Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

On an Application of Microsoft Excel’s Evolutionary Solver to the Resource-Constrained Project Scheduling Problem RCPSP

The Solver Add-in of Microsoft Excel is widely used in courses on Operations Research and in industrial applications. Since the 2010 version of Microsoft Excel, the Solver Add-in comprises a so-called evolutionary solver. We analyze how this metaheuristic can be applied to the resource-constrained project scheduling problem (RCPSP). We present an implementation of a schedule-generation scheme in a spreadsheet, which combined with the evolutionary solver can be used for devising good feasible schedules. Our computational results indicate that using this approach, non-trivial instances of the RCPSP can be (approximately) solved to optimality.

Efficient Deployment of Mobile Detectors for Security Applications

We present a real-world problem that arises in security threat detection applications. The problem consists of deploying mobile detectors on moving units that follow predefined routes. Examples of such units are buses, coaches, and trolleys. Due to a limited budget not all available units can be equipped with a detector. The goal is to equip a subset of units such that the utility of the resulting coverage is maximized. Existing methods for detector deployment are designed to place detectors in fixed locations and are therefore not applicable to the problem considered here. We formulate the planning problem as a binary linear program and present a coverage heuristic for generating effective deployments in short CPU time. The heuristic has theoretical performance guarantees for important special cases of the problem. The effectiveness of the coverage heuristic is demonstrated in a computational analysis based on 28 instances that we derived from real-world data.

Engineering Tocopherol Selectivity in alpha-TTP: A Combined In Vitro/In Silico Study

"We present a combined in vitro/in silico study to determine the molecular origin of the selectivity of a-tocopherol transfer" "protein (a-TTP) towards a-tocopherol. Molecular dynamics simulations combined to free energy perturbation calculations predict a binding free energy for a-tocopherol to a-TTP 8.26+2.13 kcal mol{1 lower than that of c-tocopherol. Our calculations show that c-tocopherol binds to a-TTP in a significantly distorted geometry as compared to that of the natural ligand. Variations in the hydration of the binding pocket and in the protein structure are found as well. We propose a mutation, A156L, which significantly modifies the selectivity properties of a-TTP towards the two tocopherols. In particular, our simulations predict that A156L binds preferentially to c-tocopherol, with striking structural similarities to the wild-type- a-tocopherol complex. The affinity properties are confirmed by differential scanning fluorimetry as well as in vitro competitive binding assays. Our data indicate that residue A156 is at a critical position for determination of the selectivity of a-TTP. The engineering of TTP mutants with modulating binding properties can have potential impact at industrial level for easier purification of single tocopherols from vitamin E mixtures coming from natural oils or synthetic processes. Moreover," "the identification of a c-tocopherol selective TTP offers the possibility to challenge the hypotheses for the evolutionary development of a mechanism for a-tocopherol selection in omnivorous animals."