An evaluation of several combinations of routing and storage location assignment policies for the order batching problem

Author(s):  
Ufuk Bahçeci ◽  
Temel Öncan
2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Marcele Elisa Fontana ◽  
Cristiano Alexandre Virgínio Cavalcante

The main variables that influence the efficiency of a warehouse are the use of space and the order picking distance. In the literature, there are proposals to add the costs with space and order picking in order to evaluate each alternative for storage location assignment. However, there were problems with the adoption of this methodology, including difficulties in determining the costs and tradeoffs between them. These difficulties can result in solutions that are suboptimal. Based on these facts, this paper proposes a class-based storage process and storage location assignment by a cube-per-order index (COI) that analyzes the space required and the total order picking distance by Pareto-optimal calculations. The efficient frontier possibilities allow the reduction of the set of alternatives, and the DM can analyze only the alternatives on efficient frontier.


2017 ◽  
Vol 64 (2) ◽  
pp. 193-212
Author(s):  
Grzegorz Tarczyński

The paper presents the model for optimal number of merged orders that will reduce the average order-picking time. Two order batching policies were described: pick-then-sort and sort-while-pick. One-block rectangular warehouses were considered. The author studied two routing heuristics: s-shape and return for which the equations for average order-picking time can be designated based on probability distributions: binomial distribution and uniform distribution. The research takes into account the possible congestion problem. Based on simulations the analytical form of blocking time for pickers was proposed. The study shows that the advantages of each additional merged order is getting smaller. Using ABC classification for storage location assignment in warehouses with low number of aisles and large pick lists can extend the average order-picking time.


2015 ◽  
Vol 9 (7) ◽  
pp. 161
Author(s):  
David Licindo ◽  
Arinne Christin Paramudita ◽  
Renanto Handogo ◽  
Juwari Purwo Sutikno

Carbon capture and storage (CCS) is one of the technologies to reduce greenhouse gas emissions (GHG) tocapture of CO2 from the flue gas of a power plant that typically use coal as a Source of energy and then store it ina suitable geological storage (in specific locations). In practice, these sites may not be readily available forstorage at the same time that the Sources (GHG producing) are operating which gives rise to multi – periodplanning problems. This study presents a mathematical approach by considering constraints limit flowratereceived by Sink, various time availability of Sink and Source and calculation with the purpose to determine theminimum cost network which is getting the maximum load that is exchanged from Source to Sink. Illustrativecase studies are given to demonstrate the application of mathematical models to obtained with the exact result ofthe exchange network from Source to Sink. Derived from network obtained from the calculation of theMaximum Load Source to Sink and results may vary in accordance with the limitations that exist in themathematical model. The case study has been prepared with 2 cases, first 6 Source and 3 Sink with value ofSource Load is greater than the amount available on the Sink. Also, second case is 2 Source and 5 Sinkwithvalue of Source Load is smaller than the amount available on the Sink. In addition, Case Studies tominimize the cost of pipeline construction and distribution of CO2 by plant and storage location determination inJava. Flowrate restriction factor that goes into Sink, Source and Sink establishment time and cost are taken intoaccount can affect the networks that can be exchanged from the Source to the Sink.


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