Titlebook: Knapsack Problems; Hans Kellerer,Ulrich Pferschy,David Pisinger Book 2004 Springer-Verlag Berlin Heidelberg 2004 algorithms.combinatorial

OUTRE

CRAMP

Exact Solution of the Knapsack Problem,of the items such that their overall profit is maximized, while the overall weight does not exceed a given capacity c. Introducing binary variables .. to indicate whether item . is included in the knapsack or not the model may be defined:

Influx

Approximation Algorithms for the Knapsack Problem,otivation in these sections was to illustrate the basic concept of constructing simple approximation schemes. The focus was put on algorithms where both the correctness and the required complexities were easy to understand without having to go deeply into the details of complicated technical constru

執(zhí)

拔出

Servile

Multidimensional Knapsack Problems,straint (1.2) thus attaining the .. After the introduction we will deal extensively with relaxations and reductions in Section 9.2. Exact algorithms to compute optimal solutions will be covered in Section 9.3 followed by results on approximation in Section 9.4. A detailed treatment of heuristic meth

FEAS

The Multiple-Choice Knapsack Problem, replaced by the selection of exactly one item out of each class of items. In Section 7.1 we already noticed that a (BKP) can be formulated as a (MCKP), and indeed the (MCKP) model is one of the most flexible knapsack models. (MCKP) is also denoted as . or for short ..

Definitive

The Quadratic Knapsack Problem,real life applications as well as in problems with roots in graph theory it is natural to assume that the profit of a packing also should reflect how well the given items fit together. One possible formulation of such an interdependence is the . (QKP) in which an item has a corresponding profit and

擋泥板

Other Knapsack Problems,ds of variations of the knapsack problem in the scientific literature, often a specific problem is treated in only one or two papers. Thus, we could not include every knapsack variant but we tried to make a representative selection of interesting problems. Two problems will be presented in the first

高爾夫

Stochastic Aspects of Knapsack Problems,e of approximation methods is worst-case analysis. As indicated in Section 1.5 also sound results on the average behaviour of algorithms would be highly appreciated. However, any venture in this direction is bound to run into two major obstacles.