Submodular Functions and Valued Constraint Satisfaction Problems over Infinite Domains

04/05/2018
by   Manuel Bodirsky, et al.
0

Valued constraint satisfaction problems (VCSPs) are a large class of combinatorial optimisation problems. It is desirable to classify the computational complexity of VCSPs depending on a fixed set of allowed cost functions in the input. Recently, the computational complexity of all VCSPs for finite sets of cost functions over finite domains has been classified in this sense. Many natural optimisation problems, however, cannot be formulated as VCSPs over a finite domain. We initiate the systematic investigation of infinite-domain VCSPs by studying the complexity of VCSPs for piecewise linear homogeneous cost functions. We show that such VCSPs can be solved in polynomial time when the cost functions are additionally submodular, and that this is indeed a maximally tractable class: adding any cost function that is not submodular leads to an NP-hard VCSP.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/18/2019

Piecewise Linear Valued CSPs Solvable by Linear Programming Relaxation

Valued constraint satisfaction problems (VCSPs) are a large class of com...
research
03/02/2020

Piecewise Linear Valued Constraint Satisfaction Problems with Fixed Number of Variables

Many combinatorial optimisation problems can be modelled as valued const...
research
08/09/2022

An Application of Farkas' Lemma to Finite-Valued Constraint Satisfaction Problems over Infinite Domains

We show a universal algebraic local characterisation of the expressive p...
research
07/05/2021

Quantaloidal approach to constraint satisfaction

The constraint satisfaction problem (CSP) is a computational problem tha...
research
03/06/2018

Testing the complexity of a valued CSP language

A Valued Constraint Satisfaction Problem (VCSP) provides a common framew...
research
01/04/2012

Complexity Classification in Infinite-Domain Constraint Satisfaction

A constraint satisfaction problem (CSP) is a computational problem where...
research
02/23/2020

Automatic Cost Function Learning with Interpretable Compositional Networks

Cost Function Networks (CFN) are a formalism in Constraint Programming t...

Please sign up or login with your details

Forgot password? Click here to reset