The expressive power of binary linear programming
M Cadoli - Principles and Practice of Constraint Programming …, 2001 - Springer
M Cadoli
Principles and Practice of Constraint Programming—CP 2001: 7th International …, 2001•SpringerVery efficient solvers for Integer Programming exist, when the constraints and the objective
function are linear. In this paper we tackle a fundamental question: what is the expressive
power of Integer Linear Programming? We are able to prove that ILP, more precisely Binary
LP, expresses the complexity class NP. As a consequence, in principle all specifications of
combinatorial problems in NP formulated in constraint languages can be translated as BLP
models.
function are linear. In this paper we tackle a fundamental question: what is the expressive
power of Integer Linear Programming? We are able to prove that ILP, more precisely Binary
LP, expresses the complexity class NP. As a consequence, in principle all specifications of
combinatorial problems in NP formulated in constraint languages can be translated as BLP
models.
Abstract
Very efficient solvers for Integer Programming exist, when the constraints and the objective function are linear. In this paper we tackle a fundamental question: what is the expressive power of Integer Linear Programming? We are able to prove that ILP, more precisely Binary LP, expresses the complexity class NP. As a consequence, in principle all specifications of combinatorial problems in NP formulated in constraint languages can be translated as BLP models.
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