在竞争市场中使用强化学习的联合定价和库存管理:基于代理和模拟优化方法的结合

IF 3 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE International Journal of Management Science and Engineering Management Pub Date : 2023-03-13 DOI:10.1080/17509653.2021.1983737
Saeed Abdolhosseini, Mahsa Ghandehari, A. Ansari, Omid Roozmand
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引用次数: 0

摘要

合理的定价机制是吸引顾客、增加利润的重要手段之一。零售商的主要问题是如何在竞争激烈的异质市场中设定价格和库存政策,以实现利润最大化,同时存在非零交货时间和销售损失。提出了一种强化学习算法来创建合适的定价决策机制。在竞争环境中,协调的库存政策可以降低物流成本,并带来更高的利润。我们使用强化学习算法来研究零售商在竞争环境中的表现。采用基于主体的建模实验环境,结合模拟优化方法,再现了一个虚拟市场。就顾客行为而言,市场不是同质化的。假设零售商使用(R, Q)策略,其中交货时间为固定数量(L),并且允许出现短缺。质量、距离、服务水平和价格是影响顾客选择的因素。对一些随机生成的算例的仿真结果表明,该算法在竞争环境下比现有的方法能获得更高的利润,仿真-优化方法的结合使用能够更好地解决考虑顾客行为的定价与库存管理混合模型。对三种不同类别的客户(对价格更敏感、对价格、质量和服务水平同样敏感、对质量更敏感)的仿真结果表明,所提算法的平均利润高于所研究的其他算法。
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Joint pricing and inventory management in a competitive market using reinforcement learning: a combination of the agent-based and simulation-optimization approaches
ABSTRACT One of the most important tools is an appropriate pricing mechanism to attract more customers and increase profits. The retailers’ main question is how to set the prices and inventory policies to maximize profit in a competitive heterogeneous market in presence of non-zero lead time and lost sales. A reinforcement learning algorithm is proposed to create appropriate decision-making mechanisms for pricing. A coordinated inventory policy in a competitive environment reduces logistic costs and leads to a higher profit. We use a reinforcement learning algorithm to investigate the performance of a retailer in a competitive environment. An agent-based modeling experimental environment combined with a simulation-optimization method in which a virtual market has been reproduced is used. The market is not homogeneous with respect to customer behavior. It is assumed that the retailer uses (R, Q) policy where the lead time is a fixed amount (L), and the shortage is permissible. The quality, distance, service level, and price are factors that influence customers’ choices. The simulation results for some randomly generated examples show that the algorithm in the competitive environment can make more profit than other available methods and the combined utilization of simulation-optimization methods has been able to find better solutions for the hybrid model of pricing and inventory management considering customer behavior. The results of simulation for three different categories of customers (more sensitive to price, equally sensitive to price, quality and service level, and more sensitive to quality (indicate that the average profit for the proposed algorithm is higher than that of other examined algorithms.
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来源期刊
CiteScore
8.50
自引率
33.30%
发文量
40
期刊介绍: International Journal of Management Science and Engineering Management (IJMSEM) is a peer-reviewed quarterly journal that provides an international forum for researchers and practitioners of management science and engineering management. The journal focuses on identifying problems in the field, and using innovative management theories and new management methods to provide solutions. IJMSEM is committed to providing a platform for researchers and practitioners of management science and engineering management to share experiences and communicate ideas. Articles published in IJMSEM contain fresh information and approaches. They provide key information that will contribute to new scientific inquiries and improve competency, efficiency, and productivity in the field. IJMSEM focuses on the following: 1. identifying Management Science problems in engineering; 2. using management theory and methods to solve above problems innovatively and effectively; 3. developing new management theory and method to the newly emerged management issues in engineering; IJMSEM prefers papers with practical background, clear problem description, understandable physical and mathematical model, physical model with practical significance and theoretical framework, operable algorithm and successful practical applications. IJMSEM also takes into account management papers of original contributions in one or several aspects of these elements.
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