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articles.bib
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%%%%%%%%%%%%%%%%%%%-*- mode: bibtex; bibtex-maintain-sorted-entries: plain; bibtex-string-files: ("abbrev.bib" "journals.bib" "authors.bib") -*-
%% articles.bib : https://iridia-ulb.github.io/references/
%%
%% To the extent that the contents of bib files may be subject to
%% copyright, the contents of the IRIDIA BibTeX Repository are placed
%% under the public domain by associating it to the Creative Commons CC0
%% 1.0 Universal license (http://creativecommons.org/publicdomain/zero/1.0/).
%
%% READ THESE RULES FIRST BEFORE MODIFYING THIS FILE
%% 1. This file should only contain 'article' entries.
%% 2. Keep the entries sorted with respect to the key.
%% 3. Check that what you are adding has not been added already with a
%% different key.
%% 4. 'author' and 'editor' fields should be taken from authors.bib.
%% 5. 'publishers', 'series' and 'institution' should be taken from abbrev.bib.
%% 6. 'journal' should be taken from journal.bib.
%% 7. The 'alias' field is used when a repeated entry is found.
%% Delete one and add its key as the alias field of the other.
%% This helps to locate entries that have been renamed or deleted.
%% 8. Since some bib-styles mandate title-case but others mandate sentence-case
%% and converting from title-case to sentence-case is done automatically but
%% the opposite cannot be done, then titles should preferably be in
%% title-case like "Data Structures and Algorithms". If a word or a letter
%% should always be in upper (or lower) case, then surround them with
%% braces, like in "The {ACO} Book", or "The {Pareto} Front".
%% 9. Braces can prevent kerning between letters, so it is in general
%% preferable to enclose entire words and not just single letters in braces
%% to protect them.
%%10. The fields 'pdf', 'supplement', and 'epub' can be used to point out to a
%% preferred PDF filename, a url containing supplementary material and a url
%% containing the document, respectively. These fields will be ignored by
%% most BibTeX styles (.bst files), but they can be used with custom styles
%% to, for example, generate an HTML bibliography, a list of publications.
%% See testbib.tex for an example.
%%11. If you wish to add an entry for supplementary material to another
%% publication, please use a Misc entry with the same label as for the main
%% publication adding -supp at the end. Example: the supplementary material
%% entry for BezLopStu2012:ants would be BezLopStu2012:ants-supp.
%% This keeps the entries together, making easier to keep them in sync.
%%12. Use the following abbreviations for months: jan, feb, mar, apr, may, jun,
%% jul, aug, sep, oct, nov, dec. Some bibstyles will abbreviate the months,
%% others may use numeric values and others will use the full name. Using
%% the abbreviations allows this customization to be consistent.
%%13. biblatex warns if 'month' field contains more than one month.
%% Use the 'date' field in that case.
%% Z. Some of the entries do not follow the above rules.
