AbstractMixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). It can represent the discrete elements of a problem with logical propositions and provides a more natural modeling framework than MILP. It can also have computational advantages, partly because it eliminates integer variables when they serve no purpose, provides alternatives to the traditional continuous relaxation, and applies logic processing algorithms. This paper surveys previous work and attempts to organize ideas associated with MLLP, some old and some new, into a coherent framework. It articulates potential advantages of MLLP's wider choice of modeling and solution options and illustrates some of them with computational experim...
In this article we illustrate that Constraint Logic Programming (CLP) systems allow easy expression ...
Linear Programming (LP) and Integer Linear Programming (ILP) are two of the most powerful tools ever...
Many optimization problems involve integer and continuous variables that can be modeled as mixed int...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
AbstractMixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming ...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
A systematic procedure for transforming a set of logical statements or logical conditions imposed on...
A Linear Programme (LP) involves a conjunction of linear constraints and has a well defined dual. It...
A systematic procedure for transforming a set of logical statements or logical conditions imposed on...
Abstract This tutorial describes a logic-based approach to formulating and solving pure and mixed in...
. This paper proposes a logic-based approach to optimization that combines solution methods from ma...
Mixed-integer programs (MIPs) involving logical implications modeled through big-M coefficients are ...
The struggle to model and solve Combinatorial Optimization Problems (COPs) has challenged the develo...
A wide range of problems can be modeled as Mixed Integer Linear Programming (MIP) problems using sta...
<p>Many optimization problems require the modelling of discrete and continuous variables, giving ris...
In this article we illustrate that Constraint Logic Programming (CLP) systems allow easy expression ...
Linear Programming (LP) and Integer Linear Programming (ILP) are two of the most powerful tools ever...
Many optimization problems involve integer and continuous variables that can be modeled as mixed int...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
AbstractMixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming ...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
A systematic procedure for transforming a set of logical statements or logical conditions imposed on...
A Linear Programme (LP) involves a conjunction of linear constraints and has a well defined dual. It...
A systematic procedure for transforming a set of logical statements or logical conditions imposed on...
Abstract This tutorial describes a logic-based approach to formulating and solving pure and mixed in...
. This paper proposes a logic-based approach to optimization that combines solution methods from ma...
Mixed-integer programs (MIPs) involving logical implications modeled through big-M coefficients are ...
The struggle to model and solve Combinatorial Optimization Problems (COPs) has challenged the develo...
A wide range of problems can be modeled as Mixed Integer Linear Programming (MIP) problems using sta...
<p>Many optimization problems require the modelling of discrete and continuous variables, giving ris...
In this article we illustrate that Constraint Logic Programming (CLP) systems allow easy expression ...
Linear Programming (LP) and Integer Linear Programming (ILP) are two of the most powerful tools ever...
Many optimization problems involve integer and continuous variables that can be modeled as mixed int...