# Daniel Aloise

Back## Publications

### Cahiers du GERAD

Providing the right data to a machine learning model is an important step to insure the performance of the model. Non-compliant training data instances may l...

BibTeX reference**Daniel Aloise**, Frédéric Quesnel, François Soumis, and Yassine Yaakoubi

Crew pairing problems (CPP) are regularly solved by airlines to produce crew schedules. The goal of CPPs is to find a set of pairings (sequence of flights a...

BibTeX reference**Daniel Aloise**, and Lucídio dos Anjos Formiga Cabral

In the Weighted Fair Sequences Problem (WFSP), one aims to schedule a set of tasks or activities so that the maximum product between the largest temporal dis...

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Distance metric learning algorithms aim to appropriately measure similarities and distances between data points. In the context of clustering, metric learnin...

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Drones have been getting more and more popular in many economy sectors. Both scientific and industrial communities aim at making the impact of drones even mo...

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We consider the problem of designing vehicle routes in a distribution system that are at the same time cost-effective and visually attractive. In this pape...

BibTeX referenceThe Covering-Assignment Problem for swarm-powered ad-hoc clouds: A distributed 3D mapping use-case

The popularity of drones is rapidly increasing across the different sectors of the economy. Aerial capabilities and relatively low costs make drones the perf...

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Clustering algorithms help identify homogeneous subgroups from data. In some cases, additional information about the relationship among some subsets of the d...

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This paper studies the Dynamic Facility Location Problem with Modular Capacities (DFLPM). We propose a linear relaxation based heuristic (LRH) and an evoluti...

BibTeX referenceConvex fuzzy \(k\)-medoids clustering

**Daniel Aloise**, and Simon Blanchard

`\(K\)`

-medoids clustering is among the most popular methods for cluster analysis, but it carries several assumptions about the nature of the latent clusters...

Clustering is an automated and powerful technique for data analysis. It aims to divide a given set of data points into clusters which are homogeneous and/o...

BibTeX referenceThe carousel scheduling problem

**Daniel Aloise**, and Lucídio dos Anjos Formiga Cabral

Scheduling problems on which constraints are imposed with regard to the temporal distances between successive executions of the same task have numerous appli...

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In this article we consider a bi-objective vehicle routing problem in which, in addition to the classical minimization of the total routing cost, the operato...

BibTeX reference**Daniel Aloise**, and Nenad Mladenović

Clustering addresses the problem of finding homogeneous and well-separated subsets, called clusters, from a set of given data points. In addition to the poi...

BibTeX reference**Daniel Aloise**, Nielsen Castelo Damasceno, Nenad Mladenović, and Daniel Nobre Pinheiro

The `\(k\)`

-means is a benchmark algorithm used in cluster analysis. It belongs to the large category of
heuristics based on location-allocation steps that ...

**Daniel Aloise**, and Nenad Mladenović

The balanced clustering problem consists of partitioning a set of `\(n\)`

objects into `\(K\)`

equal-sized clusters as long as
`\(n\)`

is a multiple of `(K...

**Daniel Aloise**, and Nenad Mladenović

In this paper we propose a new variant of the Variable Neighborhood Decomposition Search (VNDS) heuristic for solving global optimization problems and apply ...

BibTeX reference**Daniel Aloise**and Claudio Contardo

We introduce an iterative algorithm for the solution of the diameter minimization clustering problem (DMCP). Our algorithm is based upon two observations: 1)...

BibTeX reference**Daniel Aloise**, and Simon Blanchard

Clustering is a data mining method which consists in partitioning a given set of *n* objects into *p* clusters in order to minimize the dissimilarity among o...

Finding communities, or clusters, in networks, or graphs, has been the subject of intense studies in the last ten years. The most used criterion for that pu...

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The objective in the continuous facility location problem with limited distances is to minimize the sum of distance functions from the facility to the cust...

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Normalized cut is one of the most popular graph clustering criteria. The main approaches proposed for its resolution are spectral clustering methods (e.g. [1...

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Finding modules, or clusters, in networks currently attracts much attention in several domains. The most studied criterion for doing so, due to Newman and Gi...

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Given a set of entities associated with points in Euclidean space, minimum sum-of-squares clustering (MSSC) consist in partitioning this set into clusters su...

BibTeX reference**Daniel Aloise**and Celso C. Ribeiro

This paper focuses on the use of different memory strategies to improve multistart methods. A network design problem in which the costs are given by discrete...

BibTeX reference**Daniel Aloise**and Pierre Hansen

Minimum sum-of-squares clustering (MSSC) consists in partitioning a given set of <i>n</i> points into <i>k</i> clusters in order to minimize the sum of squar...

BibTeX reference**Daniel Aloise**and Pierre Hansen

Methods, models, heuristic and exact algorithms for clustering are reviewed from a mathematical programming view point.

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A recent proof of NP-hardness of Euclidean sum-of-squares clustering, due to Drineas et al., <i>Machine Learning</i> 56, 9--33, 2004, is not valid. An altern...

BibTeX reference**Daniel Aloise**and Pierre Hansen

Minimum sum-of-squares clustering consists in partitioning a given set of <i>n</i> points into <i>c</i> clusters in order to minimize the sum of squared dist...