%% Please help us to update them little by little.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@Article{AbdGad2012dynamic,
author = {Abdelkhalik, Ossama and Gad, Ahmed},
title = {Dynamic-Size Multiple Populations Genetic Algorithm for Multigravity-Assist Trajectory Optimization},
journal = jgcd,
year = 2012,
volume = 35,
number = 2,
pages = {520--529},
doi = {10.2514/1.54330}
}
@Article{AbrAmoDan1999,
title = {Simulated annealing cooling schedules for the school timetabling problem},
author = Abramson_D #and# {Amoorthy, Mohan Krishna and Dang, Henry},
journal = apjor,
volume = 16,
number = 1,
pages = {1--22},
year = 1999,
}
@Article{Abramson1991,
title = {Constructing School Timetables Using Simulated Annealing: Sequential and Parallel Algorithms},
author = Abramson_D,
journal = ms,
volume = 37,
number = 1,
pages = {98--113},
year = 1991,
publisher = informs
}
@Article{Ach2009mpc,
author = {Tobias Achterberg},
title = "{SCIP}: {Solving} constraint integer programs",
journal = mpc,
year = 2009,
volume = 1,
number = 1,
month = jul,
pages = {1--41},
epub = {http://mpc.zib.de/archive/2009/1/Achterberg2009_Article_SCIPSolvingConstraintIntegerPr.pdf}
}
@Article{AchBer2007,
title = {Improving the feasibility pump},
author = {Achterberg, Tobias and Berthold, Timo},
journal = do,
volume = 4,
number = 1,
pages = {77--86},
year = 2007,
publisher = elsevier
}
@Article{AcoMes2014jbi,
author = {H{\'e}ctor-Gabriel Acosta-Mesa and Fernando Rechy-Ram{\'i}rez}
#and# Mezura-Montes #and# {Nicandro Cruz-Ram{\'i}rez and
Hern{\'a}ndez Jim{\'e}nez, Rodolfo},
title = {Application of time series discretization using evolutionary programming for classification of precancerous cervical lesions},
journal = jbi,
volume = 49,
pages = {73--83},
year = 2014,
doi = {10.1016/j.jbi.2014.03.004},
keywords = {irace},
}
@Article{AddLocSch2008,
title = {Disk Packing in a Square: A New Global Optimization Approach},
author = {Addis, Bernardetta and Locatelli, Marco and Schoen, Fabio},
journal = informsjoc,
year = 2008,
number = 4,
pages = {516--524},
volume = 20,
doi = {10.1287/ijoc.1080.0263},
alias = "Addis2008"
}
@Article{Ade92,
author = {B. Adenso-D{\'i}az},
title = {Restricted Neighborhood in the Tabu Search for the
Flowshop Problem},
journal = ejor,
year = 1992,
volume = 62,
number = 1,
pages = {27--37}
}
@Article{AdeLag06tuning,
author = {Belarmino Adenso-D{\'i}az} #and# Laguna,
title = {Fine-Tuning of Algorithms Using Fractional Experimental
Design and Local Search},
journal = or,
year = 2006,
volume = 54,
number = 1,
pages = {99--114},
keywords = {Calibra, heuristic search, parameter setting, Taguchi design
of experiments},
doi = {10.1287/opre.1050.0243}
}
@Article{AdrBieSha2022jair,
title = {Automated dynamic algorithm configuration},
author = Adriaensen_S #and# Biedenkapp #and# {Shala, Gresa and Awad, Noor and Eimer, Theresa} #and# Lindauer_M #and# Hutter,
journal = jair,
volume = 75,
pages = {1633--1699},
year = 2022,
doi = {10.1613/jair.1.13922}
}
@Article{AfsMieRui2021survey,
author = {Afsar, Bekir} #and# Miettinen #and# Ruiz_Francisco,
title = {Assessing the Performance of Interactive Multiobjective
Optimization Methods: A Survey},
year = 2021,
volume = 54,
number = 4,
doi = {10.1145/3448301},
abstract = {Interactive methods are useful decision-making tools for
multiobjective optimization problems, because they allow a
decision-maker to provide her/his preference information
iteratively in a comfortable way at the same time as (s)he
learns about all different aspects of the problem. A wide
variety of interactive methods is nowadays available, and
they differ from each other in both technical aspects and
type of preference information employed. Therefore, assessing
the performance of interactive methods can help users to
choose the most appropriate one for a given problem. This is
a challenging task, which has been tackled from different
perspectives in the published literature. We present a
