J. M. Ries

Reducing lead time risk through multiple sourcing: the case of stochastic demand and variable lead time

This paper studies a buyer sourcing a product from multiple suppliers under stochastic demand. The buyer uses a (Q, s) continuous review, reorder point, order quantity inventory control system to determine the size and timing of orders. Lead time is assumed to be deterministic and to vary linearly with the lot size, wherefore lead time and the associated stockout risk may be influenced by varying the lot size and the number of contracted suppliers. This paper presents mathematical models for a multiple supplier single buyer integrated inventory problem with stochastic demand and variable lead time and studies the impact of the delivery structure on the risk of incurring a stockout during lead time.

Ordering policy for stock-dependent demand rate under progressive payment scheme: a comment

In a recent paper,  Soni and Shah developed a model for finding the optimal ordering policy for a retailer facing stock-dependent demand and a supplier offering a progressive payment scheme. In this comment, we correct several errors in the formulation of the models of Soni and Shah and modify some assumptions to increase the models applicability. Numerical examples illustrate the benefits of our modifications.

Environmental impact of warehousing: a scenario analysis for the United States

In recent years, there has been observed a continued growth of global carbon dioxide emissions, which are considered as a crucial factor for the greenhouse effect and associated with substantial environmental damages. Amongst others, logistic activities in global supply chains have become a major cause of industrial emissions and the progressing environmental pollution. Although a significant amount of logistic-related carbon dioxide emissions is caused by storage and material handling processes in warehouses, prior research mostly focused on the transport elements. The environmental impact of warehousing has received only little attention by research so far. Operating large and highly technological warehouses, however, causes a significant amount of energy consumption due to lighting, heating, cooling and air condition as well as fixed and mobile material handling equipment which induces considerable carbon dioxide emissions. The aim of this paper is to summarise preliminary studies of warehouse-related emissions and to discuss an integrated classification scheme enabling researchers and practitioners to systematically assess the carbon footprint of warehouse operations. Based on the systematic assessment approach containing emissions determinants and aggregates, overall warehouse emissions as well as several strategies for reducing the carbon footprint will be studied at the country level using empirical data of the United States. In addition, a factorial analysis of the warehouse-related carbon dioxide emissions in the United States enables the estimation of future developments and facilitates valuable insights for identifying effective mitigation strategies.

Dynamische Losgrößenplanung in ERP-Systemen

Kurzfassung ERP-Systeme beinhalten heutzutage vielfältige Heuristiken der dynamischen Fertigungs- und Bestellmengenplanung. Allerdings variiert die Leistungsfähigkeit dieser Verfahren je nach vorliegender Bedarfsstruktur erheblich. Daher kommt der Auswahl einer geeigneten Heuristik eine wichtige Rolle zu, um Mehrkosten auf Grund ungenauer Planungen zu vermeiden. Basierend auf umfassenden numerischen Studien zeigt sich, dass das Grenzkostenverfahren nach Groff sowie das Verfahren von Silver und Meal im Mittel die besten Ergebnisse liefern.