Large scale mixed-integer linear programming MILP models may easily prove extraordinarily difficult to solve, even with efficient commercially-implemented MILP solution codes. Drawing on experience gained in solving and analyzing three intertemporal investment planning MILP models for electric power supply, this note offers several practical suggestions for reducing computer solution times for general productionallocation MILP models. Solution time reduction stems from judicious use of the powerful computational capabilities of existing commercial LP codes in conjunction with information known or to be learned by the Practitioner about the model's structure
[[abstract]]Algorithms developed to solve linear programming (LP) problems and advances in computer ...
The integration of choice models in mixed integer linear programming (MILP) is appealing to operator...
In selecting the best mixed integer linear programming (MILP) formulation the important issue is to ...
In complex decision problems, some objectives are not well quantified or are not introduced explicit...
Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific discipl...
Many real-life problems can be tackled as Structured Mixed Integer Linear Programs(MILP). The workfl...
Proposed portfolio models are computationally attractive as they give rise to linear and mixed integ...
The complexity of Mixed-Integer Linear Programs (MILPs) increases with the number of nodes in energy...
We describe and survey the main component and the usage of Mixed-Integer Linear Programming Solvers
The central thesis of this dissertation is that the Mixed-Integer Linear Programming (MILP) technolo...
Modern Mixed-Integer Programming (MIP) solvers exploit a rich arsenal of tools to attack hard proble...
In selecting the best mixed integer linear programming (MILP) formulation the important issue is to ...
The struggle to model and solve Combinatorial Optimization Problems (COPs) has challenged the develo...
In this contribution we apply different approaches to solve four rather different MINLP problems: sp...
AbstractWe provide formulation techniques for obtaining sharp (i.e., convex hull) mixed integer prog...
[[abstract]]Algorithms developed to solve linear programming (LP) problems and advances in computer ...
The integration of choice models in mixed integer linear programming (MILP) is appealing to operator...
In selecting the best mixed integer linear programming (MILP) formulation the important issue is to ...
In complex decision problems, some objectives are not well quantified or are not introduced explicit...
Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific discipl...
Many real-life problems can be tackled as Structured Mixed Integer Linear Programs(MILP). The workfl...
Proposed portfolio models are computationally attractive as they give rise to linear and mixed integ...
The complexity of Mixed-Integer Linear Programs (MILPs) increases with the number of nodes in energy...
We describe and survey the main component and the usage of Mixed-Integer Linear Programming Solvers
The central thesis of this dissertation is that the Mixed-Integer Linear Programming (MILP) technolo...
Modern Mixed-Integer Programming (MIP) solvers exploit a rich arsenal of tools to attack hard proble...
In selecting the best mixed integer linear programming (MILP) formulation the important issue is to ...
The struggle to model and solve Combinatorial Optimization Problems (COPs) has challenged the develo...
In this contribution we apply different approaches to solve four rather different MINLP problems: sp...
AbstractWe provide formulation techniques for obtaining sharp (i.e., convex hull) mixed integer prog...
[[abstract]]Algorithms developed to solve linear programming (LP) problems and advances in computer ...
The integration of choice models in mixed integer linear programming (MILP) is appealing to operator...
In selecting the best mixed integer linear programming (MILP) formulation the important issue is to ...