Matheuristics: using mathematics for heuristic design

Matheuristics are heuristic algorithms based on mathematical tools such as the ones provided by mathematical programming, that are structurally general enough to be applied to different problems with little adaptations to their abstract structure. The result can be metaheuristic hybrids having components derived from the mathematical model of the problems of interest, but the mathematical techniques themselves can define general heuristic solution frameworks. In this paper, we focus our attention on mathematical programming and its contributions to developing effective heuristics. We briefly describe the mathematical tools available and then some matheuristic approaches, reporting some representative examples from the literature. We also take the opportunity to provide some ideas for possible future development

Predictive Analytics for Real-time Auction Bidding Support: a Case on Fantasy Football

This work reports about an end-to-end business analytics experiment, applying predictive and prescriptive analytics to real-time bidding support for fantasy football draft auctions. Forecast methods are used to quantify the expected return of each investment alternative, while subgradient optimization is used to provide adaptive online recommendations on the allocation of scarce budget resources. A distributed front-end implementation of the prescriptive modules and the rankings of simulated leagues testify the viability of this architecture for actual support

Acyclic orientations with path constraints

Many well-known combinatorial optimization problems can be stated over the set of acyclic orientations of an undirected graph. For example, acyclic orientations with certain diameter constraints are closely related to the optimal solutions of the vertex coloring and frequency assignment problems. In this paper we introduce a linear programming formulation of acyclic orientations with path constraints, and discuss its use in the solution of the vertex coloring problem and some versions of the frequency assignment problem. A study of the polytope associated with the formulation is presented, including proofs of which constraints of the formulation are facet-defining and the introduction of new classes of valid inequalities

Realizzazione e validazione sperimentale di un dataset open per l'Internet of Things

L'incremento e il continuo sviluppo dei dispositivi inerenti all'Internet of Things (IoT) ha causato un aumento esponenziale dei dati prodotti da ognuno di noi. Oltre all'incremento dei dati generati, è stata resa più semplice la condivisione libera di essi attraverso la rete internet. Una parte dei dati IoT generati dai dispositivi eterogenei possono essere liberamente accessibili e vengono chiamati Open Data, i quali possono essere reperibili in repository pubbliche fornite da enti, organizzazioni e studi/esperimenti, o realizzate da utenti grazie al crowdsourcing. Gli Open Data sono in costante aumento, ma presentano dei problemi come la scarsità di informazioni fornite, come metadati assenti o incompleti, che, a volte, li rendono poco comprensibili. Questo comporta un problema dal punto di vista dell'utilizzo dei dati vista la possibile scarsa riconoscibilità e comprensibilità. Per risolvere questo problema bisogna effettuare operazioni di annotazione e classificazione automatica. Le operazioni necessitano di essere automatiche visto che gli Open Data sono caratterizzati da grandi quantità di dati, quindi farle manualmente è impossibile. \par Nello studio sperimentale si è realizzato un dataset contente dati provenienti dalla piattaforma online Thingspeak, che è un repository pubblico che sfrutta il crowdsourcing. Il dataset realizzato è sottoposto ad un'attività di validazione e di sperimentazione. La validazione sperimentale serve per verificare se il dataset realizzato in questo studio si comporta in maniera simile a dataset ottenuti da repository pubbliche fornite da enti e studi/esperimenti esterni. La sperimentazione serve a verificare quale algoritmo di classificazione è più efficiente per i dataset realizzato e quelli considerati, e a confermare che la classificazione basata sulla successione dei dati non funzioni per il tipo di dataset considerato

Matheuristics:survey and synthesis

In integer programming and combinatorial optimisation, people use the term matheuristics to refer to methods that are heuristic in nature, but draw on concepts from the literature on exact methods. We survey the literature on this topic, with a particular emphasis on matheuristics that yield both primal and dual bounds (i.e., upper and lower bounds in the case of a minimisation problem). We also make some comments about possible future developments

An (MI)LP-based Primal Heuristic for 3-Architecture Connected Facility Location in Urban Access Network Design

We investigate the 3-architecture Connected Facility Location Problem arising in the design of urban telecommunication access networks. We propose an original optimization model for the problem that includes additional variables and constraints to take into account wireless signal coverage. Since the problem can prove challenging even for modern state-of-the art optimization solvers, we propose to solve it by an original primal heuristic which combines a probabilistic fixing procedure, guided by peculiar Linear Programming relaxations, with an exact MIP heuristic, based on a very large neighborhood search. Computational experiments on a set of realistic instances show that our heuristic can find solutions associated with much lower optimality gaps than a state-of-the-art solver.Comment: This is the authors' final version of the paper published in: Squillero G., Burelli P. (eds), EvoApplications 2016: Applications of Evolutionary Computation, LNCS 9597, pp. 283-298, 2016. DOI: 10.1007/978-3-319-31204-0_19. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-31204-0_1

Intelligent Method for Diagnosing Structural Faults of Rotating Machinery Using Ant Colony Optimization

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called “relative ratio symptom parameters” are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks

A fast ILP-based Heuristic for the robust design of Body Wireless Sensor Networks

We consider the problem of optimally designing a body wireless sensor network, while taking into account the uncertainty of data generation of biosensors. Since the related min-max robustness Integer Linear Programming (ILP) problem can be difficult to solve even for state-of-the-art commercial optimization solvers, we propose an original heuristic for its solution. The heuristic combines deterministic and probabilistic variable fixing strategies, guided by the information coming from strengthened linear relaxations of the ILP robust model, and includes a very large neighborhood search for reparation and improvement of generated solutions, formulated as an ILP problem solved exactly. Computational tests on realistic instances show that our heuristic finds solutions of much higher quality than a state-of-the-art solver and than an effective benchmark heuristic.Comment: This is the authors' final version of the paper published in G. Squillero and K. Sim (Eds.): EvoApplications 2017, Part I, LNCS 10199, pp. 1-17, 2017. DOI: 10.1007/978-3-319-55849-3\_16. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-55849-3_1

Selection of an optimal neural network architecture for computerâ aided detection of microcalcificationsâ Comparison of automated optimization techniques

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134870/1/mp5036.pd

A INCIDÊNCIA DE INCONTINÊNCIA URINÁRIA NOS TRATAMENTOS DE BRAQUITERAPIA E PROSTATECTOMIA RADICAL NO CÂNCER DE PRÓSTATA: ABORDAGEM DE ABRANGÊNCIA EM PROL DA PRÁTICA CLÍNICA

A escolha para o tratamento de câncer de próstata não é exclusiva. Os procedimentos são diversos e o ponto de convergência para todos é o mesmo resultado oncológico. No entanto, o que difere nesses tratamentos são os prejuízos que acometem a qualidade de vida após a terapia de escolha. Desenvolveu-se um estudo de revisão visando focar em uma sequela presente em dois tratamentos e que impacta o bem-estar do homem, a incontinência urinária. Foi feita uma comparação embasada em artigos científicos para ver a incidência da incontinência urinária após os procedimentos de prostatectomia radical e braquiterapia. O trabalho em questão foi realizado mediante a seleção e análise de alguns artigos e estudos coerentes com o tema escolhido, os quais foram encontrados nas bases de dados PubMed e Medline. A partir disso, observou-se que pacientes que se submeteram a prostatectomia radical apresentaram maiores índices de incontinência urinaria, com relação a aqueles que se trataram por braquiterapia. Os tratamentos para o câncer de próstata podem apresentar outras sequelas, como intestinais e sexuais. No momento da escolha da intervenção o paciente deve estar ciente dos impactos na sua qualidade de vida.