Ellipsoidal Classification via Semidefinite Programming

Separating two finite sets of points in a Euclidean space is a fundamental problem in classification. Customarily linear separation is used, but nonlinear separators such as spheres have been shown to have better performances in some tasks, such as edge detection in images. We exploit the relationships between the more general version of the spherical … Read more

Stochastic Look-Ahead Commitment: A Case Study in MISO

This paper introduces the Stochastic Look Ahead Commitment (SLAC) software prototyped and tested for the Midcontinent Independent System Operator (MISO) look ahead commitment process. SLAC can incorporate hundreds of wind, load and net scheduled interchange (NSI) uncertainty scenarios. It uses a progressive hedging method to solve a two-stage stochastic unit commitment. The first stage optimal … Read more

A Prescriptive Machine Learning Method for Courier Scheduling on Crowdsourced Delivery Platforms

Crowdsourced delivery platforms face the unique challenge of meeting dynamic customer demand using couriers not employed by the platform. As a result, the delivery capacity of the platform is uncertain. To reduce the uncertainty, the platform can offer a reward to couriers that agree to be available to make deliveries for a specified period of … Read more

Multi-depot routing with split deliveries: Models and a branch-and-cut algorithm

We study the split-delivery multi-depot vehicle routing problem (MDSDVRP) which combines the advantages and potential cost-savings of multiple depots and split-deliveries and develop the first exact algorithm for this problem. We propose an integer programming formulation using a comparably small number of decision variables and several sets of valid inequalities. These inequalities focus on ensuring … Read more

Compact extended formulations for low-rank functions with indicator variables

We study the mixed-integer epigraph of a low-rank convex function with non-convex indicator constraints, which are often used to impose logical constraints on the support of the solutions. Extended formulations describing the convex hull of such sets can easily be constructed via disjunctive programming, although a direct application of this method often yields prohibitively large … Read more

An integrated vertiport placement model considering vehicle sizing and queuing

The increasing levels of congestion and infrastructure costs in cities have created a need for more intelligent transport systems. Urban Air Mobility (UAM) offers a solution by introducing intra-urban aerial transport to overcome the existing congested infrastructure. The performance of UAM systems are highly dependent on vertiport locations, vehicle sizing and infrastructure specifications. This study … Read more

Optimisation of Step-free access Infrastructure in London Underground considering Borough Economic Inequality

Public transport is the enabler of social and economic development, as it allows the movement of people and provides access to opportunities that otherwise might have been unattainable. Access to public transport is a key aspect of social equity, with step-free access improving the inclusivity of the transport network in particular for mobility impaired population … Read more

Demand modelling and optimal vertiport placement for airport-purposed eVTOL services

Recent technological advances have only recently made Urban Air Mobility feasible as a realistic alternative to existing transport modes. Despite the growing interest, this disruptive service requires accurate strategic investments to ensure its viability in the short- and long-term. While airports have been identified as potential sites for vertiports, extending operations to the urban rest … Read more

European Gas Infrastructure Expansion Planning: An Adaptive Robust Optimization Approach

The European natural gas market is undergoing fundamental changes, fostering uncertainty regarding both supply and demand. This uncertainty is concentrated in the value of strategic infrastructure investments, e.g., projects of common interest supported by European Union public funds, to safeguard security of supply. This paper addresses this matter by suggesting an adaptive robust optimization framework … Read more

Global Complexity Bound of a Proximal ADMM for Linearly-Constrained Nonseperable Nonconvex Composite Programming

This paper proposes and analyzes a dampened proximal alternating direction method of multipliers (DP.ADMM) for solving linearly-constrained nonconvex optimization problems where the smooth part of the objective function is nonseparable. Each iteration of DP.ADMM consists of: (ii) a sequence of partial proximal augmented Lagrangian (AL) updates, (ii) an under-relaxed Lagrange multiplier update, and (iii) a … Read more