Designing and comparing multiple portfolios of parameter configurations for online algorithm selection

National Research Foundation (NRF) Singapore under its International Research Centres in Singapore Funding Initiativ

A case study of algorithm selection for the traveling thief problem

Published online: 7 April 2017Many real-world problems are composed of several interacting components. In order to facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in 2013 as the combination of two well-understood combinatorial optimization problems. With this article, we contribute in four ways. First, we create a comprehensive dataset that comprises the performance data of 21 TTP algorithms on the full original set of 9720 TTP instances. Second, we define 55 characteristics for all TPP instances that can be used to select the best algorithm on a per-instance basis. Third, we use these algorithms and features to construct the first algorithm portfolios for TTP, clearly outperforming the single best algorithm. Finally, we study which algorithms contribute most to this portfolio.Markus Wagner, Marius Lindauer, Mustafa Mısır, Samadhi Nallaperuma, Frank Hutte

The synthesis and characterization of novel (E,E)-dioxime and its nickel (II) complexes containing compartmental and twofold macrocyclic moieties

A new (E,E)-dioxime, S,S′-bis(2-acetophenone)dithioglyoxime, has been synthesized by the reaction of dichloroglyoxime with 2-thioacetophenone. Only mononuclear Ni (II) complex with a metal:ligand ratio (1:2) was prepared and then Ni(II) complex bridged BF 2 + was obtained with hydrogen-bridged Ni(II) complex and boron trifluoride etherate. The reaction of BF 2 + -capped Ni(II) complex with 4′,5′- diaminobenzo [15-crown-5] gave a twofold complex. The structure of ligand and Ni(II) complexes are proposed according to elemental analyses, 1 H, 13 C NMR, IR and mass spectral data and semi-empirical quantum chemical calculations. Graphical Abstract: Synthesis and characterization of novel (E,E)-dioxime and its Ni(II) complex as well as the BF 2 -bridged complex were prepared. Then the nickel(II) complex containing compartmental and twofold macrocyclic moieties has been synthesized by the macrocyclization reaction of 4′,5′-diaminobenzo[15-crown-5] with BF 2 + -capped nickel(II) complex. [Figure not available: see fulltext.] © 2012 Springer Science+Business Media B.V

The synthesis and characterization of novel (E,E)-dioxime and its nickel (II) complexes containing compartmental and twofold macrocyclic moieties

A new (E,E)-dioxime, S,S'-bis(2-acetophenone)dithioglyoxime, has been synthesized by the reaction of dichloroglyoxime with 2-thioacetophenone. Only mononuclear Ni (II) complex with a metal:ligand ratio (1:2) was prepared and then Ni(II) complex bridged BF 2 + was obtained with hydrogen-bridged Ni(II) complex and boron trifluoride etherate. The reaction of BF 2 + -capped Ni(II) complex with 4',5'- diaminobenzo [15-crown-5] gave a twofold complex. The structure of ligand and Ni(II) complexes are proposed according to elemental analyses, 1 H, 13 C NMR, IR and mass spectral data and semi-empirical quantum chemical calculations. Graphical Abstract: Synthesis and characterization of novel (E,E)-dioxime and its Ni(II) complex as well as the BF 2 -bridged complex were prepared. Then the nickel(II) complex containing compartmental and twofold macrocyclic moieties has been synthesized by the macrocyclization reaction of 4',5'-diaminobenzo[15-crown-5] with BF 2 + -capped nickel(II) complex. [Figure not available: see fulltext.] © 2012 Springer Science+Business Media B.V

Geoteknik mühendisliğinde sayısal yöntemlerin kullanılması

This chapter reports on the design, implementation and results from GlacsWeb, an environmental sensor network for glaciers installed in Summer 2004 at Briksdalsbreen, Norway. The importance of power control, hardware architecture and communication systems are discussed and research issues highlighted

Characterization of Neighborhood Behaviours in a Multi-neighborhood Local Search Algorithm

We consider a multi-neighborhood local search algorithm with a large number of possible neighborhoods. Each neighborhood is accompanied by a weight value which represents the probability of being chosen at each iteration. These weights are fixed before the algorithm runs, and are considered as parameters of the algorithm. Given a set of instances, off-line tuning of the algorithm's parameters can be done by automated algorithm configuration tools (e.g., SMAC). However, the large number of neighborhoods can make the tuning expensive and difficult even when the number of parameters has been reduced by some intuition. In this work, we propose a systematic method to characterize each neighborhood's behaviours, representing them as a feature vector, and using cluster analysis to form similar groups of neighborhoods. The novelty of our characterization method is the ability of reflecting changes of behaviours according to hardness of different solution quality regions. We show that using neighborhood clusters instead of individual neighborhoods helps to reduce the parameter configuration space without misleading the search of the tuning procedure. Moreover, this method is problem-independent and potentially can be applied in similar contexts.13 pagesstatus: publishe

Learning to Configure Mathematical Programming Solvers by Mathematical Programming

International audienceWe discuss the issue of finding a good mathematical programming solver configuration for a particular instance of a given problem, and we propose a two-phase approach to solve it. In the first phase we learn the relationships between the instance, the configuration and the performance of the configured solver on the given instance. A specific difficulty of learning a good solver configuration is that parameter settings may not all be independent; this requires enforcing (hard) constraints, something that many widely used supervised learning methods cannot natively achieve. We tackle this issue in the second phase of our approach, where we use the learnt information to construct and solve an optimization problem having an explicit representation of the dependency/consistency constraints on the configuration parameter settings. We discuss computational results for two different instantiations of this approach on a unit commitment problem arising in the short-term planning of hydro valleys. We use logistic regression as the supervised learning methodology and consider CPLEX as the solver of interest