An Optimization Approach to the Design of Multi-Size Heliostat fields

In this paper, the problem of optimizing the heliostats field configuration of a Solar Power Tower system with heliostats of different sizes is addressed. Maximizing the efficiency of the plant, i.e., optimizing the energy generated per unit cost, leads to a difficult high dimensional optimization problem (of variable dimension) with an objective function hard to … Read more

Relay Optimization Method

Insurance-linked securities portfolio with the VaR constraint optimization problem have a kind of weak dominance or ordering property, which enables us to reduce the variables’ dimensions gradually through exercising a genetic algorithm with randomly selected initial populations. This property also enables us to add boundary attraction potential to GA-MPC’s repair operator, among other modifications such … Read more

A heuristic method for simultaneous tower and pattern-free field optimization on solar power systems

A heuristic method for optimizing a solar power tower system is proposed, in which both heliostat field (heliostat locations and number) and the tower (tower height and receiver size) are simultaneously considered. Maximizing the thermal energy collected per unit cost leads to a difficult optimization problem due to its characteristics: it has a nonconvex black-box … Read more

A search for quantum coin-flipping protocols using optimization techniques

Coin-flipping is a cryptographic task in which two physically separated, mistrustful parties wish to generate a fair coin-flip by communicating with each other. Chailloux and Kerenidis (2009) designed quantum protocols that guarantee coin-flips with near optimal bias away from uniform, even when one party deviates arbitrarily from the protocol. The probability of any outcome in … Read more

Sparsity Optimization in Design of Multidimensional Filter Networks

Filter networks are used as a powerful tool aimed at reducing the image processing time and maintaining high image quality. They are composed of sparse sub-filters whose high sparsity ensures fast image processing. The filter network design is related to solving a sparse optimization problem where a cardinality constraint bounds above the sparsity level. In … Read more

Reactive Power Management using Firefly and Spiral Optimization under Static and Dynamic Loading Conditions

Power System planning encompasses the concept of minimization of transmission losses keeping in mind the voltage stability and system reliability. Voltage profile decides the state of a system and its control is dependent on Generator source voltage, shunt/series injection, transformer taps etc. Optimal parameter setting in system level is needed for managing the available resources … Read more

Application of the Moment-SOS Approach to Global Optimization of the OPF Problem

Finding a global solution to the optimal power flow (OPF) problem is difficult due to its nonconvexity. A convex relaxation in the form of semidefinite programming (SDP) has attracted much attention lately as it yields a global solution in several practical cases. However, it does not in all cases, and such cases have been documented … Read more

Efficient upper and lower bounds for global mixed-integer optimal control

We present a control problem for an electrical vehicle. Its motor can be operated in two discrete modes, leading either to acceleration and energy consumption, or to a recharging of the battery. Mathematically, this leads to a mixed-integer optimal control problem (MIOCP) with a discrete feasible set for the controls taking into account the electrical … Read more

Mathematical Programming: Turing completeness and applications to software analysis

Mathematical Programming is Turing complete, and can be used as a general-purpose declarative language. We present a new constructive proof of this fact, and showcase its usefulness by discussing an application to finding the hardest input of any given program running on a Minsky Register Machine. We also discuss an application of Mathematical Programming to … Read more

Convex Quadratic Relaxations for Mixed-Integer Nonlinear Programs in Power Systems

This paper presents a set of new convex quadratic relaxations for nonlinear and mixed-integer nonlinear programs arising in power systems. The considered models are motivated by hybrid discrete/continuous applications where existing approximations do not provide optimality guarantees. The new relaxations offer computational efficiency along with minimal optimality gaps, providing an interesting alternative to state-of-the-art semi-definite … Read more