交货期可以指派的供应链排序问题

考虑了由一个制造商和多个客户组成的供应链系统.每个客户有多个订单交给制造商加工,且每个客户有一个可以接受的完工订单到达时间.制造商可以与客户进行协商来选定合适的交货期.完工的订单是采用直接运输方式分批配送的,每一批配送需要花费一定的时间和费用.目标是对每个订单指派合适的交货期,并且进行生产和配送的排序,以极小化总的交货期指派费用,订单误工费用与配送费用的和.考虑了多种情况,分别给出了相应的算法.     

带交货期的工件族生产与配送的排序问题

本文考虑了多个客户订购不同种类的工件,工件生产完后需要运输到客户的单机供应链排序问题.由于工件属于不同的种类,在加工不同种类工件前要有一个准备时间.每个客户分布在不同位置,客户的每个工件都有一个交货期,工件是分批配送的,每一批配送需要花费一定的时间及费用.考虑了两个与交货期有关的目标函数,分别给出了它们的最优算法.     

具有学习效应的三层供应链排序问题

研究了具有学习效应的三层供应链排序问题. 多个客户分布在不同位置,每个客户都有订 单需要制造商进行生产. 制造商需要针对每一个不同订单的客户从不同的地方进购对应的原材料进行生产,生产完工后需要利用有限的车辆将工件运输到相应客户处. 要求每辆运输车装载尽可 能多的货物才开始运输. 利用动态规划算法研究了最大流程时间、总流程时间以及最大延迟三个目标函数.     

不确定条件下双目标组批生产的交货期设置研究

交货期是调度方法的函数,因而具有不确定性.研究变批量、变批次、变生产能力下,单阶段、双目标有条件相容组批的交货期设置问题,将它转化为订单投放策略和调度模式研究.建立了一个基于目标的双目标订单投放策略数学模型.采用目标序列优先方法进行双目标求解,用两种调度模式求出区间值,进行最优交货期逼近.模式1:松弛掉产品加工约束条件,基于负荷考虑、给出离散生产模式下订单完工率最大的订单排序算法,算法综合考虑了任务紧急程度、可调度性、重要度和流程时间最短四个方面,得到区间的一个端点.模式2是有条件相容的启发式组批调度算法,即通过聚类计算将订单安排问题转化为多队列调度问题,将新来订单的投放转化为某个队列的插单和批量分割问题,不同队列中批的投产顺序由批中优先级最高的订单决定,并在能力约束下进行批量分割计算,得到区间的另一个端点,结合流程可靠性求出区间.实例证明,模式2的交货期设置小,订单完工率和生产率高.     

具有多个制造商和分批配送的同类机排序问题

考虑了同类机环境下多个工件加工和配送的排序问题.有多个制造商分布在不同位置,每个制造商处有一台机器可以加工工件.不同的机器对应着不同的加工速度和加工费用.工件生产完后需要运输到客户处,每一批配送需要花费一定的时间和费用.研究了排序理论中主要的3个目标函数,分析了问题的复杂性,对于这些问题给出了它们的最优算法.     

应急管理中车辆受限的生产_库存及配送整合模型

针对突发事件发生后,救灾物资不足、车辆数量及容量有限的情况,本文考虑了制造商生产、包装新的救灾物资,构造了车辆返回制造商需要等待订单完成生产的时间函数,建立了一个生产、库存及配送整合的混合整数规划模型。该模型由原材料供应商、制造商、配送中心及客户需求点四部分构成,以完成原材料的运输、制造商中的订单生产并运送到需求点及配送中心的库存订单运送到需求点的总花费时间最短为目标。本文将模型分为两层子模型进行求解:第一层模型采用改进的遗传算法求解;第二层模型采用隐枚举法求解。最后给出一个具体的案例以验证模型的合理性及算法的有效性。     

订单带多类工件时的最大迟后问题

本文考虑多工类工件的单机排序问题,每一客户提供一由若干工件组成的订单,总共n个工件又分成k个类,当机器从加工某类中的工件转向加工不同于它的第i类工件时需一调整时间S_i,每一订单有一给定的应交工时间,所考虑目标函数是使订单的最大迟后最小,相应这一排序问题的三种模式,文中分别给出了一多项式算法,分枝定界算法和动态规划解法。     

考虑可拆分订单及加工类型匹配的平行机调度决策

介绍了制造资源共享环境下共享平台的生产和运作，以1688淘平台为例，将共享平台抽象刻画为考虑可拆分订单和加工类型匹配的平行机调度问题。客户将订单下达到共享平台上，供应商将闲置机器放在平台的资源池里。不同机器具有相同的加工速度但只能加工与其类型匹配的个性化订单，因此，需要决策使用哪些机器。一旦使用某台机器，会产生固定的加工或租赁成本。每个订单可以被拆分成整数长度的多个子订单，并在可用的机器上同时被加工。以最小化所使用机器的总加工成本和订单的总完工时间之和为优化目标，建立了一个整数线性规划模型。对于小规模实例，CPLEX可以求得最优解；对于中规模和大规模例子，提出了基于机器加工能力的贪婪算法和遗传算法。数据实验表明，基于机器加工能力的贪婪算法是一种高效且有效的算法。此外，尽量选择加工能力强的机器加工订单；将订单拆分在多台机器上并行加工可以缩短订单的完成时间。     

一个非常规目标函数的单机随机调度的最优策略

本文考虑了n个工件在同一台机器上加工的调度问题 ,其中工件的加工时间和交货期都是具有任意分布的随机变量 .我们考虑了一个非常规目标函数 ,其中工件的权数与平均加工时间成比例 .在工件的交货期与加工时间满足相容条件下 ,得到了个简单的最优排序策略 .     