bibliographic survey of papers where interactive
multiobjective optimization methods have been assessed
(either individually or compared to other methods). Besides
other features, we collect information about the type of
decision-maker involved (utility or value functions,
artificial or human decision-maker), the type of preference
information provided, and aspects of interactive methods that
were somehow measured. Based on the survey and on our own
experiences, we identify a series of desirable properties of
interactive methods that we believe should be assessed.},
journal = acm-cs,
numpages = 27,
keywords = {decision-makers, Interactive methods, performance assessment,
preference information, multiobjective optimization problems}
}
@Article{AfsSilMis2022design,
author = {Afsar, Bekir} #and# {Silvennoinen, Johanna} #and# {Misitano,
Giovanni} #and# Ruiz_Francisco #and# {Ruiz, Ana B.} #and#
Miettinen,
title = {Designing empirical experiments to compare interactive
multiobjective optimization methods},
journal = jors,
year = 2022,
volume = 74,
number = 11,
pages = {2327--2338},
month = nov,
doi = {10.1080/01605682.2022.2141145}
}
@Article{AgoPea1973normality,
doi = {10.2307/2335012},
year = 1973,
month = dec,
publisher = {{JSTOR}},
volume = 60,
number = 3,
pages = {613--622},
author = {Ralph {D'Agostino} and E. S. Pearson},
title = {Tests for Departure from Normality. Empirical Results for the
Distributions of $b_2$ and $\surd b_1$},
journal = biometrika
}
@Article{Agrell1997ejor,
title = {On redundancy in multi criteria decision making},
journal = ejor,
volume = 98,
number = 3,
pages = {571--586},
year = 1997,
doi = {10.1016/0377-2217(95)00340-1},
author = {Per J. Agrell},
keywords = {Multi criteria decision making, Redundancy, objective
reduction, Vector optimisation},
abstract = {The concept of redundancy is accepted in Operations Research
and Information Theory. In Linear Programming, a constraint
is said to be redundant if the feasible decision space is
identical with or without the constraint. In Information
Theory, redundancy is used as a measure of the stability
against noise in transmission. Analogies with Multi Criteria
Decision Making (MCDM) are indicated and it is argued that
the redundancy concept should be used as a regular feature in
conditioning and analysis of Multi Criteria
Programs. Properties of a proposed conflict-based
characterisation are stated and some existence results are
derived. Redundancy is here intended for interactive methods,
when the efficient set is progressively explored. A new
redundancy test for the linear case is formulated from the
framework. A probabilistic method based on correlation is
proposed and tested for the non-linear case. Finally, some
general guidelines are given concerning the redundancy
problem.}
}
@Article{AguTan2007ejor,
title = "Working principles, behavior, and performance of {MOEAs} on
{MNK}-landscapes",
author = Aguirre #and# Tanaka,
journal = ejor,
volume = 181,
number = 3,
year = 2007,
pages = {1670--1690},
doi = {10.1016/j.ejor.2006.08.004}
}
@Article{AhmOsm2004:aor,
author = {Samad Ahmadi} #and# Osman,
title = {Density Based Problem Space Search for the Capacitated Clustering $p$-Median Problem},
journal = aor,
year = 2004,
volume = 131,
pages = {21--43}
}
@Article{AhrElsSarEss2021weighted,
title = {Weighted pointwise prediction method for dynamic
multiobjective optimization},
journal = is,
volume = 546,
pages = {349--367},
year = 2021,
author = {Ali Ahrari and Saber Elsayed and Ruhul Sarker and Daryl
Essam} #and# Coello,
}
@Article{AhuErgOrlPun2002:dam,
author = Ahuja_RK #and# {O. Ergun} #and# {A. P. Punnen},
title = {A Survey of Very Large-scale Neighborhood Search
Techniques},
journal = dam,
year = 2002,
volume = 123,
number = {1--3},
pages = {75--102}
}
@Article{AieResRib2006ttt,
author = {Aiex, Renata M.} #and# Resende #and# Ribeiro,
title = {{TTT} plots: a perl program to create time-to-target plots},
journal = ol,
