A SYSTEMATIC LITERATURE REVIEW ON STOCHASTIC PROGRAMMING MODELS IN THE RETAIL INDUSTRY

C. Bisset, S. Terblanche
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Abstract

Optimisation under uncertainty, also referred to as stochastic optimisation, originated during the 1950s. This research field was later extended into prominent application areas, including finance, energy, and production planning. During the 1970s, stochastic programming was first applied in the marketing industry. Interest in this field grew exponentially during the early 2000s, and was identified as one of the most promising future research fields for optimisation. Stochastic programming is an asset for the following world researchers due to its uncertainty calculation. This paper aims to identify and evaluate all existing stochastic programming models in the literature in the retail industry. First, a historical overview of marketing models is provided, with a specific focus on stochastic optimisation. Second, all stochastic programming model applications in the retail industry are identified by conducting a systematic literature review. Last, potential gaps for future research opportunities are identified to help retailers to improve their marketing strategies.
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零售业随机规划模型的系统文献综述
不确定性下的优化,也称为随机优化,起源于20世纪50年代。这一研究领域后来扩展到突出的应用领域,包括金融、能源和生产计划。在20世纪70年代,随机规划首次应用于营销行业。在21世纪初,人们对这一领域的兴趣呈指数级增长,并被确定为未来最有前途的优化研究领域之一。随机规划由于其计算的不确定性,为今后的研究提供了宝贵的资源。本文的目的是识别和评估所有现有的随机规划模型在零售行业的文献。首先,提供了营销模型的历史概述,特别关注随机优化。其次,通过进行系统的文献回顾,确定了所有随机规划模型在零售业中的应用。最后,为未来的研究机会确定潜在的差距,以帮助零售商改善他们的营销策略。
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