The paper describes an optimization procedure for a class of discrete optimization problems which is defined by certain properties of the boundary of the feasible region and level sets of the objective function. It is shown that these properties are possessed, for example, by various scheduling problems, including a number of well-known NP-hard problems which play an important role in scheduling theory. For an important particular case the presented optimization procedure is compared with a version of the branch-and-bound algorithm by means of computational experiments. © 2010 Springer-Verlag
Discrete mathematics brings interesting problems to teach and learn proof with accessible objects su...
We describe a common extension of the fundamental theorem of Linear Programming on the existence of ...
Discrete optimization problems are very difficult to solve, even if the dimention is small. For most...
The paper describes an optimization procedure for a class of discrete optimization problems which is...
This book treats the fundamental issues and algorithmic strategies emerging as the core of the disci...
Typically, the search for solutions in discrete optimization problems is associated with fundamental...
Discrete optimization problems (DOPs) arise in various applications such as planning, scheduling, co...
Recent developments in the theory of computational complexity as applied to combinatorial problems h...
Recent developments in the theory of computational complexity as applied to combinatorial problems h...
International audienceIn this paper we introduce the concept of bound sets for multiobjective discre...
Separable problems of discrete optimization are considered in the paper aiming at the creation of th...
We propose a general branch-and-bound algorithm for discrete optimization in which binary decision d...
Enumerative approaches, such as branch-and-bound, to solving optimization problems require a subrout...
Solving large combinatorial optimization problems is a ubiquitous task across multiple disciplines. ...
To unify and generalize the branch-and-bound method used in operations research and the heuristic se...
Discrete mathematics brings interesting problems to teach and learn proof with accessible objects su...
We describe a common extension of the fundamental theorem of Linear Programming on the existence of ...
Discrete optimization problems are very difficult to solve, even if the dimention is small. For most...
The paper describes an optimization procedure for a class of discrete optimization problems which is...
This book treats the fundamental issues and algorithmic strategies emerging as the core of the disci...
Typically, the search for solutions in discrete optimization problems is associated with fundamental...
Discrete optimization problems (DOPs) arise in various applications such as planning, scheduling, co...
Recent developments in the theory of computational complexity as applied to combinatorial problems h...
Recent developments in the theory of computational complexity as applied to combinatorial problems h...
International audienceIn this paper we introduce the concept of bound sets for multiobjective discre...
Separable problems of discrete optimization are considered in the paper aiming at the creation of th...
We propose a general branch-and-bound algorithm for discrete optimization in which binary decision d...
Enumerative approaches, such as branch-and-bound, to solving optimization problems require a subrout...
Solving large combinatorial optimization problems is a ubiquitous task across multiple disciplines. ...
To unify and generalize the branch-and-bound method used in operations research and the heuristic se...
Discrete mathematics brings interesting problems to teach and learn proof with accessible objects su...
We describe a common extension of the fundamental theorem of Linear Programming on the existence of ...
Discrete optimization problems are very difficult to solve, even if the dimention is small. For most...