BibTeX reference**Daniel Aloise**and Pierre Hansen

To the best of our knowledge, the complexity of minimum sum-of-squares clustering is unknown. Yet, it has often been stated that this problem is NP-hard. We...

BibTeX reference**Daniel Aloise**, Thiago F. Noronha, Caroline Rocha, and Sebastián Urrutia

We address a multi-objective version of the car sequencing problem, which consists in sequencing a given set of cars to be produced in a single day, minimizi...

BibTeX reference### Articles

**Daniel Aloise**, Luca G. Gianoli, and Andrea Lodi

**Daniel Aloise**, Seyed Vahid Azhari, and Michel R. Dagenais

**Daniel Aloise**, and Lucídio dos Anjos Formiga Cabral

**Daniel Aloise**, and Freddie Kalaitzis

**Daniel Aloise**, Roman Vasiliev, Dmitrij Koznov, Eraldo R. Fernandes, George Chernishev, Dmitry Luciv, and Nikita Povarov

**Daniel Aloise**, Dario J. Aloise, and Claudio Contardo

**Daniel Aloise**, Simon Blanchard, and Alain Hertz

**Daniel Aloise**, François Soumis, and Romanic Pieugueu

**Daniel Aloise**, Gilles Caporossi, and Sébastien Le Digabel

**Daniel Aloise**, Michel R. Dagenais, and Mahsa Shakeri

**Daniel Aloise**, Luca G. Gianoli, and Andrea Lodi

**Daniel Aloise**, Leandro C. Coelho, and Caroline Rocha

**Daniel Aloise**, and Michel R. Dagenais

**Daniel Aloise**, and Simon Blanchard

**Daniel Aloise**, and Nenad Mladenović

**Daniel Aloise**, and Samuel Xavier-de-Souza

**Daniel Aloise**, Samuel Xavier-de-Souza, and Nenad Mladenović

**Daniel Aloise**, and Lucídio dos Anjos Formiga Cabral

**Daniel Aloise**

**Daniel Aloise**and Claudio Contardo

**Daniel Aloise**, and Nenad Mladenović

**Daniel Aloise**, and Nenad Mladenović

**Daniel Aloise**, Nielsen Castelo Damasceno, Nenad Mladenović, and Daniel Nobre Pinheiro

**Daniel Aloise**, and Wayne S. DeSarbo

**Daniel Aloise**, Dario J. Aloise, and Thiago P. Jeronimo

**Daniel Aloise**, and Simon Blanchard

**Daniel Aloise**

**Daniel Aloise**and Arthur Araújo

**Daniel Aloise**, Pierre Hansen, Caroline Rocha, and Éverton Santi

**Daniel Aloise**, Glaydston Mattos Ribeiro, Enilson M. Santos, and Allyson Fernandes da Costa Silva

**Daniel Aloise**

**Daniel Aloise**, Dario J. Aloise, Pierre Hansen, and Leo Liberti

**Daniel Aloise**, Pierre Hansen, and Leo Liberti

**Daniel Aloise**

**Daniel Aloise**, and Wayne S. DeSarbo

**Daniel Aloise**and Celso C. Ribeiro

**Daniel Aloise**and Pierre Hansen

**Daniel Aloise**, Sonia Cafieri, Gilles Caporossi, Pierre Hansen, Leo Liberti, and Sylvain Perron

**Daniel Aloise**, Amit Deshpande, Pierre Hansen, and P Popat

**Daniel Aloise**and Pierre Hansen

### Book chapters

**Daniel Aloise**, Jack Brimberg, and Nenad Mladenović

**Daniel Aloise**, Gilles Caporossi, Pierre Hansen, Leo Liberti, Sylvain Perron, and Manuel Ruiz

**Daniel Aloise**, Isaac F. Fernandes, Pierre Hansen, Leo Liberti, and Dario J. Aloise

### Proceedings

**Daniel Aloise**, Marie-Ève Rancourt, and Danny Godin

**Daniel Aloise**, and Eraldo R. Fernandes

**Daniel Aloise**, Luca G. Gianoli, and Andrea Lodi

**Daniel Aloise**, Seyed Vahid Azhari, and François Tetreault

**Daniel Aloise**, and Eraldo R. Fernandes

**Daniel Aloise**, and Simon Blanchard

**Daniel Aloise**, and Gilles Pesant

**Daniel Aloise**, Eraldo R. Fernandes, and Michel R. Dagenais

**Daniel Aloise**

**Daniel Aloise**

**Daniel Aloise**

**Daniel Aloise**

**Daniel Aloise**, Nenad Mladenović, and Pierre Hansen

**Daniel Aloise**, and Sanjay Dominik Jena

**Daniel Aloise**

**Daniel Aloise**, and J.C.C. Mello

**Daniel Aloise**and Claudio Contardo

**Daniel Aloise**, and Simon Blanchard

**Daniel Aloise**

**Daniel Aloise**, Pierre Hansen, and Caroline Rocha

**Daniel Aloise**, Pierre Hansen, and Caroline Rocha

**Daniel Aloise**

**Daniel Aloise**, Gilles Caporossi, Pierre Hansen, Leo Liberti, Sylvain Perron, and Manuel Ruiz