Abstract

Generating realistic configurations of urban models is a vital part of the modeling process, especially if these models are used for evaluation and analysis. In this work, we address the problem of assigning objects to their storage locations inside a warehouse which has a great impact on the quality of operations within a warehouse. Existing storage policies aim to improve the efficiency by minimizing travel time or by classifying the items based on some features. We go beyond existing methods as we analyze warehouse layout network in an attempt to understand the factors that affect traffic within the warehouse. We use simulated annealing based sampling to assign items to their storage locations while reducing traffic congestion and enhancing the speed of order picking processes. The proposed method enables a range of applications including efficient storage assignment, warehouse reliability evaluation and traffic congestion estimation. Document type: Part of book or chapter of book

Abstract

Carbon footprinting is regarded as one means of enhancing transparency on where greenhouse gas (GHG) emissions are produced within a transport chain and thus limiting the emissions and improving the efficiency of transport and transhipment on both the demand and supply sides of the market. To meet global GHG reduction targets and to realize sustainable transport chains, standardization of emissions calculations is progressing swiftly. One of the core requirements in the next steps of the standardization effort is harmonization of level of detail of the various transport modes. In particular logistics hubs have been identified as relevant for such a development and whereas developments for transport modes such as rail, road, air, or water are pursued by industry representatives and their organizations, logistics hubs have no organization which is intrinsically motivated to further develop an approach to emissions calculation. Research can deliver an important and valuable contribution here. Therefore, based on extensive empirical research in the form of questionnaires and real-life examples of emissions calculation, this paper describes the motivations and barriers currently experienced by shippers and logistics service providers when computing emissions. Possible approaches to overcoming these barriers and contributing to the further improvement of the level of maturity of emissions calculation of logistics hubs are described and discussed. The paper closes with an outlook on further requirements toward transport chain emissions calculation standardization developments.