year = 2006,
volume = 1,
number = 4,
pages = {355--366},
month = oct,
doi = {10.1007/s11590-006-0031-4},
keywords = {ECDF, runtime distribution}
}
@Article{AinKumCha2009asc,
author = Aine_S #and# Kumar_Rajeev #and# Chakrabarti_PP,
title = {Adaptive parameter control of evolutionary
algorithms to improve quality-time trade-off},
journal = asoco,
volume = 9,
number = 2,
year = 2009,
pages = {527--540},
doi = {10.1016/j.asoc.2008.07.001},
keywords = {anytime},
}
@Article{AlbLanSte2010,
author = {Albrecht, A. A. and Lane, P. C. R. and Steinh{\"o}fel, K.},
title = {Analysis of Local Search Landscapes for k-{SAT} Instances},
journal = mcs,
number = 4,
pages = {465--488},
volume = 3,
year = 2010,
doi = {10.1007/s11786-010-0040-7}
}
@Article{Albers2003online,
title = {Online Algorithms: A Survey},
author = {Albers, Susanne},
journal = mp,
year = 2003,
number = 1,
pages = {3--26},
volume = 97,
}
@Article{AleMos2016slr,
author = {Aldeida Aleti and Irene Moser},
year = 2016,
title = {A systematic literature review of adaptive parameter control
methods for evolutionary algorithms},
journal = acm-cs,
volume = 49,
number = "3, Article 56",
month = oct,
pages = 35,
doi = {10.1145/2996355}
}
@Article{AlfRuiPagStu2020hybrid,
title = {Automatic Algorithm Design for Hybrid Flowshop Scheduling
Problems},
author = Alfaro-Fernandez #and# Ruiz_Ruben #and# Pagnozzi #and#
Stuetzle,
journal = ejor,
volume = 282,
number = 3,
pages = {835--845},
year = 2020,
doi = {10.1016/j.ejor.2019.10.004},
keywords = {Scheduling, Hybrid flowshop, Automatic algorithm
configuration, Automatic Algorithm Design},
abstract = {Industrial production scheduling problems are challenges that
researchers have been trying to solve for decades. Many
practical scheduling problems such as the hybrid flowshop are
NP-hard. As a result, researchers resort to metaheuristics to
obtain effective and efficient solutions. The traditional
design process of metaheuristics is mainly manual, often
metaphor-based, biased by previous experience and prone to
producing overly tailored methods that only work well on the
tested problems and objectives. In this paper, we use an
Automatic Algorithm Design (AAD) methodology to eliminate
these limitations. AAD is capable of composing algorithms
from components with minimal human intervention. We test the
proposed AAD for three different optimization objectives in
the hybrid flowshop. Comprehensive computational and
statistical testing demonstrates that automatically designed
algorithms outperform specifically tailored state-of-the-art
methods for the tested objectives in most cases.}
}
@Article{AliMei2011kemeny,
annote = {Computational Foundations of Social Choice},
year = 2012,
month = jul,
publisher = {Elsevier {BV}},
volume = 64,
number = 1,
pages = {28--40},
author = {Alnur Ali and Marina Meil{\u{a}}},
doi = {10.1016/j.mathsocsci.2011.08.008},
journal = mss,
title = {Experiments with {Kemeny} ranking: What Works When?},
keywords = "Borda ranking, Kemeny ranking"
}
@Article{AllAyd2013,
title = {Algorithms for no-wait flowshops with total
completion time subject to makespan},
author = {Allahverdi, Ali and Aydilek, Harun},
journal = ijamt,
pages = {1--15},
year = 2013
}
@Article{AllJasLieTam2022cor,
title = {What if we increase the number of objectives? {Theoretical}
and empirical implications for many-objective combinatorial
optimization},
author = Allmendinger #and# Jaszkiewicz #and# Liefooghe #and# {Tammer,
Christiane},
doi = {10.1016/j.cor.2022.105857},
journal = cor,
volume = 145,
pages = 105857,
year = 2022,
publisher = {Elsevier}
}
@Article{AllKno2013ephemeral,
title = {On Handling Ephemeral Resource Constraints in Evolutionary
Search},
author = Allmendinger #and# Knowles,
year = 2013,
month = sep,
journal = ec,
volume = 21,
number = 3,
pages = {497--531},
issn = {1063-6560, 1530-9304},
doi = {10.1162/EVCO_a_00097},
abstract = {We consider optimization problems where the set of solutions
