Algorithms on Discrete Near Optimal Partitions

In practice, many NP-hard combinatorial optimization
problems can be formulated as partitioning problems.
In such a formulation, each component in the
partition is assigned with a numerical objective
value and the objective function is defined as a
function on the numerical values assigned. The
optimization problem is to minimize or maximize
the objective function on all possible partitions
that satisfy certain constraints. A feasible
partition (i.e., a partition that satisfy all the
constraints) with the optimal objective value is
called an optimal partition. A near-optimal partition
is a partition with an objective value close to the
optimal value. In a partitioning problem, by
exploiting the properties of the underlying
domain, one may be able to construct efficient
heuristic algorithms to produce near-optimal
partitions. We present algorithms for applications in
Higher Dimensional Domain Decomposition, Intensity
Modulated Radiation Therapy (IMRT) including
Intensity Modulated Arc Therapy (IMAT)

Autorentext
Athula D. Gunawardena:BS(EE, U. of Peradeniya, Sri Lanka), Ph.D.(Mathematics, U. of Wyoming), Ph.D.(Computer Sciences, U. of Wisconsin-Madison), Associate Professor at U. of Wisconsin-Whitewater. Robert R. Meyer: Ph.D.(U. of Wisconsin-Madison), Professor Emeritus of Computer Sciences, U. of Wisconsin-Madison.

Klappentext
In practice, many NP-hard combinatorial optimization problems can be formulated as partitioning problems. In such a formulation, each component in the partition is assigned with a numerical objective value and the objective function is defined as a function on the numerical values assigned. The optimization problem is to minimize or maximize the objective function on all possible partitions that satisfy certain constraints. A feasible partition (i.e., a partition that satisfy all the constraints) with the optimal objective value is called an optimal partition. A near-optimal partition is a partition with an objective value close to the optimal value. In a partitioning problem, by exploiting the properties of the underlying domain, one may be able to construct efficient heuristic algorithms to produce near-optimal partitions. We present algorithms for applications in Higher Dimensional Domain Decomposition, Intensity Modulated Radiation Therapy (IMRT) including Intensity Modulated Arc Therapy (IMAT)