Fulfillment of Rush Customer Orders under Limited Capacity

Customer demand fulfillment is the business process within a company that determines how the customer demand is fulfilled. A rush order is the last minute customer order after the production plan of a company has been concluded. For these rush orders, appropriate and reasonable response is imperative as it could put strain on customer relationship and services. A good and positive response could help the company to build and retain its market share in today’s highly competitive markets. A model aims at decreasing the product inventory cost is proposed in this paper. In this model, the prioritized fulfillment sequence of rush customer demands can be searched in terms of the product inventory cost. The paper focuses on two main issues: the available-to-promise (ATP) based fulfillment ability and the prioritized fulfillment of customer demands. For ATP based fulfillment, a dynamic bill-of-material (BOM) is proposed to handle the complicated issues of BOM, BOM explosion and production capacity. By means of dynamic BOM, material availability as well as production capacity can be taken into consideration simultaneously and efficiently. Two methods, mathematical optimization and heuristic algorithm, are constructed and elaborated on in the second issue. The proposed model allows companies to prioritize customer rush orders in terms of product inventory cost.Singapore-MIT Alliance (SMA

Algorithms for On-line Order Batching in an Order-Picking Warehouse

In manual order picking systems, order pickers walk or ride through a distribution warehouse in order to collect items required by (internal or external) customers. Order batching consists of combining these – indivisible – customer orders into picking orders. With respect to order batching, two problem types can be distinguished: In off-line (static) batching all customer orders are known in advance. In on-line (dynamic) batching customer orders become available dynamically over time. This report considers an on-line order batching problem in which the total completion time of all customer orders arriving within a certain time period has to be minimized. The author shows how heuristic approaches for the off-line order batching can be modified in order to deal with the on-line situation. A competitive analysis shows that every on-line algorithm for this problem is at least 2-competitive. Moreover, this bound is tight if an optimal batching algorithm is used. The proposed algorithms are evaluated in a series of extensive numerical experiments. It is demonstrated that the choice of an appropriate batching method can lead to a substantial reduction of the completion time of a set of customer orders.Warehouse Management, Order Picking, Order Batching, On-line Optimization

Metaheuristics for the Order Batching Problem in Manual Order Picking Systems

In manual order picking systems, order pickers walk or drive through a distribution warehouse in order to collect items which are requested by (internal or external) customers. In order to perform these operations effciently, it is usually required that customer orders are combined into (more substantial) picking orders of limited size. The Order Batching Problem considered in this paper deals with the question of how a given set of customer orders should be combined such that the total length of all tours is minimized which are necessary to collect all items. The authors introduce two metaheuristic approaches for the solution of this problem; the rst one is based on Iterated Local Search, the second one on Ant Colony Optimization. In a series of extensive numerical experiments, the newly developed approaches are benchmarked against classic solution methods. It is demonstrated that the proposed methods are not only superior to existing methods, but provide solutions which may allow for operating distribution warehouses signicantly more effcient.Warehouse Management, Order Picking, Order Batching, Iterated Local Search, Ant Colony Optimization

A distributed multi-agent framework for shared resources scheduling

Nowadays, manufacturers have to share some of their resources with partners due to the competitive economic environment. The management of the availability periods of shared resources causes a problem because it is achieved by the scheduling systems which assume a local environment where all resources are on the same site. Therefore, distributed scheduling with shared resources is an important research topic in recent years. In this communication, we introduce the architecture and behavior of DSCEP framework (distributed, supervisor, customer, environment, and producer) under shared resources situation with disturbances. We are using a simple example of manufacturing system to illustrate the ability of DSCEP framework to solve the shared resources scheduling problem in complex systems

Simulation model of the logistic distribution in a medical oxygen supply chain

Research activities on operations management in the last years are always more dedicated to supply chain and logistics optimization models. The study belongs to this branch and describes the problems related to a re-configuration of the distribution net in a company that produces medical oxygen cylinders for Italian market. The enterprise is particularly sensible to the optimization of supplying processes due to the characteristics of its product, as any delay in the delivery could create dangerous health situation for patients. The work has the objective to realize a software for supply chain management that could be a decision support system, analyzing strategic impacts that changes in distribution system create. In details, the model shows the differences in service level in case of closing one or more factories and the relative necessary changes in logistics net. The paper is articulated in the following parts: • analysis of company and construction of simulation model; • study of classic operation research techniques to solve dynamic vehicle routing problems; • description of possible scenes derived by strategic decision in closing factories; analysis of experiments and global conclusions and developments

Single-machine scheduling with stepwise tardiness costs and release times

We study a scheduling problem that belongs to the yard operations component of the railroad planning problems, namely the hump sequencing problem. The scheduling problem is characterized as a single-machine problem with stepwise tardiness cost objectives. This is a new scheduling criterion which is also relevant in the context of traditional machine scheduling problems. We produce complexity results that characterize some cases of the problem as pseudo-polynomially solvable. For the difficult-to-solve cases of the problem, we develop mathematical programming formulations, and propose heuristic algorithms. We test the formulations and heuristic algorithms on randomly generated single-machine scheduling problems and real-life datasets for the hump sequencing problem. Our experiments show promising results for both sets of problems

Minimizing weighted total earliness, total tardiness and setup costs

The paper considers a (static) portfolio system that satisfies adding-up contraints and the gross substitution theorem. The paper shows the relationship of the two conditions to the weak dominant diagonal property of the matrix of interest rate elasticities. This enables to investigate the impact of simultaneous changes in interest rates on the asset demands.