he pays more frequent setup costs since the savings in inventory holding costs is greater than the increased setup costs. In the latter case, setup reduction is realized by the knowledge and efficiency gained through frequent setup operations. To provide guidelines for the policy selection, we examine the interactions among variables, such as production capacity, learning rate, and holding costs for both parties. The paper also discusses the benefit sharing plan, which discusses according to the contribution (or sacrifice) each party made to the partnership efforts.     

依赖于价格的供应链质量惩罚策略研究

为了有效激励供应商提高产品质量,提出了一种制造商主导下依赖于产品价格的供应链质量惩罚策略。分别考虑由于供应商提供不合格产品而引起的制造商内部质量损失和外部质量损失。制造商依据产品价格对供应商实施质量惩罚,运用主从对策的方法建立了供应商与制造商的Stackelberg博弈模型,求解了模型的子博弈精炼纳什均衡解。算例则针对4种常见情况下的惩罚策略,利用数值结果分析比较了所构建的质量惩罚策略的优势。结果表明：依赖于价格的质量惩罚策略有利于激励供应商提高产品质量,增加供应链收益。     

Manufacturing lot-sizing,procurement and delivery schedules over a finite planning horizon

In this study, an integrated manufacturing system for technology-related companies whose products are experiencing continuous price decrease during the life cycle is studied for optimal procurement, production and delivery schedules over a finite planning horizon. The model considers the inventory cost both at manufacturing and at delivery from supplier. Since the price is continuously decreasing, a manufacturing firm delivers the finished goods in small quantities frequently. Frequent deliveries in small lots are effective to reduce the total cost of the supply chain. The key for high-tech industries is to reduce the inventory holding time since the component prices are continuously decreasing, and this can only be achieved by implementing an efficient supply chain. Therefore, the main purpose of this paper is to develop an integrated inventory model for high-tech industries in JIT environment under continuous price decrease over finite planning horizon while effectively and successfully accomplishing supply chain integration so that the total cost of the system is minimal. An efficient algorithm is developed to determine the optimal or near-optimal lot sizes for raw material procurement, and manufacturing batch under a finite planning horizon. Finally, the solution technique developed for the model is illustrated with numerical examples.     

The economic lot and delivery scheduling problem: the common cycle case

We analyze the interface between a supplier and an assembly facility, where direct shipments are made from one to the other. The final manufacturing step at the supplier involves multiple components produced on a single machine or production line. The assembly facility uses these components at a constant rate. The supplier incurs a sequence-independent setup cost and/or setup time each time the production line is changed over from one component to another. On the other hand, setup costs and times for the assembly facility are negligible. We consider two types of delivery cost: a fixed charge for each delivery, and a fixed-charge-per-truck cost.

We develop a heuristic procedure to find a 'just-in-time' schedule in which one production run of each product and a subsequent delivery of these products to the assembly facility occur in each cycle. The objective is to find the cycle duration that minimizes the average cost per unit time of transportation, inventory at both the supplier and the assembly facility, and setup costs at the supplier. We also develop an error bound for this procedure, and use some of the insights gained from the analysis to explain how delivery schedules can influence the attractiveness of reductions in production setup costs.     

Incorporating supplier selection and order allocation into the vehicle routing and multi-cross-dock scheduling problem

In the vehicle routing problem with cross-docking (VRPCD), it is assumed that the selected suppliers and the quantity of the products purchased from each supplier are known. This paper presents an MILP model which incorporates supplier selection and order allocation into the VRPCD in a multi-cross-dock system minimising the total costs, including purchasing, transportation, cross-docking, inventory and early/tardy delivery penalty costs. The sensitivity of the model on the key parameters of the objective function is analysed and the supply decisions are evaluated when the coefficients of the distribution cost are changed. A two-stage solution algorithm (TSSA) is proposed and the results of the TSSA for small-sized instances are compared with the exact solutions. Finally, a large-sized real case of an urban freight transport is solved using the TSSA.     

