Coordinated supply chain scheduling

A mixed integer programming approach is proposed for a long-term, integrated scheduling of material manufacturing, material supply and product assembly in a customer driven supply chain. The supply chain consists of three distinct stages: manufacturer/supplier of product-specific materials (parts), producer where finished products are assembled according to customer orders and a set of customers who generate final demand for the products. The manufacturing stage consists of identical production lines in parallel and the producer stage is a flexible assembly line. The overall problem is how to coordinate manufacturing and supply of parts and assembly of products such that the total supply chain inventory holding cost and the production line start-up and parts shipping costs are minimized. A monolithic approach, where the manufacturing, supply and assembly schedules are determined simultaneously, is compared with a hierarchical approach. Numerical examples modeled after a real-world integrated scheduling in a customer driven supply chain in the electronics industry are presented and some computational results are reported.     

A two-stage model for the design of supply chain networks

This research aims to develop an analytical model of the supplier selection process in designing a supply chain network. The constraints on the capacity of each potential supplier are considered in the process. The assumed objective of the supply chain is to minimize the level of customer dissatisfaction, which is evaluated by two performance criteria: (i) price and (ii) delivery lead time. The overall model operates at two levels of decision-making: the operational level and the chain level. The operational level concerns decisions related to optimizing the manufacturing and logistical activities of each potential supplier in order to meet the customer's requirements. At the chain level, all the bids from potential suppliers are evaluated and the final configuration of the supply chain is determined. The structure of the chain depends on the product specifications and on the customer's order size. An optimal solution in terms of the models for the two levels can be obtained by using a mixed-integer programming technique.     

A model for supply management of agile manufacturing supply chains

This paper addresses the configuration problem of Manufacturing Supply Chains (MSC) with reference to the supply planning issue. Assuming that the manufacturing system is composed of different stages, we present a technique for the strategic management of the chain addressing supply planning and allowing the improvement of the MSC agility in terms of ability in reconfiguration to meet performance. More in detail, we enhance a previous design method by some of the authors that employs digraph modeling and integer linear programming to optimally design the MSC. The original approach avoids supply chain disruption and stock out and, at the same time, can manage spare parts distribution. In order to take into account the level of demands and maximum production capacities with single/multiple sourcing, in this new formulation we introduce supplier capacity constraints. A case study is presented describing the optimal MSC configuration of an Italian manufacturing firm. The obtained results show that the design method provides managers with key answers to issues related to the supply chain strategic configuration and agility, e.g., choosing the right location for distributors and retailers for enhanced MSC flexibility and performance.     

A weighted max-min model for fuzzy multi-objective supplier selection in a supply chain

Supplier selection is one of the most important activities of purchasing departments. This importance is increased even more by new strategies in a supply chain. Supplier selection is a multi-criteria decision making problem in which criteria have different relative importance. In practice, for supplier selection problems, many input information are not known precisely. The fuzzy set theories can be employed due to the presence of vagueness and imprecision of information. A weighted max-min fuzzy model is developed to handle effectively the vagueness of input data and different weights of criteria in this problem. Due to this model, the achievement level of objective functions matches the relative importance of the objective functions. In this paper, an analytic hierarchy process (AHP) is used to determine the weights of criteria. The proposed model can help the decision maker (DM) to find out the appropriate order to each supplier, and allows the purchasing manager(s) to manage supply chain performance on cost, quality and service. The model is explained by an illustrative example.     

Dynamic supply chain coordination under consignment and vendor-managed inventory in retailer-centric B2B electronic markets

This study examines the dynamic performance of vertically decentralized two-echelon channel coordination for deteriorating goods under consignment and vendor-managed inventory (VMI) contracts with revenue sharing from retailer-centric business-to-business transactions in both traditional markets and electronic markets (EMs). The research presents the profit-maximization problem and devises a method for making cross-enterprise dynamic joint decisions by combining calculus with dynamic programming for a retailer-led Stackelberg supply chain under cooperative and non-cooperative game settings over a multi-period planning horizon. The applicability of the proposed model is assessed using a case study involving a highly perishable product, sliced raw fish, in a supply chain comprising a regional seafood supplier and a local store belonging to a large national retail chain. The analytical results show that, in a cooperative setting, the EM with a consigned revenue-sharing VMI contract tends to achieve lower retail prices, larger stock quantity, improved channel efficiency, and increases in both retailer and supplier profits through an additional one-part tariff. Additionally, consumers benefit from lower retail prices and society benefits from increased overall channel profits in the cooperative channel and EM.     

