Product-oriented time window assignment for a multi-compartment vehicle routing problem

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Sara Martins (Author) Other; Manuel Ostermeier (Author) Other; Pedro Amorim (Author) FEUP; Alexander Hübner (Author) Other; Bernardo Almada Lobo (Author) FEUP

Journal

Title: European Journal of Operational Research

Vol. 276 No. 3

Pages: 893-909

ISSN: 0377-2217

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 2 Citations

Scopus - 16 Citations

INSPEC

Other information

Authenticus ID: P-00Q-5ZC

DOI: 10.1016/j.ejor.2019.01.053

Abstract (EN): Besides fuel and waste distribution, one core application of multi-compartment vehicles (MCVs) is the distribution of groceries, as they enable retailers to jointly transport products with different temperature requirements, thus reducing the number of visits to a store. Grocery stores usually define preferable time windows that depend on the temperature of products (for example, fresh products in the morning) to indicate when deliveries should occur to better plan their in-store operations. Distribution planning therefore needs to take these preferences into consideration to obtain consistent delivery times. This work extends the research on multi-compartment vehicle routing problems (MCVRPs) by tackling a multi-period setting with a product-oriented time window assignment. In this problem, a fleet of MCVs is used for distribution and a unique time window for the delivery of each product segment to each store is defined consistently throughout the planning horizon. An ALNS is proposed to solve the product-oriented time window assignment for MCVRP. Daily and weekly operators are developed respectively focusing on the improvement of routing aspects of the problem on each day and aligning the time window assignment consistently throughout the planning horizon. The approach is tested on benchmark instances from the literature to demonstrate its effectiveness. We also use direct information from retail practice and enhance this with simulated data to further generalize our findings. The numerical experiments demonstrate that planning consistent MCV distribution leads to better overall solutions than the ex-post time window assignment of daily plans, facilitating more on-time deliveries.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 17