Pre-positioning inventory and service outsourcing of relief material supply chain

Service outsourcing is very common in a commercial supply chain, and in humanitarian relief area, the transportation service is usually outsourced. To practice relief supply more effectively, it seems essential to enlarge outsourcing from shipping to more areas, and private enterprises could play a vital role. This paper examines the optimal pre-disaster order quantity of a certain relief commodity, based on a two-stage coordinated approach. Our findings show that the delay cost, shortage penalty cost, risk of supply shortage, salvage value, expected perishable rate, unit inventory cost and reactive price have significant impacts on the optimal amount of propositioned inventory. Moreover, the outsourcing strategies differ by types of relief commodities. For perishable supplies, proactive or reactive outsourcing would improve the benefits of buyer and supplier simultaneously. As for imperishable supplies, it is better to combine proactive insourcing approach and reactive outsourcing strategy. In view of some supplies whose monitoring cost is high, the insourcing approach is much better than the outsourcing approach.     

Joint production and shipment lot sizing for a delivery price-based production facility

A joint economic production quantity (EPQ) and delivery quantity model for a production system is investigated in this paper. More specifically, an EPQ policy is implemented in the production system, while a smaller shipping quantity is periodically dispatched to the customer. The production system is also responsible for the shipment cost, i.e. a delivery price-based procurement from the customer. The considered cost includes setup cost to launch the batch production, inventory carrying cost, and transportation cost, where the transportation cost is a function of the delivery quantity. A per unit time cost model is developed and analysed to determine the optimal production and delivery quantities. Under some mild conditions, it can be shown that the joint cost function is convex with respect to the production quantity; and the number of delivery is an integer in each replenishment cycle. Computational study has demonstrated the significant impact of the joint decision model on the operating cost. In particular, the reduction in total cost can be more than 15% when inventory carrying costs, and/or transportation costs, are high.     

Integrated production scheduling and vehicle routing problem with job splitting and delivery time windows

In this paper, we study a production scheduling and vehicle routing problem with job splitting and delivery time windows in a company working in the metal packaging industry. In this problem, a set of jobs has to be processed on unrelated parallel machines with job splitting and sequence-dependent setup time (cost). Then the finished products are delivered in batches to several customers with heterogeneous vehicles, subject to delivery time windows. The objective of production is to minimize the total setup cost and the objective of distribution is to minimize the transportation cost. We propose mathematical models for decentralized scheduling problems, where a production schedule and a distribution plan are built consecutively. We develop a two-phase iterative heuristic to solve the integrated scheduling problem. We evaluate the benefits of coordination through numerical experiments.     

随机需求条件下供应链的补货及折扣策略研究

研究一个供应商和多个零售商围绕单品种商品组成的供应链体系中,以供应商为核心的供应链库存管理,目标是通过直接降低供应商的库存成本,从而降低供应链的总成本.假设每个零售商面对服从随机正态分布的提前期客户需求,在不考虑交货时间的情况下,供应商在固定的时间间隔满足零售商的补货需要,并以价格折扣的方式补偿零售商的成本增加.由此得到较优的补货间隔,并给出了求解方法.最后,通过仿真验证了该解法的可行性并评估了该策略对各方的影响.     

The economic lot and delivery scheduling problem: common cycle, rework, and variable production rate

The economic lot and delivery scheduling problem is to simultaneously determine the production sequence of several assembly components at a supplier and the delivery interval of those components to the customer. The customer, an assembly facility, is assumed to use the components at a constant rate. The objective is to find the production sequence and delivery interval that minimize the holding, setup, and transportation cost for the supply chain. Previous solutions to the problem assume a constant production rate for each component and that all components are of acceptable quality. These assumptions ignore volume flexibility and quality cost. Volume flexibility permits a system to adjust the production rate upwards or downwards within wide limits. Also, component quality may deteriorate with larger lot sizes and decreased unit production times. In this paper, we develop an algorithm for solving the economic lot and delivery scheduling problem for a supplier using a volume flexible production system where component quality depends on both lot sizes and unit production times. We test the performance of the algorithm and illustrate the models with numerical examples.     

Maintenance contract assessment for aging systems

This paper considers an aging system, where the system failure rate is known to be an increasing function. After any failure, maintenance is performed by an external repair team. Repair rate and cost of repair are determined by a corresponding maintenance contract with a repair team. There are many different maintenance contracts suggested by the service market to the system owner. In order to choose the best maintenance contract, a total expected cost during a specified time horizon should be evaluated for an aging system. In this paper, a method is suggested based on a piecewise constant approximation for the increasing failure rate function. Two different approximations are used. For both types of approximations, the general approach for building the Markov reward model is suggested in order to assess lower and upper bounds of the total expected cost. Failure and repair rates define the transition matrix of the corresponding Markov process. Operation cost, repair cost and penalty cost for system failures are taken into account by the corresponding reward matrix definition. A numerical example is presented in order to illustrate the approach. Copyright © 2008 John Wiley & Sons, Ltd.     

