In a production scheduling with delivery problem, there are different types of products processed by a distribution center and then delivered to retailers. Each retailer order might be consisted of different products. The resolution of this problem is to determine the production sequence, retailers needs to heterogeneous fleet of vehicles and the visiting sequence of each vehicle for delivery goods within time windows. In this article, a nonlinear mathematical model is proposed with minimizing the total cost which includes transportation cost, vehicle arrangement cost and penalty costs, subjected to satisfy all demands of each retailer. Following, two adaptive genetic algorithms (AGAs) are designed and tested in variety of production and delivery scenarios. The computational experiments show that the total cost gradually decreases as the vehicle type employed in the delivery stage increasing. In addition, more kinds of vehicle types provided in the delivery stage could reduce fixed vehicle cost and variable routing cost.
- Adaptive genetic algorithm
- Heterogeneous fleet
- Production scheduling with delivery
- Time windows