We describe Pyomo, an open source software package for modeling and solving
mathematical programs in Python. Pyomo can be used to define abstract and concrete …

We present the mapping of a class of simplified air traffic management problems (strategic
conflict resolution) to quadratic unconstrained Boolean optimization problems. The mapping …

By representing the constraints and objective function in factorized form, graphical models
can concisely define various NP-hard optimization problems. They are therefore extensively …

In recent years, portfolio approaches to solving SAT problems and CSPs have become
increasingly common. There are also a number of different encodings for representing CSPs …

In this document, we introduce PyCSP $3 $, a Python library that allows us to write models of
combinatorial constrained problems in a declarative manner. Currently, with PyCSP $3 …

In this paper we propose the technology for constructing propositional encodings of discrete
functions. It is aimed at solving inversion problems of considered functions using state-of-the …

This paper formalises a packing problem that emerges as a core sub-problem for managing
workload consolidation in data centres. As a generalisation of the Bin Packing (BP) problem …

A method for harvest planning based on the coupling of crop assignment with vehicle
routing is presented. Given a setting with multiple fields, a path network connecting these …

CP modeling languages offer convenience to the user by allowing both constants and
decision variables to be first class citizens over which mathematical and Boolean operators …

Constraints make hard optimization problems even harder to solve on quantum devices
because they are implemented with large energy penalties and additional qubit overhead …