Most practical problems lead either to solving a system of equation or to optimization. From the computational viewpoint, both classes of problems can be reduced to each other: optimization can be reduced to finding points at which all partial derivatives are zeros, and solving systems of equations can be reduced to minimizing sums of squares. It is therefore natural to expect that, on average, both classes of problems have the same computational complexity -- i.e., require about the same computation time. However, empirically, optimization problems are much faster to solve. In this paper, we provide a possible explanation for this unexpected empirical phenomenon
We study the complexity of some computational problems in case certain stability guarantees are requ...
Optimization is defined as the mathematical procedures involved in effecting optimality. It is also ...
Computational optimization is ubiquitous in many applications in engineering and industry. In this c...
Optimization Theory is an active area of research with numerous applications; many of the books are ...
This chapter aims to address some of the fundamental issues that are often encountered in optimizati...
We address the question: "Are some classes of combinatorial optimization problems intrinsically...
Computational optimization is an important paradigm with a wide range of applications. In virtually ...
This week, at the Rmetrics conference, there has been an interesting discussion about heuristic opti...
One of the main objectives of theoretical research in computational complexity and feasibility is to...
Can we measure the difficulty of an optimization problem? Although optimization plays a crucial role...
In many real-life circumstances decision problems arise. Optimisation problems can be for- mulated a...
One of the main objectives of theoretical research in computational complexity and feasibility is to...
Many important problems in computer science, such as CLIQUE, COLORING, and TRAVELLING SALESPERSON, ...
Often, several different algorithms can solve a certain practical problem. Sometimes, algorithms whi...
There exists many applications with so-called costly problems, which means that the objective functi...
We study the complexity of some computational problems in case certain stability guarantees are requ...
Optimization is defined as the mathematical procedures involved in effecting optimality. It is also ...
Computational optimization is ubiquitous in many applications in engineering and industry. In this c...
Optimization Theory is an active area of research with numerous applications; many of the books are ...
This chapter aims to address some of the fundamental issues that are often encountered in optimizati...
We address the question: "Are some classes of combinatorial optimization problems intrinsically...
Computational optimization is an important paradigm with a wide range of applications. In virtually ...
This week, at the Rmetrics conference, there has been an interesting discussion about heuristic opti...
One of the main objectives of theoretical research in computational complexity and feasibility is to...
Can we measure the difficulty of an optimization problem? Although optimization plays a crucial role...
In many real-life circumstances decision problems arise. Optimisation problems can be for- mulated a...
One of the main objectives of theoretical research in computational complexity and feasibility is to...
Many important problems in computer science, such as CLIQUE, COLORING, and TRAVELLING SALESPERSON, ...
Often, several different algorithms can solve a certain practical problem. Sometimes, algorithms whi...
There exists many applications with so-called costly problems, which means that the objective functi...
We study the complexity of some computational problems in case certain stability guarantees are requ...
Optimization is defined as the mathematical procedures involved in effecting optimality. It is also ...
Computational optimization is ubiquitous in many applications in engineering and industry. In this c...