供应中断下双源采购的供应链契约设计

考虑由一个制造商和两个供应商构成的两级供应链契约设计问题,将可靠性服从随机分布的供应商作为主供应商,将完全中断供应商作为次供应商,建立以利润最大化为目标的签约和执行两阶段博弈的动态规划模型,得到制造商的最优契约设计。制造商根据产品零售价格的变化灵活做出只与一个供应商签约、与两个供应商同时签约或都不签约的决定,供应商根据契约设计内容决定自己的最优生产规模。研究表明：供应商最优生产规模与产品的单位生产成本呈负相关,与单位变动支付和单位惩罚成本呈正相关;次供应商的订货量与其本身的可靠性呈正相关,与主供应商的可靠性呈负相关;供应商的固定支付与其相应的可靠性呈负相关。     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

An integrated production-distribution model for a deteriorating inventory item

We develop an integrated production-distribution model for a deteriorating item in a two-echelon supply chain. The supplier’s production batch size is restricted to an integer multiple of the discrete delivery lot quantity to the buyer. Exact cost functions for the supplier, the buyer and the entire supply chain are developed. These lead to the determination of individual optimal policies, as well as the optimal policy for the overall, integrated supply chain. We outline a procedure for determining the optimal supply chain decisions with the objective of minimizing the total system cost. Our approach is illustrated through a numerical example.     

Supply chain risk, simulation, and vendor selection

This paper considers three types of risk evaluation models within supply chains: chance constrained programming (CCP), data envelopment analysis (DEA), and multi-objective programming (MOP) models. Various risks are modeled in the form of probability and simulation of specific probability distribution in risk-embedded attributes is conducted in these three types of risk evaluation models. We model a supply chain consisting of three levels and use simulated data with representative distributions. Results from three models as well as simulation models are compared and analysis is conducted. The results show that the proposed approach allows decision makers to perform trade-off analysis among expected costs, quality acceptance levels, and on-time delivery distributions. It also provides alternative tools to evaluate and improve supplier selection decisions in an uncertain supply chain environment.     

Supply chain scheduling and coordination with dual delivery modes and inventory storage cost

We study a two-echelon supply chain scheduling problem in which a manufacturer acquires supplies from an upstream supplier and processes orders from the downstream retailers. The supply chain sells a single short-life product in a single season. We consider the scenario where the manufacturer can only accept some of the orders from the retailers due to its supplier's common production time window and its own two common production and delivery time windows. The upstream supplier processes materials and delivers the semi-finished products to the manufacturer within its time window. Then the manufacturer further processes these products to produce finished products and delivers them to the retailers within its two time windows, where one window is for production and normal delivery, and the other is for production and express delivery. Having to store the materials before processing them, the supplier incurs a storage cost, which depends on the order size and storage time. The manufacturer pays the transportation cost for delivering the finished products to the retailers. Due to double marginalization, the performance of the supply chain is sub-optimal. We model the supply chain problem as a flow shop scheduling problem with multiple common time windows. We derive some dominance properties and establish some theorems that help solve the sequencing problems for the orders and eliminate the idle time among the orders. Based on these results, we develop fast pseudo-polynomial dynamic algorithms to optimally solve the problem. We prove that the problem is NP-hard in the ordinary sense only. We develop two practically relevant and robust methods for the supply chain to achieve optimal profit-making performance through channel coordination.     