单机带有可拒绝的供应链排序问题

考虑了单机上带有工件拒绝的供应链排序问题.有多个客户分布在不同区域,每个客户都有一定数量的工件需要在一台机器上进行加工.制造商可以拒绝加工一些工件,但要支付相应的拒绝费用.工件生产完后需要运输到相应的客户处,每一批配送需要花费一定的时间和费用.我们研究了排序理论中主要的几个目标函数,构建了单机情况下的具体模型,分析了问题的复杂性,对具体的问题给出了它们的最优算法.     

Minimizing Labor Requirements in a Periodic Vehicle Loading Problem

In this paper, we address a logistics problem that a manufacturer of auto parts in the north of Spain described to the authors. The manufacturer stores products in its warehouse until customers retrieve them. The customers and the manufacturer agree upon an order pickup frequency. The problem is to find the best pickup schedule, which consists of the days and times during the day that each customer is expected to retrieve his/her order. For a given planning horizon, the optimization problem is to minimize the labor requirements to load the vehicles that the customers use to pick up their orders. Heuristically, we approach this situation as a decision problem in two levels. At the first level, customers are assigned to a calendar, consisting of a set of days with the required frequency during the planning horizon. Then, for each day, the decision at the second level is to assign each customer to a time slot. The busiest time slot determines the labor requirement for a given day. Therefore, once customers have been assigned to particular days in the planning horizon, the second-level decision is a multiprocessor scheduling problem, where each time slot is the equivalent of a processor, and where the objective is to minimize the makespan. A metaheuristic procedure is developed for the problem of minimizing labor requirements in this periodic vehicle-loading problem and artificial as well as real data are used to assess its performance.     

Channel Coordination with Cooperative Advertising Considering Effect of Advertising on Willingness to Pay

In this paper, cooperative advertising in a manufacturer–retailer supply chain is studied. Advertising can enhance willingness to pay (WTP) of customers. This trade-off between the benefits of increasing WTP of customers and the advertising expenditure is a key to understanding the retailers optimal advertising decision. On the other hand, it is interesting to understand in which condition supporting the retailer for his advertising expenditure is beneficial for the manufacturer. In this study, in order to capture pricing and advertising strategies of the channel member, three non-cooperative games including Nash, Stackelberg retailer and Stackelberg manufacturer game-theoretic models are established. In spite of the related studies which restrict price in order to prevent negative demand, the proposed model allows channel members to increase their prices by enhancing WTP of customers. In this study, contrary to similar additive form demand functions applied in the co-op ad literature which limits their studies for cases that profit function is concave with respect to variables, optimal prices and advertising strategies are obtained for all the solution space. Surprisingly for the very high values of the advertising effect coefficient, a finite optimal advertising expenditure is achieved.     

Production and availability policies through the Markov Decision Process and myopic methods for contractual and selective orders

In this paper, we consider a supply chain with one manufacturer, one retailer, and some online customers. In addition to supplying the retailer, manufacturers may selectively take orders from individuals online. Through the Markov Decision Process, we explore the optimal production and availability policy for a manufacturer to determine whether to produce one more unit of products and whether to indicate “in stock” or “out of stock” on website. We measure the benefits and influences of adding online customers with and without the retailer’s inventory information sharing. We also simulate the production and availability policy via a myopic method, which can be implemented easily in the real world. Prediction of simple switching functions for the production and availability is proposed. We find the information sharing, production capacity and unit profit from online orders are the primary factors influencing manufacturer profits and optimal policy. The manufacturer might reserve 50% production capacity for contractual orders from the retailer and devote the remaining capacity to selective orders from spontaneous online customers.     

Inventory competition and allocation in a multi-channel distribution system

Consider a supply chain involving one manufacturer and one independent retailer. The manufacturer distributes her product to the end consumer through the independent retailer as well as through her direct channel. Each of the two channels faces a stochastic demand. If one channel is out of stock, a fraction of the unsatisfied customers visit the other channel, which induces inventory competition between the channels. Under the scenario described above, will the manufacturer ever undercut the retailer’s order when the capacity is infinite? What are the equilibria of the game? How does a capacity constraint affect the equilibrium outcome? What is the optimal inventory allocation strategy for the manufacturer? Using a game theoretic model we seek answers to the above questions. Both the capacitated and the infinite capacity games are considered. We establish the necessary condition for a manufacturer to undercut a retailer’s order and show that a manufacturer may deny the retailer of inventory even when the capacity is ample. We show that there can be an equilibrium in the capacitated game where a manufacturer might not use the entire capacity and still deny a retailer inventory. We also show that a mild capacity constraint may make both parties better off and thereby increase the total supply chain profit. We develop a simple yet practical contract called the reverse revenue sharing contract and show that along with a fixed franchise fee this contract can coordinates our decentralized supply chain.     

