Mixed Integer (Non-) Linear Programming Formulations of Graph Neural Networks

Recently, ReLU neural networks have been modelled as constraints in mixed integer linear programming (MILP) enabling surrogate-based optimisation in various domains as well as efficient solution of machine learning verification problems. However, previous works have been limited to multilayer perceptrons (MLPs). The Graph Convolutional Neural...

Dynamic planning for simultaneous recharging and relocation of shared electric taxies: A sequential MILP approach

Short driving range, limited chargers, and long charging times challenge the profitability of electric taxi operations. In this paper, a charging algorithm is developed to accompany a taxi service with online trip requests, which uses a private charging infrastructure for both slow and fast charging. The vehicle charging curves are assumed to be...

Data-Driven Transportation Planning for a Large Manufacturing Plant: Analysis and development of a planning support tool for the internal transportation at Tata Steel IJmuiden

Planning the on-site transportation of large manufacturing sites is a complex process. Currently these plans are made based on the on-site logistics constraints rather than on KPIs. Research has been focused on either analysis of system parameters or generally on KPIs, but lacks the combination of both on real-life cases. This gap is closed by...

Development and Validation of Short-term Mine Planning Optimization Algorithms for a Sublevel Stoping Operation with Backfilling