Designing a stochastic multi-objective simulation-based optimization model for sales and operations planning in built-to-order environment with uncertain distant outsourcing

Abstract

To this day, sales & operations planning (S&OP) remains one of the most critical challenges of supply chain management in terms of improving customers’ experience level and managing supply chain costs. Nowadays the synchronization of sales essentials and industrial restrictions in an uncertain environment is critical for all global companies facing complexity in supply chain networks and operations systems. Sales and supply chain structures in build-to-order industries generally have cross-functional and conflicting objects that are not easily comparable. The current research is an extension of an innovative S&OP model within a more dynamically complex system in terms of demands uncertainty and unreliability of backup supplies. The promoted model is utilized for more efficient management and integration of industrial restrictions and sales essentials in global supply chain networks in terms of demand and supply coordination and responsiveness toward customers’ needs. Accordingly, this research has applied a simulation-based optimization approach to balance the trade-off between logistics cost and customers’ experience level as the main objectives. Two classes of strategies are offered for handling parts’ replenishment and flexibility to the sales structure. Initially, the proposed model evaluates two main inventory strategies’ performances. Thereafter, the optimized values of flexibility degree and safety stock fraction for corresponding inventory strategies are calculated by using a multi-objective simulation-optimization method. The investigation begins with an overall assessment of the system's performance. Furthermore, it details the alterations among the strategies’ key performance indicators (KPIs) as system parameters’ function.