Multi-Item Grouping Algorithm Yielding Near-Optimal Logistics Cost

This article describes an algorithm used to formulate an inbound consolidation strategy when multi-items are replenished in groups and when total logistics cost is to be minimized. The importance of this algorithm is threefold (1) no optimal procedure exists for grouping multi-items when minimizing total logistics cost, (2) a complete enumeration of all possible groups (from which the optimal grouping set can be identified) is impractical due to the combinatorial nature of the grouping problem, and (3) no other heuristics have been developed that adequately reflect shipping cost in the analysis like this one does. We report the experience of using this algorithm to group and reorder 75 selected ensembles containing a total of 517 inventory items of a retail merchandising firm.     

Solution Procedures for the Lot-Streaming Problem

Lot streaming is the process of splitting a job into sublots so its operations can be overlapped and its progress accelerated. We present a computationally efficient procedure for solving the m-machine, two-sublot problem, and we discuss the bottleneck insights that emerge from the analysis. We also examine heuristic approaches for more than two sublots and discuss computational results for these procedures.     

On Sampling Error in Market Share Estimates*

The relative error in the usual estimator of a brand's market share is reformulated in terms of marketing parameters. Such error is shown to be influenced in an important way by market penetration, as well as by variation in brand and product category volume. Of particular interest is the result that the relative error does not depend on the actual share level. Using data from a marketing research firm that supplies share estimates to the health products industry, we find that the relative error may be substantial even when a large sample is available. An upper bound on this relative error is obtained using marketing parameters that can frequently be measured using industry data and a company's internal records, thus reducing the level of judgmental input required in the planning of sample surveys.     

Vegetation on and around large-scale buildings positively influences native tropical bird abundance and bird species richness

High population growth in the tropics is driving urbanisation, removing diverse natural ecosystems. This is causing native species to suffer while introduced synanthropes flourish. City planners are developing urban greenspace networks, in part trying to address this issue. Architects contribute to these greenspace networks by designing elevated and ground level green spaces on large-scale buildings. However, little evidence is available on whether building green spaces support native fauna. This is true for birds in tropical Singapore that support important ecosystem services and have existence value. Therefore, in this study, we conducted bird surveys and statistical analyses to determine, if and how vegetation on three building green space types (ground gardens, roof gardens and green walls) have a positive impact on native or introduced bird species. We found that elevated greenery (roof gardens and green walls) on large-scale buildings supported a higher richness of birds and abundance of urban native birds than control roofs and walls without vegetation. Ground gardens supported similar levels of native species as roof gardens but also a larger proportion of generalist synanthropes. However, we found no tropical forest habitat specialists across any space type. Therefore, we recommend roof gardens and ground gardens as a potential space for urban natives outside of a less competitive ground-level urban environment. Our study also found certain building design elements (height of elevated space, presence of specific plants) supported different species groups. Therefore, we suggest that these ecological requirements for different species groups are considered when designing a building’s green space.