available for evaluation at any given time t during
optimization is some subset of the feasible space. This model
is appropriate to describe many closed-loop optimization
settings (i.e. where physical processes or experiments are
used to evaluate solutions) where, due to resource
limitations, it may be impossible to evaluate particular
solutions at particular times (despite the solutions being
part of the feasible space). We call the constraints
determining which solutions are non-evaluable ephemeral
resource constraints (ERCs). In this paper, we investigate
two specific types of ERC: one encodes periodic resource
availabilities, the other models `commitment' constraints
that make the evaluable part of the space a function of
earlier evaluations conducted. In an experimental study, both
types of constraint are seen to impact the performance of an
evolutionary algorithm significantly. To deal with the
effects of the ERCs, we propose and test five different
constrainthandling policies (adapted from those used to
handle `standard' constraints), using a number of different
test functions including a fitness landscape from a real
closed-loop problem. We show that knowing information about
the type of resource constraint in advance may be sufficient
to select an effective policy for dealing with it, even when
advance knowledge of the fitness landscape is limited.},
}
@Article{Alm10,
author = Almeder,
title = {A hybrid optimization approach for multi-level
capacitated lot-sizing problems},
number = 2,
journal = ejor,
year = 2010,
keywords = {Ant colony optimization, Manufacturing, Material
requirements planning, Mixed-integer programming},
pages = {599--606},
volume = 200,
doi = {10.1016/j.ejor.2009.01.019},
abstract = {Solving multi-level capacitated lot-sizing problems
is still a challenging task, in spite of increasing
computational power and faster algorithms. In this
paper a new approach combining an ant-based
algorithm with an exact solver for (mixed-integer)
linear programs is presented. A {MAX-MIN} ant system
is developed to determine the principal production
decisions, a {LP/MIP} solver is used to calculate
the corresponding production quantities and
inventory levels. Two different local search methods
and an improvement strategy based on reduced
mixed-integer problems are developed and integrated
into the ant algorithm. This hybrid approach
provides superior results for small and medium-sized
problems in comparison to the existing approaches in
the literature. For large-scale problems the
performance of this method is among the best},
}
@Article{AluKat2004:ieee,
author = {S. Alupoaei and S. Katkoori},
title = {Ant Colony System Application to Marcocell Overlap Removal},
journal = tvlsis,
year = 2004,
volume = 12,
number = 10,
pages = {1118--1122}
}
@Article{Amaral2012corridor,
title = "The Corridor Allocation Problem",
journal = cor,
volume = 39,
number = 12,
pages = "3325--3330",
year = 2012,
author = "Amaral, Andr{\'e} R. S.",
doi = "10.1016/j.cor.2012.04.016",
keywords = "Facility layout, Double row layout, Integer programming",
abstract = "The corridor allocation problem (CAP) seeks an arrangement of
facilities along a central corridor defined by two horizontal
lines parallel to the x-axis of a Cartesian coordinate
system. The objective is to minimize the total communication
cost among facilities, while respecting two main conditions:
(i) no space is allowed between two adjacent facilities; (ii)
the left-most point of the arrangement on either line should
have zero abscissa. The conditions (i) and (ii) are required
in many applications such as the arrangement of rooms at
office buildings or hospitals. The CAP is a NP-Hard
problem. In this paper, a mixed-integer programming
formulation of the CAP is proposed, which allows us to
compute optimal layouts in reasonable time for problem
instances of moderate sizes. Moreover, heuristic procedures
are presented that can handle larger instances."
