Shelf Space Allocation and Profit Maximization in Mass Retailing

1973 ◽  
Vol 37 (3) ◽  
pp. 54-60 ◽  
Author(s):  
Ronald C. Curhan
Keyword(s):  
Conceptual Models ◽  
Empirical Studies ◽  
Profit Maximization ◽  
Shelf Space ◽  
For Profit ◽  
Space Allocation ◽  
Practical Management ◽  
Shelf Space Allocation ◽  
Relationship Of ◽  
The Relationship

Conceptual models and empirical studies of the relationship of shelf space allocation to unit sales are reviewed in this article. This knowledge is organized to support specific recommendations for the practical management of shelf space for profit maximization.

scholarly journals Genetic Algorithm for the Retailers’ Shelf Space Allocation Profit Maximization Problem

2021 ◽  
Vol 11 (14) ◽  
pp. 6401
Author(s):  
Kateryna Czerniachowska ◽  
Karina Sachpazidu-Wójcicka ◽  
Piotr Sulikowski ◽  
Marcin Hernes ◽  
Artur Rot
Keyword(s):  
Genetic Algorithm ◽  
Profit Maximization ◽  
Allocation Rule ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Shelf Space Allocation ◽  
To Receive

This paper discusses the problem of retailers’ profit maximization regarding displaying products on the planogram shelves, which may have different dimensions in each store but allocate the same product sets. We develop a mathematical model and a genetic algorithm for solving the shelf space allocation problem with the criteria of retailers’ profit maximization. The implemented program executes in a reasonable time. The quality of the genetic algorithm has been evaluated using the CPLEX solver. We determine four groups of constraints for the products that should be allocated on a shelf: shelf constraints, shelf type constraints, product constraints, and virtual segment constraints. The validity of the developed genetic algorithm has been checked on 25 retailing test cases. Computational results prove that the proposed approach allows for obtaining efficient results in short running time, and the developed complex shelf space allocation model, which considers multiple attributes of a shelf, segment, and product, as well as product capping and nesting allocation rule, is of high practical relevance. The proposed approach allows retailers to receive higher store profits with regard to the actual merchandising rules.

scholarly journals Simulated Annealing Hyper-Heuristic for a Shelf Space Allocation on Symmetrical Planograms Problem

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1182
Author(s):  
Kateryna Czerniachowska ◽  
Marcin Hernes
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Profit Maximization ◽  
Point Of View ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Effective Decision Making ◽  
Shelf Space Allocation

The allocation of products on shelves is an important issue from the point of view of effective decision making by retailers. In this paper, we investigate a practical shelf space allocation model which takes into account the number of facings, capping, and nesting of a product. We divide the shelf into the segments of variable size in which the products of the specific types could be placed. The interconnections between products are modelled with the help of categorizing the products into specific types as well as grouping some of them into clusters. This results in four groups of constraints—shelf constraints, shelf type constraints, product constraints, position allocation constraints—that are used in the model for aesthetic symmetry of a planogram. We propose a simulated annealing algorithm with improvement and reallocation procedures to solve the planogram profit maximization problem. Experiments are based on artificial data sets that have been generated according to real-world conditions. The efficiency of the designed algorithm has been estimated using the CPLEX solver. The computational tests demonstrate that the proposed algorithm gives valuable results in an acceptable time.

Incorporating Knowledge Management into E-Commerce Applications

2010 ◽  
pp. 975-982
Author(s):  
Sandra Moffett ◽  
Martin Doherty ◽  
Rodney McAdam
Keyword(s):  
Knowledge Management ◽  
New Technologies ◽  
Business Success ◽  
Business World ◽  
For Profit ◽  
Employee Relationships ◽  
Business Function ◽  
Knowledge Intensive ◽  
Relationship Of ◽  
The Relationship

Knowledge Management (KM) is the process of critically managing knowledge to meet existing needs, identify and exploit existing and acquired knowledge assets and develop new opportunities (Quintas et al, 1997). With the emergence of knowledge-intensive industries, where organisations rely on knowledge of their staff for competitive advantage (Lustri et al., 2007), KM has become key for business success (Mu-jung et al., 2007). KM is now an integral business function (Zhou and Fink, 2003) in both traditional and internet-based businesses (Borges Tiago et al., 2007) to the extent that KM is now viewed essential for profit (Yang, 2008). It is widely acknowledged today that new technologies, in particular access to the Internet, tend to modify communication between stakeholders in the business world, such as relationships between the organisation and its clients, the internal functioning of the organisation, including enterprise-employee relationships and the relationship of the organisation with partners and suppliers. This integration to improve the functioning of the organisation to create value for all parties involved is referred to as Electronic Commerce (e-commerce, EC) (Turban et al, 2006).

scholarly journals Community Core Evolution in Mobile Social Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Hao Xu ◽  
Weidong Xiao ◽  
Daquan Tang ◽  
Jiuyang Tang ◽  
Zhenwen Wang
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
Empirical Studies ◽  
Mobile Social Networks ◽  
The Real ◽  
Temporary Connection ◽  
Whole Process ◽  
Relationship Of ◽  
The Relationship ◽  
Stable Community

Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

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