A strategic-tactical model for the supply chain design in the delocalization context: Mathematical formulation and a case study

In this paper, we propose a mathematical model for the design of supply chains in the delocalization context. Our main objective is to develop a strategic-tactical supply chain design model that integrates all the relevant components that characterize the delocalization problem. We adopt the activity based approach to model the problem and we focus on the logistic decisions of activity location, technology choice, supplier selection, etc., and the financial decisions of transfer pricing, transportation costs allocation, etc. The mathematical formulation is illustrated by a case study from the automotive sector. A comparison between the model solution and the real decisions is used to prove the applicability and the utility of the proposed model.     

Incorporating uncertainty into a supplier selection problem

Supplier selection is an important strategic supply chain design decision. Incorporating uncertainty of demand and supplier capacity into the optimization model results in a robust selection of suppliers. A two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts. Both models include several objectives and strive to balance a small number of suppliers with the risk of not being able to meet demand. The SP model is scenario-based and uses penalty coefficients whereas the CCP model assumes a probability distribution and constrains the probability of not meeting demand. Both formulations improve on a deterministic mixed integer linear program and give the decision maker a more complete picture of tradeoffs between cost, system reliability and other factors. We present Pareto-optimal solutions for a sample problem to demonstrate the benefits of the SP and CCP models. In order to describe the tradeoffs between costs and risks in an analytical form, we use multi-parametric programming techniques to more completely analyze the alternative Pareto-optimal supplier selection solutions in the CCP model. This analysis gives insights into the robustness of the solutions with respect to number of suppliers, costs and probability of not meeting demand.     

An integrated production–distribution model for the dynamic location and allocation problem with safety stock optimization

The design and management of a multi-stage production–distribution system is one of the most critical problems in logistics and in facility management. Companies need to be able to evaluate and design different configurations for their logistic networks as quickly as possible. This means coordinating the entire supply chain effectively in order to minimize costs and simultaneously optimize facilities location, the allocation of customer demand to production/distribution centers, the inbound and outbound transportation activities, the product flows between production and/or warehousing facilities, the reverse logistics activities, etc.Full optimization of supply chain is achieved by integrating strategic, tactical, and operational decision-making in terms of the design, management, and control of activities. The cost-based and mixed-integer programming model presented in this study has been developed to support management in making the following decisions: the number of facilities (e.g. warehousing systems, distribution centers), the choice of their locations and the assignment of customer demand to them, and also incorporate tactical decisions regarding inventory control, production rates, and service-level determination in a stochastic environment. This paper presents an original model for the dynamic location–allocation problem with control of customer service level and safety stock optimization. An experimental analysis identifies the most critical factors affecting the logistics cost, and to finish, an industrial application is illustrated demonstrating the effectiveness of the proposed optimization approach.     

基于改进TOPSIS法的供应商选择模型研究

为有效地帮助企业快速找到合适的供应商合作伙伴,采用直觉模糊集、评分函数等方法对TOPSIS评估法进行优化,并以此为基础建立了一种供应商选择模型。首先,采集和评估供应商的产品质量、产品价格、产品交货的可靠性、供应位置、财务情况、库存水平、劳资关系、发展能力和技术能力等相关信息,由专家给出主观评估信息,汇总为综合属性值;然后,通过直觉模糊熵确定各评估指标的权重;最后,综合考虑供应商选择决策过程中的多个目标和标准,应用改进TOPSIS法的对供应商进行分类选择。结果显示,基于改进TOPSIS法的供应商选择模型能够较准确地反映出各供应商的真实水平和对企业的潜在价值,可以有效地解决不确定条件下对供应商的选择问题,提高了供应商选择结果的可靠性。改进后的模型简便易行,具有良好的稳定性,对于合理制定企业供应商选择标准以及进一步优化决策模型具有一定的借鉴意义。     

Inter-temporal inventory competition and the effects of capacity constraints

This paper addresses an intertemporal inventory competition between a supplier (a provider, manufacturer) and a retailer engaged in a supply chain. The paper's focus is on the effect of capacity constraints on both parties when demands are seasonal. The paper provides a comparative study of two solution approaches, one is based on supply chain competition and the other is based on system wide optimization. Our results demonstrate that with dynamic inventory competition, the retailer reduces inventory costs by reducing the response period to higher demands while increasing the supply requests compared to the system-wide optimal approach. As a result, the supplier's inventory costs increase. An example illustrating these particular facets of the problem and its application is presented and discussed in light of the supplier and the retailer coordinating policies.     