A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty

Humanitarian relief logistics is one of the most important elements of a relief operation in disaster management. The present work develops a multi-objective robust stochastic programming approach for disaster relief logistics under uncertainty. In our approach, not only demands but also supplies and the cost of procurement and transportation are considered as the uncertain parameters. Furthermore, the model considers uncertainty for the locations where those demands might arise and the possibility that some of the pre-positioned supplies in the relief distribution center or supplier might be partially destroyed by the disaster. Our multi-objective model attempts to minimize the sum of the expected value and the variance of the total cost of the relief chain while penalizing the solution’s infeasibility due to parameter uncertainty; at the same time the model aims to maximize the affected areas’ satisfaction levels through minimizing the sum of the maximum shortages in the affected areas. Considering the global evaluation of two objectives, a compromise programming model is formulated and solved to obtain a non-dominating compromise solution. We present a case study of our robust stochastic optimization approach for disaster planning for earthquake scenarios in a region of Iran. Our findings show that the proposed model can help in making decisions on both facility location and resource allocation in cases of disaster relief efforts.     

Multivariate tolerance design using quality loss

The determination of tolerance allocations among design parameters is an integral phase of product/process design. Such allocations are often necessary to achieve desired levels of product performance. We extend our prior research on tolerance allocation by developing both parametric and nonparametric methods for a multivariate set of performance measures that are functions of a common set of design parameters. The parametric method is novel and assumes full information about the probability distribution of design parameter processes. The proposed nonparametric method assumes that only partial information is available and significantly extends prior research by considering a more contemporary and realistic model for manufacturer costs. For both methods we derive economically based models that represent the costs, both internal (supplier) and external (manufacturer), of tolerance allocation under several different process scenarios. These scenarios are based on the manner of disposition of nonconforming product. For the parametric methods we derive tolerance allocation solutions that jointly minimize expected total cost of the supplier and manufacturer. For the nonparametric methods we derive solutions for tolerance allocation that jointly minimizes the maximum expected total cost. An example in the fabrication of a rubber tread compound is used to: (i) demonstrate the implementation of our proposed methodologies for tolerance allocation; (ii) illustrate and compare the nonparametric and parametric methods; land iii) assess the sensitivity of optimal tolerance allocations to changes in process model types, cost coefficient estimates, and manner of disposition of nonconforming product.     

考虑订单合批批量的在线制造商承诺交货期决策研究

承诺交货期策略即向所有顾客承诺一致的交货时间是在线制造商最常用的基于时间的竞争策略。制造商通过调整运营参数来改变交货时间以实现向顾客承诺的交货期。基于运营批量对生产提前期的影响,本文构建了考虑订单合批批量的承诺交货期决策模型,分析了各种参数对生产提前期与运输提前期决策的影响。研究表明,库存成本、单位产品的加工时间、顾客需求的价格敏感性和时间敏感性系数等参数对于在线制造商的生产提前期和运输提前期决策往往具有不同的影响。最后本文的算例验证了研究的结论。     

Supplier development or supplier switching?

We study a firm's cost-based sourcing decision of whether to invest in an incumbent supplier or switch to an alternative supplier in order to realise lower purchasing costs. In isolation, it can be shown that the development of an incumbent supplier (i.e., a cooperative investment) becomes more attractive, the higher the uncertainty about the price the buying firm can realise on the market and the incumbent supplier's cost. Likewise, switching to an alternative supplier becomes more attractive, the higher the expected value of and the uncertainty about the buying firm's market price. For comparing these two sourcing strategies simultaneously we provide a profit-maximising framework for the buying firm that shows that switching is less recommendable the higher the variance of the incumbent's cost and if the uncertain maximum demand is negatively correlated with the uncertain incumbent supplier's cost. Overall, our study substantially expands the frequently followed approach of basing supplier development versus supplier switching decisions merely on strategic and qualitative considerations.     

