Dynamic Programming Multi-Objective Combinatorial Optimization (Studies in Systems, Decision and Control, 331) von Mankowski, Michal; Moshkov, Mikhail: New (2021)

Beschreibung

Bestandsnummer des Verk�ufers I-9783030639198

Bibliografische Details

Titel: Dynamic Programming Multi-Objective Combinatorial Optimization (Studies in Systems, Decision and Control, 331)
Verlag: Springer
Erscheinungsjahr: 2021
Sprache: Englisch
ISBN-10: 3030639193
ISBN-13: 9783030639198
Einband: Hardcover
Zustand: New

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Inhaltsangabe

This book introduces a fairly universal approach to the design and analysis of exact optimization algorithms for multi-objective combinatorial optimization problems. It proposes the circuits without repetitions representing the sets of feasible solutions along with the increasing and strictly increasing cost functions as a model for such problems. The book designs the algorithms for multi-stage and bi-criteria optimization and for counting the solutions in the framework of this model.

As applications, this book studies eleven known combinatorial optimization problems: matrix chain multiplication, global sequence alignment, optimal paths in directed graphs, binary search trees, convex polygon triangulation, line breaking (text justification), one-dimensional clustering, optimal bitonic tour, segmented least squares, optimization of matchings in trees, and 0/1 knapsack problem.

The results presented are useful for researchers in combinatorial optimization. This book is also useful as the basis for graduate courses.

Von der hinteren Coverseite

This book introduces a fairly universal approach to the design and analysis of exact optimization algorithms for multi-objective combinatorial optimization problems. It proposes the circuits without repetitions representing the sets of feasible solutions along with the increasing and strictly increasing cost functions as a model for such problems. The book designs the algorithms for multi-stage and bi-criteria optimization and for counting the solutions in the framework of this model.

As applications, this book studies eleven known combinatorial optimization problems: matrix chain multiplication, global sequence alignment, optimal paths in directed graphs, binary search trees, convex polygon triangulation, line breaking (text justification), one-dimensional clustering, optimal bitonic tour, segmented least squares, optimization of matchings in trees, and 0/1 knapsack problem.

The results presented are useful for researchers in combinatorial optimization. This book is also useful as the basis for graduate courses.

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