The final order problem for repairable spare parts under condemnation

We consider a manufacturer of complex machines that offers service contracts to her customers, committing herself to repair failed spare parts throughout a fixed service period. The suppliers of spare parts often discontinue the production of some parts as technology advances and ask the manufacturer to place a final order. We address the problem of determining final orders for such spare parts. The parts that we consider are repairable, but they are subject to the risk of condemnation. We build a transient Markovian model to represent the problem for a repairable spare part with a certain repair probability and repair lead time and we present some approximations that allow for further real-life characteristics to be included. Furthermore, an approximate model that can be computed more efficiently is presented, and the sensitivity of the results obtained with respect to the problem parameters is discussed, helping us develop several managerial insights.     

Capacity reservation contracts for high-tech industry

Capacity reservation provides a risk-sharing mechanism that encourages a manufacturer to expand its capacity more. We propose a deductible reservation (DR) contract where customers reserve future capacity with a fee that is deductible from the purchasing price. The manufacturer’s ex ante announcement of the “excess” capacity that she will have in addition to the reservation amount is a unique feature of the DR contract. An individually rational DR contract that provides channel coordination always exists. Since there is a unique Nash equilibrium for the reservation game among multiple customers, the main results of the one-customer case can be extended to the n-customer case. The DR contract is compared with another capacity reservation contract called take-or-pay. While the manufacturer may gain more profit under a take-or-pay contract, there may not be a channel-coordinated contract that is also individually rational for the customer. Finally, the similarities and differences between the capacity reservation contracts and other well-known supply contracts are discussed.     

Environmental corporate responsibility for investments evaluation: an alternative multi-objective programming model

The manufacturer who is a supplier of trade credit may face non-payment risk from customers and a capital shortage problem simultaneously. Trade credit insurance, as one of the most important risk management tools, has been widely used in companies’ daily operation. In this study, the manufacturer who allows customers to delay payment for goods already delivered purchases trade credit insurance to transfer and reduce non-payment risk and borrows money from a bank to accommodate the capital constraint problem. The Stackelberg game and loss-averse theory are used to establish a newsboy model including trade credit insurance, and the optimal insurance coverage and total sales of the manufacturer are thereby investigated. Subsequently, the interest rate decision of the bank under different risk-averse situations is also characterized. We find that the interest rate set by a loss-averse bank is equal to or greater than that given by a risk-neutral bank. The use of trade credit insurance can help the manufacturer expand sales and dramatically reduce its default risk. Both the bank and the manufacturer are better off due to the use of trade credit insurance, but contrary to what one might expect, the bank prefers giving a higher interest rate to the manufacturer when the premium rate is in a reasonable region, which indicates that the manufacturer cannot use the insurance to negotiate better financing terms.     

Real-time order tracking for supply systems with multiple transportation stages

This paper presents a stochastic model that evaluates the value of real-time shipment tracking information for supply systems that consist of a retailer, a manufacturer, and multiple stages of transportation. The retailer aggregates demand for a single product from end customers and places orders on the manufacturer. Orders received by the manufacturer may take several time periods before they are fulfilled. Shipments dispatched by the manufacturer move through multiple stages before they reach the retailer, where each stage represents a physical location or a step in the replenishment process. The lead time for a new order depends on the number of unshipped orders at the manufacturer’s site and the number and location of all shipments in transportation. The analytic model uses real-time information on the number of orders unfulfilled at the manufacturer’s site, as well as the location of shipments to the retailer, to determine the ordering policy that minimizes the long-run average cost for the retailer. It is shown that the long-run average cost is lower with real-time tracking information, and that the cost savings are substantial for a number of situations. The model also provides some guidelines for operating this supply system under various scenarios. Numerical examples demonstrate that when there is a lack of information it is better for the retailer to order every time period, but with full information on the status in the supply system it is not always necessary for the retailer to order every time period to lower the long-run average cost.     

Studying the interdependence of contractual and operational flexibilities in the market of specialty chemicals

This paper focuses on the market of specialty chemicals and deals with the joint investigation and valuation of contractual and operational flexibilities from a manufacturers’ point of view. In this market, customized services related to research, development and manufacturing of chemicals, intermediates and active pharmaceutical ingredients are offered to a small number of customers. Traditionally, customers are granted a large degree of freedom with respect to demand quantity and time exposing the manufacturer to high uncertainty and financial risk. Using a model-based approach we quantify the effect of this contractual flexibility and relate it to the manufacturing flexibility concerning capacity allocation. Through the valuation of these flexibilities we provide first insights for the manufacturer on which customer requests to accept, how to set up the associated contracts with the customers and how to allocate capacity for a given portfolio of products.