DocumentCode :
2467587
Title :
An Evolutionary Algorithm for the Product to Shelf Allocation Problem
Author :
Esparcia-Alcázar, Anna I. ; Lluch-Revert, Lidia ; Albarracín-Guillem, José Miguel ; Palmer-Gato, Marta ; Sharman, Ken
fYear :
0
fDate :
0-0 0
Firstpage :
3197
Lastpage :
3203
Abstract :
In this paper we propose an evolutionary algorithm to address the problem of allocating products to shelves in a supermarket (product to shelf allocation problem or P2SAP) and show several instances where it was applied successfully. We first show the main problem exact methods pose, namely bad scalability properties. This means the computational time is of the order of a few minutes for the simplest of cases (one shelf with few modules; few products), while for more complex problems it exceeds 30 hours or, worse still, the method does not provide a solution at all. We then propose an evolutionary algorithm and test it on four different problem configurations (three with one shelf and one with two shelves). In all cases acceptable results can be obtained in a very short timescale.
Keywords :
evolutionary computation; retailing; evolutionary algorithm; product allocation; shelf allocation problem; supermarket; Evolutionary computation; Marketing and sales; Scalability; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
Type :
conf
DOI :
10.1109/CEC.2006.1688714
Filename :
1688714
Link To Document :
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