}
@Article{AmiBadFar2007:cis,
author = {Amir, C. and Badr, A. and Farag, I},
title = {A Fuzzy Logic Controller for Ant Algorithms},
journal = cis,
year = 2007,
volume = 11,
number = 2,
pages = {26--34}
}
@Article{AndDefDouJor2003,
title = {An Introduction to {MCMC} for Machine Learning},
author = Andrieu_C #and# DeFreitas_N #and# Doucet_A #and# Jordan_MI,
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volume = 50,
number = {1-2},
pages = {5--43},
year = 2003,
publisher = springer
}
@Article{AndFagHob2015maritime,
author = {Andersson, Henrik and Fagerholt, Kjetil and Hobbesland,
Kirsti},
title = {Integrated maritime fleet deployment and speed optimization:
Case study from {RoRo} shipping},
journal = cor,
year = 2015,
volume = 55,
pages = {233--240},
month = mar,
doi = {10.1016/j.cor.2014.03.017}
}
@Article{AndJorLin1996,
author = {Andersen, K. A. and J{\"o}rnsten, K. and Lind, M.},
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volume = 23,
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year = 1996,
}
@Article{AnejaNair79,
author = {Aneja, Y. P. and Nair, K. P. K.},
title = {Bicriteria Transportation Problem},
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volume = 25,
number = 1,
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year = 1979,
}
@Article{AngBamGou2004tcs,
author = {Eric Angel} #and# {Evripidis Bampis} #and# {Laurent
Gourv{\'e}s},
title = {Approximating the {Pareto} curve with local search
for the bicriteria {TSP}(1,2) problem},
journal = tcs,
number = {1-3},
pages = {135--146},
volume = 310,
year = 2004,
doi = {10.1016/S0304-3975(03)00376-1},
keywords = {Archiving, Local search, Multicriteria TSP,
Approximation algorithms}
}
@Article{AngWoo09,
author = Angus #and# "Clinton Woodward",
title = {Multiple Objective Ant Colony Optimisation},
journal = swarm,
year = 2009,
volume = 3,
number = 1,
pages = {69--85},
doi = {10.1007/s11721-008-0022-4},
}
@Article{AnjVie2017flp,
title = {Mathematical optimization approaches for facility layout
problems: The state-of-the-art and future research
directions},
author = {Anjos, Miguel F. and Vieira, Manuel V. C.},
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volume = 261,
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pages = {1--16},
year = 2017,
publisher = {Elsevier}
}
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author = {Kurt Anstreicher and Nathan Brixius and Jean-Pierre Goux and
Jeff Linderoth},
title = {Solving large quadratic assignment problems on computational
grids},
doi = {10.1007/s101070100255},
year = 2002,
month = feb,
volume = 91,
number = 3,
pages = {563--588},
journal = mpb,
abstract = "The quadratic assignment problem (QAP) is among the hardest
combinatorial optimization problems. Some instances of size
$n = 30$ have remained unsolved for decades. The solution of
these problems requires both improvements in mathematical
programming algorithms and the utilization of powerful
computational platforms. In this article we describe a novel
approach to solve QAPs using a state-of-the-art
branch-and-bound algorithm running on a federation of
geographically distributed resources known as a computational
grid. Solution of QAPs of unprecedented complexity, including
the nug30, kra30b, and tho30 instances, is reported."
}
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year = 2003,
volume = 97,
number = {1--2},
pages = {91--153},
doi = "10.1007/s10107-003-0440-4"
}
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author = Applegate_D #and# Bixby #and# Chvatal #and# Cook_W,
title = "On the Solution of Traveling Salesman Problems",
journal = "Documenta Mathematica",
year = 1998,
volume = "Extra Volume ICM III",
pages = "645--656",
}
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their application to other scheduling problems},
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year = 1961,
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number = 4,
pages = {237--245},
doi = {10.1093/comjnl/3.4.237}
}
