We study real-time demand fulfillment for networks consisting of multiple local warehouses, where spare parts of expensive technical systems are kept on stock for customers with different service contracts. Each service contract specifies a maximum response time in case of a failure and hourly penalty costs for contract violations. Part requests can be fulfilled from multiple local warehouses via a regular delivery, or from an external source with ample capacity via an expensive emergency delivery. The objective is to minimize delivery cost and penalty cost by smartly allocating items from the available network stock to arriving part requests. We propose a dynamic allocation rule that belongs to the class of one-step lookahead policies. To approximate the optimal relative cost, we develop an iterative calculation scheme that estimates the expected total cost over an infinite time horizon, assuming that future demands are fulfilled according to a simple static allocation rule. In a series of numerical experiments, we compare our dynamic allocation rule with the optimal allocation rule, and a simple but widely used static allocation rule. We show that the dynamic allocation rule has a small optimality gap and that it achieves an average cost reduction of 7.9% compared to the static allocation rule on a large test bed containing problem instances of real-life size. (C) 2013 Elsevier B.V. All rights reserved.

The primary objective of closed-loop supply chains (CLSC) is to improve the maximum economic benefit from end-of-use products. Nevertheless, the literature within this stream of research advocates that closing the loop also helps to mitigate the undesirable environmental footprint of supply chains. Therefore, closed-loop supply chains are assumed to be sustainable supply chains almost by definition. In this paper we analyse if and when this assumption holds. We illustrate our findings based on the Electric and Electronic Equipment (EEE) supply chain. For all phases of the supply chain, i.e. manufacturing, usage, transportation and end-of-life activities, we assess the magnitude of the environmental impacts, based on a single environmental metric, namely the Cumulative Energy Demand (CED). Given the environmental hot-spots in the Electric and Electronic Equipment supply chain, we propose useful extensions for existing CLSC optimisation models to ensure that closed-loop supply chains are at the same time sustainable supply chains.

Recent literature on sustainable logistics networks points to two important questions: (i) How to spot the preferred solution(s) balancing environmental and business concerns? (ii) How to improve the understanding of the trade-offs between these two dimensions? We posit that a visual exploration of the efficient frontier and trade-offs between profitability and environmental impacts are particularly suitable to answer these two questions. The visual representation of the efficient frontier, however, presents two challenges. The first is to obtain a good approximation for such frontier without enumerating all extreme efficient solutions. The second is to obtain a good visual representation of the efficient frontier. We propose a two-phased heuristic to handle these two problems. The algorithm is designed for the multi-objective linear problem with three objectives: minimize costs, cumulative energy demand and waste in a reverse logistics network. We illustrate our approach by designing a complex recycling logistics network in Germany.

Consumers and legislation have pushed companies to re-design their logistic networks in order to mitigate negative environmental impacts. The objective in the design of logistic networks has changed, therefore, from cost minimization only, to cost and environmental impact minimization. The objective of this paper is to develop a framework for the design and evaluation of sustainable logistic networks, in which profitability and environmental impacts are balanced. In this paper, we review the main activities affecting environmental performance and cost efficiency in logistic networks, we show the advantages of using multi-objective programming (MOP) to design sustainable networks, we present the expected computational difficulties of using the MOP approach in the design of sustainable networks, and we introduce a technique, based on the commonalities between data envelopment analysis (DEA) and MOP, to evaluate the efficiency of existing logistic networks. The European pulp and paper industry will be used to illustrate our findings.

This review addresses the specific supply chain management issues of Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and reviews corresponding quantitative models. In this way, we aim to enhance the understanding of multi-channel e-fulfillment and to identify gaps between relevant managerial issues and academic literature, thereby indicating directions for future research. One of the recurrent patterns in today’s e-commerce operations is the combination of ‘bricks-and-clicks’, the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies need to master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operations decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering.

Introduction Closing supply chains refers to taking care of items once they are no longer desired or can no longer be used by their user. Smart management of closed-loop supply chains means profitable

Statistica NeerlandicaVolume 54, Issue 2 p. 116-126 Jaap wessels – his life with stochastic processes J. A. E. E. Van Nunen, J. A. E. E. Van Nunen Erasmus University, The NetherlandsSearch for more papers by this authorJ. Van Der Wal, J. Van Der Wal Erasmus University, The NetherlandsSearch for more papers by this author J. A. E. E. Van Nunen, J. A. E. E. Van Nunen Erasmus University, The NetherlandsSearch for more papers by this authorJ. Van Der Wal, J. Van Der Wal Erasmus University, The NetherlandsSearch for more papers by this author First published: 28 June 2008 https://doi.org/10.1111/1467-9574.00131AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Volume54, Issue2July 2000Pages 116-126 RelatedInformation

In this paper we investigate product remanufacturing in general, and the influence of product remanufacturing on production planning and inventory control. The contents of this paper are as follows: (i) we discuss some important issues concerning the application of product remanufacturing in industry, (ii) we review the literature on production planning and inventory control models that apply to the situation of remanufacturing, (iii) we investigate the steady-state behaviour of re-order point strategies with remanufacturing, and (iv) we indicate some new areas for future research in production planning and inventory control with remanufacturing.