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1. |
Record Nr. |
UNISALENTO991003639449707536 |
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Autore |
Caramia, Federica |
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Titolo |
Il metodo local branching per la programmazione mista intera. Tesi di laurea / laureanda Federica Caramia ; relat. Paolo Nobili |
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Pubbl/distr/stampa |
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Lecce : Università del Salento. Corso di laurea in Matematica, a.a. 2017-18 |
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Descrizione fisica |
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Classificazione |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Mathematical programming |
Polyhedral combinatorics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910797852703321 |
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Autore |
Crew Robert E., Jr. |
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Titolo |
The 2012 elections in Florida : Obama wins and democrats make strides in downticket races / / Robert E. Crew, Jr. and Mary Ruggiero Anderson |
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Pubbl/distr/stampa |
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Lanham : , : University Press of America, Incorporated, , [2016] |
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©2016 |
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ISBN |
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Descrizione fisica |
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1 online resource (134 p.) |
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Collana |
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Patterns and trends in Florida elections |
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Soggetti |
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Elections - Florida |
Political campaigns - Forida |
Presidents - United States - Election - 2012 |
Florida Politics and government 21st century |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Contents; List of Figures; List of Tables; I: The 2012 Presidential Election in Florida; 1 An Overview; The Florida Presidential Contest in 2012; 2 The Nomination Process; Republican Presidential Primary; The Lead-In to the Florida Primary; The Florida Presidential Primary: Romney vs. Gingrich; The Florida Presidential Primary: Rick Santorum and Ron Paul; The Outcome of the Republican Presidential Primary; Summary; 3 The Presidential General Election Process; The Strategic Context; Positioning, Targeting, and Message; How the Democrats Campaigned; How the Republicans Campaigned; Summary |
4 The Presidential Election ResultsEarly Voting; Voter Registration and Turnout; 5 Voting Behavior in the Presidential Election; Sex; Race and Ethnicity; Age; Summary of Key Demographic Groups; Summary; 6 Issues and Candidate Perceptions; Days Leading Up to the Election: Likely Voters in Florida; The Day of Election: CNN Exit Polling, Data, Florida Voters, and the Nation; Summary; II: The Race for the U.S. Senate; 7 The Campaign for the U.S. Senate; Background and Context; The Primary Campaign; The US Senate General Election; The Outcome of the Senate Race |
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8 Explaining the Voter in the Senate ElectionGeneral Election Results; Summary of Key Demographic Groups; Summary; III: The Race for Congress; 9 The Campaign for Congress; Introduction; The Pattern of Outcomes in the 2012 Congressional Elections; IV: The State Legislative Campaigns; 10 The State Legislative Races; Introduction; The Parameters of the 2012 Legislative Session; Overall Results; Patterns in the Outcomes of the Florida Legislative Races; V: What's Next in Politics in Florida?; 11 Patterns, Trends, and the Future of Florida Politics; Introduction |
Trends in the Florida Electoral SystemTrends in Voter Registration and Voter Turnout; Politically Relevant Population Trends; Trends in Campaign Finance; The Source of Campaign Funding; Work Cited; Index |
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Sommario/riassunto |
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This book places the 2012 election in Florida in historical context and provides an explanation for the outcome of the races involved. It offers descriptions of the races for President, US Senate, US Congress and the Florida State Legislature as well as explanations for the outcomes of these races. |
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3. |
Record Nr. |
UNINA9910557283803321 |
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Autore |
Caraffini Fabio |
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Titolo |
Evolutionary Computation & Swarm Intelligence |
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Pubbl/distr/stampa |
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
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Descrizione fisica |
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1 online resource (286 p.) |
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Soggetti |
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Information technology industries |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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The vast majority of real-world problems can be expressed as an optimisation task by formulating an objective function, also known as cost or fitness function. The most logical methods to optimise such a function when (1) an analytical expression is not available, (2) |
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mathematical hypotheses do not hold, and (3) the dimensionality of the problem or stringent real-time requirements make it infeasible to find an exact solution mathematically are from the field of Evolutionary Computation (EC) and Swarm Intelligence (SI). The latter are broad and still growing subjects in Computer Science in the study of metaheuristic approaches, i.e., those approaches which do not make any assumptions about the problem function, inspired from natural phenomena such as, in the first place, the evolution process and the collaborative behaviours of groups of animals and communities, respectively. This book contains recent advances in the EC and SI fields, covering most themes currently receiving a great deal of attention such as benchmarking and tunning of optimisation algorithms, their algorithm design process, and their application to solve challenging real-world problems to face large-scale domains. |
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