A polynomial size model with implicit SWAP gate counting for exact qubit reordering

Due to the physics behind quantum computing, quantum circuit designers must adhere to the constraints posed by the limited interaction distance of qubits. Existing circuits need therefore to be modified via the insertion of SWAP gates, which alter the qubit order by interchanging the location of two qubits’ quantum states. We consider the...

An Exact and Heuristic Approach for the Ship-to-Shore Problem

After a hurricane, for example hurricane Irma in Sint-Maarten, the navy can provide aid by bringing supplies, helping to clear roads and evacuating victims. If the destinations cannot be reached over land via a port, resources can be transported using smaller ships and helicopters, called connectors. This has to be done e_ciently so that the...

Economic optimization for a dual-feedstock lignocellulosic-based sustainable biofuel supply chain considering greenhouse gas emission and soil carbon stock

Environmental factors, including greenhouse gas (GHG) emissions and soil organic carbon (SOC), should be considered when building a sustainable biofuel supply chain. This work developed a three-step optimization approach integrating a geographical information system-based mixed-integer linear programming model to economically optimize the...

Classifying and modelling demand response in power systems

Demand response (DR) is expected to play a major role in integrating large shares of variable renewable energy (VRE) sources in power systems. For example, DR can increase or decrease consumption depending on the VRE availability, and use generating and network assets more efficiently. Detailed DR models are usually very complex, hence,...

Mathematical formulation of quantum circuit design problems in networks of quantum computers

Integer programming approaches to find row–column arrangements of two-level orthogonal experimental designs

Design of experiments is an effective, generic methodology for problem solving as well as for improving or optimizing product design and manufacturing processes. The most commonly used experimental designs are two-level fractional factorial designs. In recent years, nonregular fractional factorial two-level experimental designs have gained much...

A Single-Level Rule-Based Model Predictive Control Approach for Energy Management of Grid-Connected Microgrids

A single-level rule-based model predictive control (RBMPC) scheme is presented for optimizing the energy management of a grid-connected microgrid composed of local production units, renewable energy sources, local loads, and several types of energy storage systems (ESSs). The single-level controller uses two different models that yield different...

Techno-economic optimization of an energy system with sorption thermal energy storage in different energy markets

Sorption thermal energy storage (STES) has the potential to have higher energy densities and lower thermal losses compared to conventional thermal storage technologies, and it can contribute to increase the energy grid flexibility and the penetration of intermittent and distributed energy sources. However, STES is a technology still under...

Symmetry breaking in mixed integer linear programming formulations for blocking two-level orthogonal experimental designs

Two-level orthogonal designs play an important role in industrial screening experiments, in which the primary goal is to identify the treatment factors with the largest main effects on the output of a process or the performance of a product. Often, the experimental tests suggested by the orthogonal designs cannot be performed on a single day or...

Bridging the information gap of disaster responders by optimizing data selection using cost and quality

Natural disasters are chaotic and disruptive events, with compressed timelines and high levels of uncertainty. Comprehensive data on the impact becomes only available well into the response phase and data is scattered across organizations. Data heterogeneity issues are common. Consequently, responding organizations have difficulties finding data...

Constructing General Orthogonal Fractional Factorial Split-Plot Designs

While the orthogonal design of split-plot fractional factorial experiments has received much attention already, there are still major voids in the literature. First, designs with one or more factors acting at more than two levels have not yet been considered. Second, published work on nonregular fractional factorial split-plot designs was either...

Blocking Orthogonal Designs With Mixed Integer Linear Programming

We present a mixed integer linear programming approach to orthogonally block two-level, multilevel, and mixed-level orthogonal designs. The approach involves an exact optimization technique which guarantees an optimal solution. It can be applied to many problems where combinatorial methods for blocking orthogonal designs cannot be used. By means...

Economic CO2 network optimization model COCATE European project (2010-2013)

The COCATE project is a three-year collaboration project under the EU 7th framework program for research. One of the objective of COCATE project is to tackle the problems of rolling out a shared transportation infrastructure capable of connecting geological storage sites with various CO2 emitting industrial facilities. An economic model based on...

Implicit structural inversion of gravity data using linear programming, a validation study

In this study, a regional scale gravity data set has been inverted to infer the structure (topography) of the top of the basement underlying sub-horizontal strata. We apply our method to this real data set for further proof of concept, validation and benchmarking against results from an earlier forward modelling done elsewhere.Our aim is to...

Robust spectral factor approximation of discrete-time frequency domain power spectras

This paper presents a subspace-based identification algorithm for estimating the state-space quadruple [A,B,C,D] of a minimum-phase spectral factor from matrix-valued power spectrum data. For a given pair [A,C] with A stable, the minimum-phase property is guaranteed via the solution of a conic linear programming (CLP) problem. In comparison with...

Cost optimal allocation of rail passenger lines

We consider the problem of cost optimal railway line allocation for passenger trains for the Dutch railway system. At present, the allocation of passenger lines by Dutch Railways is based on maximizing the number of direct travelers. This paper develops an alternative approach that takes operating costs into account. A mathematical programming...