Showing papers on "Distribution center published in 1989"
TL;DR: In this article, kernel density estimation is used to estimate flexibly the geographic distribution of customers in a market and a density-based product positioning methodology is applied to site selection, using the estimated geographic customer density to help locate a new or relocated store or distribution center.
Abstract: This paper shows how kernel density estimation may be used to estimate flexibly the geographic distribution of customers in a market. In addition it shows how a density-based product positioning methodology may be applied to site selection, using the estimated geographic customer density to help locate a new or relocated store or distribution center. This application provides a conceptual basis for more complicated site selection and spatial demand models which might involve several predictor variables.
56 citations
01 Jan 1989
TL;DR: A new design and management methodology for AS/RS’s is developed and examined, based on knowledge structures, mathematical models and on the state-operator framework for problem solving.
Abstract: The successful operation of every manufacturing facility or distribution center depends to a large extent on the efficient hadling, storage and flow controls of materials. A key component in many material flow activities is the Automated Storage and Retrieval System (AS/RS) which serves as an unmanned warehouse for raw material, work in progress inventories and finished goods. In this paper a new design and management methodology for AS/RS’s is developed and examined. It is based on knowledge structures, mathematical models and on the state-operator framework for problem solving. An industrial case study is used to illustrate the applicability of these concepts to the operational controls of a unit-load AS/RS. The impacts of recent developments in related information technologies, data representation schemes and industrial communications are also examined.