关键词: 物流工程, IRPP, 需求价格函数, 离散分布, 改进粒子群算法

Abstract:

This paper studied the inventory routing and pricing problem (IRPP) with discretely distributed random disturbance items in the demand price function. Based on the discrete distribution rate of the random disturbance item and requirements on retailers' inventory service level, an IRPP optimization model was established to maximize the expected revenues of the supplier. The tabu search algorithm was embedded into the improved particle swarm algorithm to solve the model. Three numerical examples with different sizes show that the supplier's expected revenue can be increased by 3.1%, 3.5%, and 3.8% respectively when considering the random disturbance item, under the same retailors' inventory service level. The research indicates that the more severe the random disturbance of the product demand price function, the less the supplier's expected return, and the higher the price elasticity of the customer's product, the greater the expected return of the supplier. This finding can provide a useful reference for the supplier's IRPP decision-making.

Key words: logistics engineering, IRPP, demand price function, discrete distribution, improved particle swarm optimization