Applying an electromagnetism-like mechanism algorithm on parameter optimisation of a multi-pass milling process

Multi-pass milling is a common manufacturing process in practical production. Parameter optimisation is of great significance since the parameters largely affect the production time, quality, cost and some other process performance measures. However, the parameter optimisation of the multi-pass milling process is a nonlinear constrained optimisation problem. It is very difficult to obtain satisfactory results by the traditional optimisation methods. Therefore, in this paper, a new optimisation technique based on the electromagnetism-like mechanism (EM) algorithm is proposed to solve the parameter optimisation problem in a multi-pass milling process. The EM algorithm is a population based meta-heuristic algorithm for unconstrained optimisation problems. As the parameter optimisation problem is a constrained problem, the proposed approach handles the constraints of the problem by improving the charge calculation formula combined with the feasibility and dominance rules at the same time. This paper also puts forward flexible cutting strategies to simultaneously optimise the depth of cut for each pass, cutting speed and feed to improve solutions. A case study is presented to verify the effectiveness of the proposed approach. The results show that the proposed method is better than other algorithms and achieves significant improvement.     

Pre-positioning of relief inventories: a multi-product newsvendor approach

Inventory pre-positioning is critical to quickly and efficiently responding to potential disasters. This paper considers a NPO (a relief agent) that requires stockpiling multiple products for responding multiple potential disaster events. By employing the multi-product newsvendor (MPNV) approach, this paper establishes a multiple relief materials’ storage model that aims to minimise the expected total cost of the NPO. Our model acknowledges that the occurrence of a disaster, the demand after a disaster and the donation after a disaster are uncertain. Given the no-budget constraint, this paper shows the implicit conditions that determine the optimal solutions; for the case with a budget constraint, the paper develops a two-binary iterative approach to solve the model with a budget constraint. Numerical examples are conducted to investigate the impacts of model parameters. The paper further proposes a flexible storage policy, in which the NPO and the supplier jointly stockpile relief materials. The optimal solution of the case with the flexible stockpiling policy is also characterised. Moreover, this paper shows the policy implementation can simultaneously increase the performance of the NPO and the supplier; and both players of the supply chain prefer that the supplier solely holds all inventory.     

The economic lot and delivery scheduling problem: models for nested schedules

We investigate the problem of simultaneously determining schedules for the production of several assembly components at a captive supplier and delivery of those components to the customer. We consider situations in which production economies of scale in the form of setup costs and/or setup times make it desirable for the supplier to produce in batches that are larger than the desired order quantity of the customer. The objective is to minimize the average cost per unit time of transportation, inventory at both the customer and the supplier, and, where applicable, setup costs.

We develop a heuristic solution procedure and a lower bounding approach for this problem. We also report experimental results that indicate that the heuristic provides solutions close to the lower bound in most instances. Our results provide a means to answer the often-asked question of whether just-in-time suppliers are (or should be) asked to hold inventory for their customers, and the question of how much setup costs and setup times need to be reduced so that the suppliers no longer need to hold that inventory.     

The multilocation transshipment problem

We consider a supply chain, which consists of several retailers and one supplier. The retailers, who possibly differ in their cost and demand parameters, may be coordinated through replenishment strategies and transshipments, that is, movement of a product among the locations at the same echelon level. We prove that in order to minimize the expected long-run average cost for this system, an optimal replenishment policy is for each retailer to follow an order-up-to S policy. Furthermore, we demonstrate how the values of the order-up-to quantities can be calculated using a sample-path-based optimization procedure. Given an order-up-to S policy, we show how to determine an optimal transshipment policy, using a linear programming/network flow framework. Such a combined numerical approach allows us to study complex and large systems.     

Switchgear component commonality design based on trade-off analysis among inventory level,delivery lead-time and product performance

The shortening of product delivery lead-times can usually be achieved by keeping high-level components in inventory, however in small-volume production systems, maintaining such inventories is often a costly as well as a risky business strategy. If the risk of maintaining unsold inventory can be decreased, even small-volume manufacturers may be able to justify holding more significant quantities of versatile inventory. This paper discusses a component commonality effect to breakthrough the trade-off relationship between inventory levels and delivery lead-times for such small-volume production systems. By using the same component in different products, inventory maintenance costs can be dramatically reduced, but component commonality design problems are inherently complex, since excessive module commonality may lead to lower product performances, and there are trade-off relationships between product performance and cost reductions obtained through component commonality. In this paper, such a design problem is formulated as a multiobjective component commonality design optimisation problem considering inventory level, delivery lead-time and product performance, and the optimal solutions are obtained as a Pareto optimal solution set. Detailed procedures concerning the proposed design method, including inventory simulation, are discussed and developed for a switchgear design problem. Finally, an example switchgear design problem is solved to illustrate that optimal use of component commonalities across different modules can significantly reduce inventory costs, while also shortening product delivery lead-times.