Algorithms for On-line Order Batching in an Order-Picking Warehouse

In manual order picking systems, order pickers walk or ride through a distribution warehouse in order to collect items required by (internal or external) customers. Order batching consists of combining these – indivisible – customer orders into picking orders. With respect to order batching, two problem types can be distinguished: In off-line (static) batching all customer orders are known in advance. In on-line (dynamic) batching customer orders become available dynamically over time. This report considers an on-line order batching problem in which the total completion time of all customer orders arriving within a certain time period has to be minimized. The author shows how heuristic approaches for the off-line order batching can be modified in order to deal with the on-line situation. A competitive analysis shows that every on-line algorithm for this problem is at least 2-competitive. Moreover, this bound is tight if an optimal batching algorithm is used. The proposed algorithms are evaluated in a series of extensive numerical experiments. It is demonstrated that the choice of an appropriate batching method can lead to a substantial reduction of the completion time of a set of customer orders.Warehouse Management, Order Picking, Order Batching, On-line Optimization

Adaptive batching scheme for multicast near video-on-demand (nvod) system

Video-on-Demand is becoming most sought after multimedia applications. It is difficult to attain a true video-on-demand (TVOD) system, so near video-on-demand (NVOD) is catching the attention of people. In NVOD, requests are multicast in different streams. Important issue in this system is the choice of batching time. Traditionally the batching time is fixed depending on the number of requests. In this paper we have suggested an adaptive batching scheme (ABS) where batching time is adjusted according to the current arrival rate, which follows the hyper-exponential distribution pattern. A comparison is made between the fixed and adaptive batching schemes. Numerical illustrations are provided to show that adaptive batching policy is better than fixed batching policy for optimizing bandwidth requirements

Program Transformations for Asynchronous and Batched Query Submission

The performance of database/Web-service backed applications can be significantly improved by asynchronous submission of queries/requests well ahead of the point where the results are needed, so that results are likely to have been fetched already when they are actually needed. However, manually writing applications to exploit asynchronous query submission is tedious and error-prone. In this paper we address the issue of automatically transforming a program written assuming synchronous query submission, to one that exploits asynchronous query submission. Our program transformation method is based on data flow analysis and is framed as a set of transformation rules. Our rules can handle query executions within loops, unlike some of the earlier work in this area. We also present a novel approach that, at runtime, can combine multiple asynchronous requests into batches, thereby achieving the benefits of batching in addition to that of asynchronous submission. We have built a tool that implements our transformation techniques on Java programs that use JDBC calls; our tool can be extended to handle Web service calls. We have carried out a detailed experimental study on several real-life applications, which shows the effectiveness of the proposed rewrite techniques, both in terms of their applicability and the performance gains achieved.Comment: 14 page

Effect of Batching Methods on the fresh and hardened properties of Concrete

This paper investigated the effect of batching by mass and volume on concrete’s compressive strength and workability. Influence of mix proportion at five levels and various water-cement ratios were also studied. All samples were cured by complete immersion in water and tested up to 28 days. The results indicated higher workabilities for concrete batched by mass than concrete batched by volume at all w/c ratios and mix proportions investigated. The workability increased with increase in w/c ratios in both methods. The compressive strength results showed that for rich structural mixes (1:1:2 and 1:1.5:3), concrete batched by mass had 20 % and 6 % strength increases respectively over the concrete batched by volume. Ordinary structural mix (1:2:4) had 14 % increase while non-structural mixes (1:3:6 and 1:4:8) had 8 % and 6 % increases respectively. In all cases, concrete batched by mass had better fresh and hardened properties of concrete

Assessing water footprint and associated water scarcity indicators at different spatial scales : a case study of concrete manufacture in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Master in Environmental Management, Massey University, Manawatu Campus, New Zealand

Water scarcity is a growing issue of concern across the globe. In recent times a complex suite of water footprint impact assessment tools and concepts have supplemented traditional management approaches. There are several methods proposed in the literature to both quantify water use and assess its environmental impacts at defined spatial scales. In New Zealand, case studies in the water footprinting space are sparse, and are for the majority focused on the agricultural industry. This thesis focused on evaluation of different water footprint methods and their associated water scarcity indicators to assess water use impacts for the building and construction sector of New Zealand. The water footprints of 1 m³ ready mix concrete manufactured at 27 concrete batching plants throughout New Zealand were calculated at three distinct spatial scales: the freshwater management zone scale, catchment scale, and regional scale. Four water footprint characterisation factors (blue water scarcity (WSblue) (Hoekstra et al., 2011), water stress index (WSI) (Pfister et al., 2009), water depletion index (WDI) (Berger et al., 2014), and available water minus demand (AMD) (Boulay et al., 2016)) were used to assess the environmental impact of water use for 1 m³ ready mix concrete at the three spatial scales. The average volumetric blue water footprint of the 27 ready mix batching plants was quantified at 0.18 m3 (180 litres) of water per m³ of concrete, and ranged from 0.15 (150 litres) to 0.29 m³ (290 litres) of freshwater per m³ of concrete. For three of the four water footprint methods used (WDI, WSI and WSblue), and across the three spatial, the Ashburton boundary ranked highest in terms of the environmental impacts of a specified quantity of water use. In contrast, the AMD method ranked the Palmerston North boundary highest across the three spatial scales. At the freshwater management zone and catchment scales, the WDI, WSI and WSblue methods ranked the Wanganui area lowest, and the AMD method ranked the Greymouth area lowest. At the regional scale, all the four water footprint methods ranked the West Coast region lowest in terms of the environmental impact of water use, due mainly to the fact that the West Coast has more available water and a lower allocation demand than other regions studied. The analysis indicated that volumetric water use varied by a factor of two across the different plants (per m3 concrete). For three of the four WF methods (WDI, WSI and WSblue), the WF results were similar in their rankings of the different plants at all the geographical scales; however, the AMD method resulted in different rankings at all the geographical scales. Overall, the WDI and WSI water scarcity indices calculated by Berger et al. (2014) and Pfister et al. (2009) were less readily adaptable to the finer resolution in New Zealand. The WSblue and AMD calculated by Hoekstra et al. (2011) and Boulay et al. (2016) however, were found to be more readily adaptable. It is recommended that these methods be explored further with respect to their potential use at the finer resolution in New Zealand