Metaheuristics with local search techniques for retail shelf-space optimization

• 成果类型: Article
• 署名作者: Lim, A; Rodrigues, B; Zhang, XW
• 署名单位: Hong Kong University of Science & Technology; Singapore Management University; Hong Kong University of Science & Technology
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.1030.0165
• 发表日期: 2004
• 页码: 117-131
• 关键词: retail; shelf allocation; metaheuristics

摘要

Efficient shelf-space allocation can provide retailers with a competitive edge. While there has been little study on this subject, there is great interest in improving product allocation in the retail industry. This paper examines a practicable linear allocation model for optimizing shelf-space allocation. It extends the model to address other requirements such as product groupings and nonlinear profit functions. Besides providing a network flow solution, we put forward a strategy that combines a strong local search with a metaheuristic approach to space allocation. This, strategy is flexible and efficient, as it can address both linear and nonlinear problems of realistic size while achieving, near-optimal solutions through easily implemented algorithms in reasonable timescales. It offers, retailers opportunities for more efficient and,profitable shelf management, as well as higher-quality planograms.