Optimizing Integrated Supply Chain Scheduling: A Mathematical Model for Order Acceptance, Vehicle Routing, and Customers’ Heterogeneity Encountering Delivery Timing

In today’s competitive supply chain landscape, manufacturers in make-to-order environments face the challenge of meeting diverse customer delivery expectations while minimizing operational costs. Existing models often overlook customer heterogeneity in delivery preferences and fail to integrate critical decisions such as order acceptance, production scheduling, and distribution routing. To address these gaps, this study proposes a mixed integer linear programming model that simultaneously optimizes order acceptance, job scheduling, vehicle routing, and delivery timing to maximize total profit. A key innovation is the differentiation between two customer types: those who incur earliness penalties due to limited storage capacity and those who offer rewards for early deliveries to enhance responsiveness. The model incorporates revenues from accepted jobs, tardiness and earliness penalties, earliness rewards, transportation costs, and vehicle fixed costs to provide a practical optimization framework. Computational experiments demonstrate the model’s effectiveness, with solution times ranging from ۰.۱۶ seconds for small instances (e.g., ۴ customers) to approximately ۱۱۵ seconds for larger instances (e.g., ۱۰ customers and ۵ vehicles). For more complex scenarios, such as ۱۰ customers with ۱۰ vehicles, advanced solution methods are required due to increased computational demands. This research offers supply chain managers a valuable tool to balance customer satisfaction with cost efficiency, while highlighting the impact of customer-specific preferences and vehicle constraints on operational performance.

کلیدواژه ها:

Optimization ، Transportation Routing ، Tardiness and earliness Penalty ، Customer Heterogeneity ، Earliness Reward