OICC Press International Journal of Mathematical Modelling & Computations 2228-6233 2026 07 09 Sales Force Schedule and Recovery Model: A Benders Decomposition Approach 10.57647/ijm2c.2027.1702.11 EN Shervin Zeini Department of Industrial Engineering, NT.C., Islamic Azad University, Tehran, Iran Alireza Rashidi Komijan Department of Industrial Engineering, SR.C., Islamic Azad University, Tehran, Iran Vahid Baradaran Department of Industrial Engineering, NT.C., Islamic Azad University, Tehran, Iran Journal Article 2026 07 09 Sales Force Scheduling Problem (SFSP) is one of the challenging problems in Fast-Moving Consumer Goods (FMCG) industry. In SFSP, the daily schedule of each salesperson is determined. An efficient schedule that includes timely customer visits can lead to purchase increase, competitive advantage increase, and market share gain. However, initial schedules may need some modifications due to disruptions. In this paper, two mathematical models are presented. In the first model, the optimal daily schedule for a salesperson is determined. In other words, it is determined which customers should be visited on each day to ensure all customers are visited with the required frequency and at the right time. The second model is the recovery model which is used to update the original schedule under disruption. The main advantage of the proposed recovery model is that it can be used both before and after disruption. The pre-disruption application of the recovery model can provide sales managers with a high degree of analytical capability and serve as a suitable alternative to conservative robust optimization approach. An accelerated Benders decomposition algorithm has been used as the solution approach. The proposed models has been successfully implemented in one of the biggest FMCGs in Iran.