Vehicle routing problem with vendor selection, intermediate pick-ups and deliveries

Official URL: http://risc01.sabanciuniv.edu/record=b1534387 (Table of Contents)

Online shopping is becoming nowadays more indispensable to many people in their daily lives with a growing service range for a wide variety of goods. In this thesis, we study a distribution planning model for online retailers to fulfill the diverse consumer demands especially for premium goods, i.e. goods with a high potential to create additional income such as organic food, electronic materials, special gifts etc., without increasing inventory related costs. We refer to the related distribution planning problem as the Vehicle Routing Problem with Vendor Selection, Intermediate Pick-ups and Deliveries (VRPVSIPD). The VRPVSIPD is based on a distribution network where premium goods are acquired from a proper set of external vendors at multiple locations in the supply network and delivered to customers. In order to solve the VRPVSIPD, we present an improved Adaptive Large Neighborhood Search (ALNS) heuristic by introducing new removal, insertion and vendor selection/allocation algorithms. To investigate the performance of the proposed methodology, we conduct an extensive computational study using both the well-known Solomon instances for Vehicle Routing Problem with Time Windows and newly generated benchmark instances for the VRPVSIPD. Our results reveal that the proposed methodology is effective in terms of both the solution quality and computational time.