AbstractWe describe an effective method for doing binary-encoded modeling, in the context of 0/1 linear programming, when the number of feasible configurations is not a power of two. Our motivation comes from modeling all-different restrictions
We show how to efficiently model binary constraint problems (BCP) as integer programs. After conside...
\u3cp\u3eThis paper considers integer formulations of binary sets X of minimum sparsity, i.e., the m...
New algorithms for the soft-derision and the hard-derision maximum likelihood decoding (MLD) for bin...
AbstractWe describe an effective method for doing binary-encoded modeling, in the context of 0/1 lin...
In this thesis, we aim at finding appropriate integer programming models and associated solution app...
w9259490 For mathematical programming (MP) to have greater impact upon the decision making proc...
Creating good integer programming formulations had, as a basic axiom, the rule “Find formulations wi...
It is shown that the optimum of an integer program in fixed dimension, which is defined by a fixed n...
The splitting of variables in an integer programming model into the sum of other variables can allow...
Abstract. Creating good integer programming formulations had, as a basic axiom, the rule “Find formu...
AbstractIt is proved that there exist encoding schemes which are arbitrarily as efficient as the bin...
It is shown that the optimum of an integer program in fixed dimension, which is defined by a fixed...
In this work we show how Binary Decision Diagrams can be used as a powerful tool for 0/1~Integer Pr...
Integer programming (discrete optimization) is best used for solving problems involving discrete, wh...
This paper provides a new, generalized approach to the problem of encoding information as vectors of...
We show how to efficiently model binary constraint problems (BCP) as integer programs. After conside...
\u3cp\u3eThis paper considers integer formulations of binary sets X of minimum sparsity, i.e., the m...
New algorithms for the soft-derision and the hard-derision maximum likelihood decoding (MLD) for bin...
AbstractWe describe an effective method for doing binary-encoded modeling, in the context of 0/1 lin...
In this thesis, we aim at finding appropriate integer programming models and associated solution app...
w9259490 For mathematical programming (MP) to have greater impact upon the decision making proc...
Creating good integer programming formulations had, as a basic axiom, the rule “Find formulations wi...
It is shown that the optimum of an integer program in fixed dimension, which is defined by a fixed n...
The splitting of variables in an integer programming model into the sum of other variables can allow...
Abstract. Creating good integer programming formulations had, as a basic axiom, the rule “Find formu...
AbstractIt is proved that there exist encoding schemes which are arbitrarily as efficient as the bin...
It is shown that the optimum of an integer program in fixed dimension, which is defined by a fixed...
In this work we show how Binary Decision Diagrams can be used as a powerful tool for 0/1~Integer Pr...
Integer programming (discrete optimization) is best used for solving problems involving discrete, wh...
This paper provides a new, generalized approach to the problem of encoding information as vectors of...
We show how to efficiently model binary constraint problems (BCP) as integer programs. After conside...
\u3cp\u3eThis paper considers integer formulations of binary sets X of minimum sparsity, i.e., the m...
New algorithms for the soft-derision and the hard-derision maximum likelihood decoding (MLD) for bin...
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