Analytics and machine learning in scheduling and routing research.

In total, more than 200 papers were reviewed and classified into 4 categories which are: machine learning assisted VRP modelling, machine learning guided VRP decomposition strategies, machine learning guided perturbative VRP algorithms, and finally learning to construct VRP solutions. It provides an extensive review of vehicle routing (VRP) researches that use both analytical optimisation approaches and machine learning (ML) modules and mechanisms. This special issue largely originated from various discussions during several cross-domain, multi-disciplinary conferences and workshops, especially the 9th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA2019), which attracted scientists, researchers and practitioners from Computer Science, Operations Research as well as Business and Management. " A Two-Stage Stochastic Programming Model for Collaborative Asset Protection Routing Problem Enhanced with Machine Learning; A Learning Based Matheuristic Algorithm.". [Extracted from the article]