The Complexity of the Optimal Spanning Hypertree Problem

The Complexity Of The Optimal Spanning Hypertree Problem

Learning Graphical Models by Extending Optimal Spanning Trees

In learning graphical models we often face the problem that a good fit to the data may call for a complex model, while real time requirements for later inferences force us to strive for a simpler one. In this paper we suggest a learning algorithm that tries to achieve a compromise between the goodness of fit of the learned graphical model and the complexity of inferences in it. It is based on t...

Backtracking Procedures for Hypertree, HyperSpread and Connected Hypertree Decomposition of CSPs

Hypertree decomposition has been shown to be the most general CSP decomposition method. However, so far the exact methods are not able to find optimal hypertree decompositions of realistic instances. We present a backtracking procedure which, along with isomorphic component detection, results in optimal hypertree decompositions. We also make the procedure generic; variations of which results in...

Reducing Redundancy in the Hypertree Decomposition Scheme

Hypertree decomposition is a powerful technique for transforming near-acyclic CSPs into acyclic CSPs. Acyclic CSPs have efficient, polynomial time solving techniques, and so these conversions are of interest to the constraints community. We present here an improvement on the opt-k-decomp algorithm for finding an optimal hypertree decomposition. Abstract Hypertree decomposition is a powerful tec...

SOLVING A STEP FIXED CHARGE TRANSPORTATION PROBLEM BY A SPANNING TREE-BASED MEMETIC ALGORITHM

In this paper, we consider the step fixed-charge transportation problem (FCTP) in which a step fixed cost, sometimes called a setup cost, is incurred if another related variable assumes a nonzero value. In order to solve the problem, two metaheuristic, a spanning tree-based genetic algorithm (GA) and a spanning tree-based memetic algorithm (MA), are developed for this NP-hard problem. For compa...