Revisiting the fitting of the Nelson-Siegel and Svensson models

The Nelson-Siegel and the Svensson models are two of the most widely used models for the term structure of interest rates. Even though the models are quite simple and intuitive, fitting them to market data is numerically challenging and various difficulties have been reported. In this paper, a novel mathematical analysis of the fitting problem … Read more

Fast convergence of the primal-dual dynamical system and algorithms for a nonsmooth bilinearly coupled saddle point problem

\(\) This paper is devoted to study the convergence rates of a second-order dynamical system and its corresponding discretizations associated with a nonsmooth bilinearly coupled convex-concave saddle point problem. We derive the convergence rate of the primal-dual gap for the second-order dynamical system with asymptotically vanishing damping term. Based on the implicit discretization, we propose … Read more

Distributed Task Assignment in a Swarm of UAVs

We consider the problem of distributed task assignment in a swarm of Unmanned Aerial Vehicles (UAVs), where heterogeneous agents that can have different capabilities need to work in teams to execute tasks. We consider the case where communication between UAVs is costly or dangerous and should be limited or avoided, while individual UAVs have uncertain … Read more

Trajectory Optimization of Unmanned Aerial Vehicles in the Electromagnetic Environment

We consider a type of routing problems common in defence and security, in which we control a fleet of unmanned aerial vehicles (UAVs) that have to reach one or more target locations without being detected by an adversary. Detection can be carried out by a variety of sensors (radio receivers, cameras, personnel, etc) placed by … Read more

A Radial Basis Function Method for Noisy Global Optimisation

We present a novel response surface method for global optimisation of an expensive and noisy (black-box) objective function, where error bounds on the deviation of the observed noisy function values from their true counterparts are available. The method is based on the well-established RBF method by Gutmann (2001a,c) for minimising an expensive and deterministic objective … Read more

Complexity of gradient descent for multiobjective optimization

A number of first-order methods have been proposed for smooth multiobjective optimization for which some form of convergence to first order criticality has been proved. Such convergence is global in the sense of being independent of the starting point. In this paper we analyze the rate of convergence of gradient descent for smooth unconstrained multiobjective … Read more

Glider Routing and Trajectory Optimisation in Disaster Assessment

In this paper, we introduce the Glider Routing and Trajectory Optimisation Problem (GRTOP), the problem of finding simultaneously optimal routes and trajectories for a fleet of gliders with the aim of surveying a set of locations. We propose a novel Mixed-Integer Nonlinear Programming (MINLP) formulation for the GRTOP, which simultaneously optimises the routes as well … Read more

The Unmanned Aerial Vehicle Routing and Trajectory Optimisation Problem

Unmanned Aerial Vehicles (UAVs) are becoming increasingly popular over the past few years. The complexity of routing UAVs has not been fully investigated in the literature. In this survey, we aim to review recent contributions in UAV trajectory optimisation, UAV routing and contributions addressing these two problems simultaneously. A unified framework is introduced to describe … Read more

A SQP type method for constrained multiobjective optimization

We propose an SQP type method for constrained nonlinear multiobjective optimization. The proposed algorithm maintains a list of nondominated points that is improved both for spread along the Pareto front and optimality by solving singleobjective constrained optimization problems. Under appropriate differentiability assumptions we discuss convergence to local optimal Pareto points. We provide numerical results for … Read more

On the effects of combining objectives in multi-objective optimization

In multi-objective optimization, one considers optimization problems with more than one objective function, and in general these objectives conflict each other. As the solution set of a multiobjective problem is often rather large and contains points of no interest to the decision-maker, strategies are sought that reduce the size of the solution set. One such … Read more