Does a green supply chain improve corporate reputation? Empirical evidence from European manufacturing sectors

Managing supplier relationships in an environmentally responsible way may prevent risk of adverse publicity and reputational damage to the buying firm. Drawing on the stakeholder approach and the environmental management capability framework, the purpose of this paper is to gain further knowledge regarding the impact of strategies oriented to green supply chain management on a firm's corporate reputation. We test a set of hypotheses in a panel data of European manufacturing companies for a period of ten years. Our findings provide strong support for the premise that supplier selection, monitoring and partnership termination based on environmental criteria positively influence corporate reputation. Additionally, evidence suggests that the implementation of those strategies in an integral way as well as progressing towards the adoption of green supply chain management benefit a firm's reputation. This study has implications for theory and practice.     

An improved model for supplier selection under capacity constraint and multiple criteria

Ghodsypour and O'Brien [2001. The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International Journal of Production Economics 73(1), 15–27] study multiple sourcing problem with multiple criteria and capacitated suppliers. Considering the buyer's quality requirements as a constraint, they develop a mixed integer non-linear programming model to find the least-cost cyclic ordering policy for the buyer. They propose to solve the model by enumerating over all possible supplier combinations. Although the problem is interesting and their analysis is correct, we point out two issues with their assumptions, namely, capacitated suppliers and cyclic ordering policy. We discuss two different capacitated supplier settings: (i) long-run average annual capacity, and (ii) exact annual capacity. First, under long-run average annual capacity assumption we propose a model which provides the same or a better solution and is much easier to solve than their model. Then, we discuss how to modify our and their models to handle exact annual capacity assumption.     

Coping with time pressure in interfirm supply chain relationships

In today's evolving marketplace, firms must increasingly focus on developing responsiveness to meet customer demands. In the pursuit of such rapid response to customer needs, firms often demand that other members of their supply chain reduce cycle times of key business activities. Although tight deadlines are commonly imposed by customers, little is known about how supplier firms respond to such time pressure. Therefore, the purpose of this research was to learn more about the phenomenon of time pressure in interfirm relationships and determine how firms cope with this common situational constraint. Grounded theory methodology was utilized to discover a time pressure coping strategies taxonomy that is driven by evaluative criteria such as the frequency, magnitude, and attribution of time pressure. The model that emerged from this research provides information about the potential costs of leveraging interfirm relationships in order to achieve supply chain responsiveness.     

Supply contract with options

The purpose of this paper is to analyze the impact of an option contract for two companies of a supply chain: retailer and supplier. With an option contract the retailer orders a quantity of units and has the right to modify his order if necessary. A model to calculate the performance of an option contract in terms of contract value for the two companies engaged is presented. The two considered cases are multiple suppliers and one retailer, and one supplier and one retailer. The performance improvement obtained using this kind of contract is compared by simulation.     

Evaluation of 4PL operating models: A decision making approach based on 2-additive Choquet integral

By being a supply chain integrator who can assemble and manage the resources, capabilities, and technology of its own organization with those of complementary service providers, fourth party logistics (4PL) providers deliver comprehensive supply chain solutions and form an important option for business outsourcing. The adequate design of the partnership between companies in this type of outsourcing activities is essential. In order to support the effective usage of 4PL services, this paper proposes an analytical multiple criteria decision making approach to evaluate 4PL operating models. While decision criteria and their hierarchy were identified, it is observed that there exist interactions, e.g. simultaneous satisfaction of two or criteria is sometimes required. This situation can not be handled with traditional multi-criteria decision making methods which assume criteria independence. 2-additive Choquet integral is appropriate to model criteria interactions by pairs and is used in this study. The proposed framework is applied for a logistics company willing to expand its operations. Finally, an application is provided to demonstrate the potential of the methodology for 4PL operating model selection.