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author = Applegate_D #and# Cook_W,
title = "A Computational Study of the Job-Shop Scheduling
Problem",
journal = orsa,
year = 1991,
volume = 3,
number = 2,
pages = "149--156",
}
@Article{AppCooRoh2003,
title = {Chained {Lin}-{Kernighan} for Large Traveling Salesman
Problems},
author = Applegate_D #and# Cook_W #and# " Andr{\'e} Rohe",
journal = informsjoc,
volume = 15,
number = 1,
pages = {82--92},
year = 2003,
alias = "AppCooRoh99",
doi = "10.1287/ijoc.15.1.82.15157"
}
@Article{AppEtAl09,
author = Applegate_D #and# Bixby #and# Chvatal #and# Cook_W #and# "
D. Espinoza and M. Goycoolea " #and# Helsgaun,
title = {Certification of an Optimal {TSP} Tour Through 85,900 Cities},
journal = orl,
volume = 37,
number = 1,
year = 2009,
pages = {11--15}
}
@Article{AraCamCam2022openletter,
author = Aranha #and# Camacho_C #and# Campelo #and# Dorigo #and# Ruiz_Ruben #and# Sevaux_M #and# Sorensen #and# Stuetzle,
title = {Metaphor-based Metaheuristics, a Call for Action: the Elephant in the Room},
journal = swarm,
pages = {1--6},
volume = 16,
number = 1,
doi = "10.1007/s11721-021-00202-9",
year = 2022
}
@Article{ArcSavSpe2016vehicle,
title = {The Vehicle Routing Problem with Occasional Drivers},
author = {Archetti, Claudia} #and# Savelsbergh_M #and# Grazia_Speranza,
journal = ejor,
volume = 254,
number = 2,
pages = {472--480},
year = 2016,
doi = "10.1016/j.ejor.2016.03.049",
publisher = {Elsevier}
}
@Article{ArnSanSorVid2019,
author = Arnold_F #and# {Santana, \'{I}talo} #and# Sorensen #and#
Vidal_T,
title = {{PILS}: Exploring high-order neighborhoods by pattern mining
and injection},
journal = arxiv # {1912.11462 [cs.AI]},
year = 2019,
doi = {10.48550/arXiv.1912.11462}
}
@Article{ArnSor2019knowledge,
author = Arnold_F #and# Sorensen,
title = {Knowledge-guided local search for the vehicle routing
problem},
journal = cor,
year = 2019,
volume = 105,
pages = {32--46},
doi = {10.1016/j.cor.2019.01.002}
}
@Article{ArnSor2019vrp,
author = Arnold_F #and# Sorensen,
title = {What makes a {VRP} solution good? The generation of
problem-specific knowledge for heuristics},
journal = cor,
year = 2019,
volume = 106,
pages = {280--288},
doi = {10.1016/j.cor.2018.02.007}
}
@Article{AroKadKhu2006,
title = {An empirical comparison of tabu search, simulated annealing,
and genetic algorithms for facilities location problems},
author = {Arostegui Jr, Marvin A. and Kadipasaoglu, Sukran N. and Khumawala, Basheer M.},
journal = ijpe,
volume = 103,
number = 2,
pages = {742--754},
year = 2006,
publisher = elsevier
}
@Article{Arr04,
title = "A partial enumeration heuristic for multi-objective
flowshop scheduling problems",
author = Arroyo_JEC #and# Armentano,
journal = jors,
volume = 55,
number = 9,
pages = {1000--1007},
year = 2004,
}
@Article{ArrArm05,
author = Arroyo_JEC #and# Armentano,
title = "Genetic local search for multi-objective flowshop
scheduling problems",
journal = ejor,
volume = 167,
number = 3,
pages = "717--738",
year = 2005,
keywords = "Multicriteria Scheduling",
}
@Article{ArrLeu2017,
author = Arroyo_JEC #and# Leung_JYT,
title = {An Effective Iterated Greedy Algorithm for Scheduling Unrelated Parallel Batch Machines with Non-identical Capacities and Unequal Ready Times},
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year = 2017,
volume = 105,
pages = {84--100}
}
@Article{ArzCebIru2022jcgs,
author = {Arza, Etor} #and# Ceberio #and# Irurozki_E #and# {P{\'e}rez,
Aritz},
title = {Comparing Two Samples Through Stochastic Dominance: A
Graphical Approach},
journal = jcgs,
year = 2022,
pages = {1--38},
month = jun,
doi = {10.1080/10618600.2022.2084405}
}
@Article{Asch01tsptw,
author = Ascheuer #and# Fischetti #and# Groetschel,
title = {Solving asymmetric travelling salesman problem with
time windows by branch-and-cut},
journal = mp,
year = 2001,
volume = 90,
pages = {475--506}
}
@Article{AssWanFre2014hetero,
author = {John{-}Alexander M. Assael and Ziyu Wang} #and# DeFreitas_N,
title = {Heteroscedastic Treed Bayesian Optimisation},
