An investigation of automated planograms using a simulated annealing based hyper-heuristic

Ruibin Bai, Graham Kendall

Research output: Journal PublicationArticlepeer-review

57 Citations (Scopus)

Abstract

This paper formulates the shelf space allocation problem as a non-linear function of the product net profit and store-inventory. We show that this model is an extension of multi-knapsack problem, which is itself an NP-hard problem. A two-stage relaxation is carried out to get an upper bound of the model. A simulated annealing based hyper-heuristic algorithm is proposed to solve several problem instances with different problem sizes and space ratios. The results show that the simulated annealing hyper-heuristic significantly outperforms two conventional simulated annealing algorithms and other hyper-heuristics for all problem instances. The experimental results show that our approach is a robust and efficient approach for the shelf space allocation problem.

Original languageEnglish
Pages (from-to)87-108
Number of pages22
JournalOperations Research/ Computer Science Interfaces Series
Volume32
DOIs
Publication statusPublished - 2005
Externally publishedYes

Keywords

  • Hyper-heuristics
  • Planograms
  • Shelf space allocation
  • Simulated annealing

ASJC Scopus subject areas

  • Computer Science (all)
  • Management Science and Operations Research

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