Martin Schlueter

• Ph.D.
• Honorary Senior Research Fellow at University of Birmingham

COVID-19 has got us to face a new situation where, for the lack of ready-to-use vaccines, it is necessary to support vaccination with complex non-pharmaceutical strategies. In this paper, we provide a novel Mixed Integer Nonlinear Programming formulation for fine-grained optimal intervention planning (i.e., at the level of the single day) against n...

This contribution presents new state-of-the-art results for ESA’s Messenger space mission benchmark, which is arguably one of the most difficult benchmarks available. The European Space Agency (ESA) created a continuous mid-scale black-box optimization benchmark which resembles an accurate model of NASA’s 2004 launched Messenger interplanetary spac...

This contribution introduces the GTOPX space mission benchmark collection, which is an extension of the GTOP database published by the European Space Agency (ESA). The term GTOPX stands for Global Trajectory Optimization Problems with eXtension. GTOPX consists of ten individual benchmark instances representing real-world interplanetary space trajec...

This contribution introduces the GTOPX space mission benchmark collection, which is an extension of GTOP database published by the European Space Agency (ESA). GTOPX consists of ten individual benchmark instances representing real-world interplanetary space trajectory design problems. In regard to the original GTOP collection, GTOPX includes three...

This contribution introduces a mixed-integer extension to the well-known Cassini1 space mission benchmark published by the European Space Agency (ESA). Due to it's highly nonlinear function properties, the Cassini1 benchmark is widely recognized by the evolutionary computing community as interesting test case. The Cassini1 benchmark implements a si...

This contribution presents numerical results for global optimization of a multi-objective formulation of the well-known Cassini1 interplanetary space trajectory benchmark published by the European Space Agency (ESA). The original Cassini1 bench-mark is extended to four objectives and thus classified as many-objective problem. The MIDACO optimizatio...

This contribution presents numerical results for optimizing a many-objective space mission trajectory benchmark under consideration of massively parallelized co-evaluation of solution candidates. The considered benchmark is the well-known Cassini1 instance published by the European Space Agency (ESA) extended to four objectives. The MIDACO optimiza...

In this paper, we provide a novel framework to assess the vulnerability/robustness of a network with respect to pair-wise nodes' connectivity. In particular, we consider attackers that aim, at the same time, at dealing the maximum possible damage to the network in terms of the residual connectivity after the attack and at keeping the cost of the at...

Cloud computing in the field of scientific applications such as scientific big data processing and big data analytics has become popular because of its service oriented model that provides a pool of abstracted, virtualized, dynamically scalable computing resources and services on demand over the Internet. However, resource selection to make the rig...

This contribution presents a numerical evaluation of the impact of parallelization on the performance of an evolutionary algorithm for mixed-integer nonlinear programming (MINLP). On a set of 200 MINLP benchmarks the performance of the MIDACO solver is assessed with gradually increasing parallelization factor from one to three hundred. The results...

The design and optimization of interplanetary space mission trajectories is known to be a difficult challenge. The trajectory of the Messenger mission (launched by NASA in 2004) is one of the most complex ones ever created. The European Space Agency (ESA) makes available a numerical optimization benchmark which resembles an accurate model of Messen...

In this paper an heuristic optimisation technique for a characteristic response curve of CFRP z-frames used in aerospace applications is investigated. Therein, the focus is to identify a dynamic response being most suitable to map onto a specified reference curve. For that purpose a parametric finite element model was established. Discrete laminate...

A novel algorithm for many-objective optimization based on continuous Ant Colony Optimization (AGO) is proposed.

A numerical study of the MIDACO optimization software on the well known GTOP benchmark set, published by the European Space Agency (ESA), is presented. The GTOP database provides trajectory models of real-world interplanetary space missions such as Cassini, Messenger or Rosetta. The trajectory models are formulated as constrained nonlinear optimiza...

The impact of parallelization on the optimization process of space mission trajectories is investigated in this contribution. As space mission trajectory reference model, the well known Cassini1 benchmark, published by the European Space Agency (ESA), is considered and solved here with the MIDACO optimization software. It can be shown that signific...

A new wearable computing era featuring devices such as Google Glass, smartwatches, and digital contact lenses is almost upon us, bringing with it usability issues that conventional human computer interaction (HCI) modalities cannot resolve. Brain computer interface (BCI) technology is also rapidly advancing and is now at a point where noninvasive B...

This paper presents a numerical study on MIDACO, a new global optimization software for mixed integer nonlinear programming (MINLP) based on ant colony optimization and the oracle penalty method. Extensive and rigorous numerical tests on a set of 100 non-convex MINLP benchmark problems from the open literature are performed. Results obtained by MID...

Two different parallelization strategies for evo- lutionary algorithms for mixed integer nonlinear programming (MINLP) are discussed and numerically compared in this contri- bution. The first strategy is to parallelize some internal parts of the evolutionary algorithm. The second strategy is to parallelize the MINLP function calls outside and indep...

A numerical study on two challenging MINLP space applications and their optimization with MIDACO, which is a recently developed general purpose optimization software, is pre- sented. The applications are in particular the optimal control of the ascent of a multiple-stage space launch vehicle and the space mission trajectory design from Earth to Jup...

In this thesis a new algorithm for mixed integer nonlinear programming (MINLP) is developed and applied to several real world applications with special focus on space applications. The algorithm is based on two main components, which are an extension of the Ant Colony Optimization metaheuristic and the Oracle Penalty Method for constraint handling....

A new and universal penalty method is introduced in this contribution. It is especially intended to be applied in stochastic metaheuristics like genetic algorithms, particle swarm optimization or ant colony optimization. The novelty of this method is, that it is an advanced approach that only requires one parameter to be tuned. Moreover this parame...

Two novel extensions for the well known ant colony optimization (ACO) framework are introduced here, which allow the solution of mixed integer nonlinear programs (MINLPs). Furthermore, a hybrid implementation (ACOmi) based on this extended ACO framework, specially developed for complex non-convex MINLPs, is presented together with numerical results...

The problem of integrated process and control system design is discussed in this paper. We formulate it as a mixed integer nonlinear programming problem subject to differential-algebraic constraints. This class of problems is frequently non-convex and, therefore, local optimization techniques usually fail to locate the global solution. Here we prop...