journal = arxiv # {1410.7172},
doi = "10.48550/arXiv.1410.7172",
year = 2014,
eprinttype = {arXiv},
eprint = {1410.7172},
keywords = "Treed-GP"
}
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journal = mp,
year = 2003,
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number = 1,
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}
@Article{AuBigCar2021perf,
author = Audet_C #and# {Bigeon, Jean and Cartier, Dominique and Le
Digabel, S{\'e}bastien and Salomon, Ludovic},
title = {Performance indicators in multiobjective optimization},
journal = ejor,
year = 2021,
volume = 292,
number = 2,
pages = {397--422},
doi = {10.1016/j.ejor.2020.11.016}
}
@Article{AudDanOrb2014,
author = Audet_C #and# Dang_CK #and# Orban_D,
title = {Optimization of Algorithms with {OPAL}},
journal = mpc,
year = 2014,
volume = 6,
number = 3,
pages = {233--254}
}
@Article{AudEgla1977,
title = {New approach to the design of multifactor experiments},
author = {Audze, P. and Egl{\~a}js, Vilnis},
journal = {Problems of Dynamics and Strengths},
year = 1977,
note = {(in Russian)},
pages = {104--107},
volume = 35,
publisher = {Zinatne Publishing House, Riga},
alias = "Audze1977"
}
@Article{AudOrb06:mads,
author = Audet_C #and# Orban_D,
title = {Finding Optimal Algorithmic Parameters Using Derivative-Free
Optimization},
journal = siamo,
year = 2006,
volume = 17,
number = 3,
pages = {642--664},
keywords = "mesh adaptive direct search; pattern search",
doi = "10.1137/0406208"
}
@Article{Aue2002using,
title = {Using Confidence Bounds for Exploitation-Exploration
Trade-offs},
author = {Auer, Peter},
journal = jmlr,
volume = 3,
month = nov,
pages = {397--422},
year = 2002,
abstract = "We show how a standard tool from statistics --- namely
confidence bounds --- can be used to elegantly deal with
situations which exhibit an exploitation-exploration
trade-off. Our technique for designing and analyzing
algorithms for such situations is general and can be applied
when an algorithm has to make exploitation-versus-exploration
decisions based on uncertain information provided by a random
process. We apply our technique to two models with such an
exploitation-exploration trade-off. For the adversarial
bandit problem with shifting our new algorithm suffers only
$O((ST)^{1/2})$ regret with high probability over $T$ trials
with $S$ shifts. Such a regret bound was previously known
only in expectation. The second model we consider is
associative reinforcement learning with linear value
functions. For this model our technique improves the regret
from $O(T^{3/4})$ to $O(T^{1/2})$."
}
@Article{AueCesFis2002finite,
title = {Finite-time analysis of the multiarmed bandit problem},
author = {Auer, Peter and Cesa-Bianchi, Nicolo and Fischer, Paul},
journal = ml,
volume = 47,
number = {2-3},
pages = {235--256},
year = 2002,
}
@Article{AugBadBroZit2012tcs,
author = Auger_A #and# Bader_J #and# Brockhoff #and# Zitzler,
title = {Hypervolume-based multiobjective optimization:
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@Article{AvcTop2017:cor,
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year = 2017,
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@Article{AvrAllLop2021arxiv,
author = Avramescu_A #and# Allmendinger #and# Lopez-Ibanez,
title = "Managing Manufacturing and Delivery of Personalised Medicine:
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year = 2021,
journal = arxiv # {2105.12699 [econ.GN]},
url = {https://arxiv.org/abs/2105.12699}
}
@Article{AydYavStu2017:si,
author = Dogan #and# Yavuz #and# Stuetzle,
title = {{ABC-X:} A Generalized, Automatically Configurable Artificial Bee
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journal = swarm,
year = 2017,
volume = 11,
number = 1,
pages = {1--38}
}
@Article{AyoAllLopPar2022scalarisation,
author = Ayodele_M #and# Allmendinger #and# Lopez-Ibanez #and# Parizy,
title = {A Study of Scalarisation Techniques for Multi-Objective
{QUBO} Solving},
journal = arxiv # {2210.11321},
year = 2022,
doi = {10.48550/arXiv.2210.11321}
}