Graph Theory (Graduate Texts in Mathematics, 173)
Graph Theory (Graduate Texts in Mathematics, 173)
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Graph Theory (Graduate Texts in Mathematics, 173)
Almosttwodecadeshavepassedsincetheappearanceofthosegrapht- ory texts that still set the agenda for most introductory courses taught today. The canon created by those books has helped to identify some main?eldsofstudyandresearch, andwilldoubtlesscontinuetoin?uence the development of the discipline for some time to come. Yet much has happened in those 20 years, in graph theory no less thanelsewhere: deepnewtheoremshavebeenfound, seeminglydisparate methods and results have become interrelated, entire new branches have arisen. To name just a few such developments, one may think of how the new notion of list colouring has bridged the gulf between inva- ants such as average degree and chromatic number, how probabilistic methods andtheregularity lemmahave pervadedextremalgraphtheory and Ramsey theory, or how the entirely new ?eld of graph minors and tree-decompositions has brought standard methods of surface topology to bear on long-standing algorithmic graph problems. Clearly, then, the time has come for a reappraisal: what are, today, the essential areas, methods and results that should form the centre of an introductory graph theory course aiming to equip its audience for the most likely developments ahead? I have tried in this book to o?er material for such a course. In view of the increasing complexity and maturity of the subject, I have broken with the tradition of attempting to cover both theory and app- cations: this book o?ers an introduction to the theory of graphs as part of (pure) mathematics it contains neither explicit algorithms nor 'real world' applications.
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Graph Theory (Graduate Texts in Mathematics, 173)
Almosttwodecadeshavepassedsincetheappearanceofthosegrapht- ory texts that still set the agenda for most introductory courses taught today. The canon created by those books has helped to identify some main?eldsofstudyandresearch, andwilldoubtlesscontinuetoin?uence the development of the discipline for some time to come. Yet much has happened in those 20 years, in graph theory no less thanelsewhere: deepnewtheoremshavebeenfound, seeminglydisparate methods and results have become interrelated, entire new branches have arisen. To name just a few such developments, one may think of how the new notion of list colouring has bridged the gulf between inva- ants such as average degree and chromatic number, how probabilistic methods andtheregularity lemmahave pervadedextremalgraphtheory and Ramsey theory, or how the entirely new ?eld of graph minors and tree-decompositions has brought standard methods of surface topology to bear on long-standing algorithmic graph problems. Clearly, then, the time has come for a reappraisal: what are, today, the essential areas, methods and results that should form the centre of an introductory graph theory course aiming to equip its audience for the most likely developments ahead? I have tried in this book to o?er material for such a course. In view of the increasing complexity and maturity of the subject, I have broken with the tradition of attempting to cover both theory and app- cations: this book o?ers an introduction to the theory of graphs as part of (pure) mathematics it contains neither explicit algorithms nor 'real world' applications.
Almosttwodecadeshavepassedsincetheappearanceofthosegrapht- ory texts that still set the agenda for most introductory courses taught today. The canon created by those books has helped to identify some main?eldsofstudyandresearch, andwilldoubtlesscontinuetoin?uence the development of the discipline for some time to come. Yet much has happened in those 20 years, in graph theory no less thanelsewhere: deepnewtheoremshavebeenfound, seeminglydisparate methods and results have become interrelated, entire new branches have arisen. To name just a few such developments, one may think of how the new notion of list colouring has bridged the gulf between inva- ants such as average degree and chromatic number, how probabilistic methods andtheregularity lemmahave pervadedextremalgraphtheory and Ramsey theory, or how the entirely new ?eld of graph minors and tree-decompositions has brought standard methods of surface topology to bear on long-standing algorithmic graph problems. Clearly, then, the time has come for a reappraisal: what are, today, the essential areas, methods and results that should form the centre of an introductory graph theory course aiming to equip its audience for the most likely developments ahead? I have tried in this book to o?er material for such a course. In view of the increasing complexity and maturity of the subject, I have broken with the tradition of attempting to cover both theory and app- cations: this book o?ers an introduction to the theory of graphs as part of (pure) mathematics it contains neither explicit algorithms nor 'real world' applications.
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