Machine Learning Predictions and Optimization: Working together for better decisions.

我正在与Tesco合作进行一个与非易腐产品定价相关的多学科博士项目。我们的目标是通过使用运筹学，人工智能和组合学的最新进展来开发一个强大的定价算法。定价决策需要同时满足短期业务需求和对组织未来增长前景的长期影响。在竞争激烈的市场中，产品基本上都是同质的，价格是任何消费者做出购买决定的关键因素。许多公司依靠人工输入来做出定价决策。然而，这些基于人类的方法是次优的，昂贵的，并且容易产生行为偏差。开发一种自动化的方法来设定连锁超市所有门店的价格是一个重大的挑战;目前的文献通常是在逐站的基础上尝试的，这忽略了继承的网络结构。此外，定价问题可以细分为两个部分。首先，我们需要估计各种模型参数，如需求和竞争对手的价格。第二个优化，我们需要得到一个满足所有业务目标的最优销售价格。整合这两个子问题的最常见框架是一个顺序过程。然而，根据历史数据做出的任何预测都存在不确定性，但基础的顺序过程在上游优化时不包括这种预测不确定性;因此，导致次优决策。我们将开发一个框架，在考虑预测的不确定性的同时，为整个网络中的非易腐产品提供最佳定价。

I am working on a multidisciplinary PhD project related to non-perishable product pricing in association with Tesco. We aim to develop a robust pricing algorithm by using recent advancements in Operational Research, Artificial intelligence, and Combinatorics. Pricing decisions need to satisfy both the short-term business needs and the long-lasting impact on the future growth prospects of the organisation. In a competitive market with primarily homogeneous products, price is a key incentive for any consumer when making a purchase decision. Many companies rely on manual inputs for a pricing decision. However, these human-based methods are suboptimal, expensive, and prone to behavioural bias. Developing an automated approach to set prices at all outlets of a supermarket chain is a significant challenge; current literature typically attempts this on a station-by-station basis, which ignores the inherited network structure. Furthermore, the pricing problem can be subdivided into two parts. First prediction, we require estimates of various model parameters such as demand, and competitor's price. Second optimisation, we need to get an optimal selling price satisfying all the business objectives. The most common framework to integrate these two subproblems is a sequential process. However, any projections made on historical data are subject to uncertainty, but the underlying sequential process does not include this prediction uncertainty at upstream optimisation; thus, results in a suboptimal decision. We will develop a framework to optimally price non-perishable products across the network while accounting for the uncertainty in predictions.In partnership with Tesco.