This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for the case of small-scale and large-scale learning problems. Small-scale learning problems are subject to the usual approximation– estimation tradeoff. Large-scale learning problems are subject to a qualitatively differ...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

Based on the principles of equalized sliding coefficients and equalized teeth bending strength, the optimization mathematical model for calculating and allocating the addendum modification coefficients of involute cylindrical gear is firstly established. Then the measures to calculate the tooth parameters in real-time during the optimization steps are achieved. Finally, the optimization program...

The paper deals with an efficient solution technique to large– scale discretized shape and topology optimization problems. The efficiency relies on multigrid preconditioning. In case of shape optimization, we apply a geometric multigrid preconditioner to eliminate the underlying state equation while the outer optimization loop is the sequential quadratic programming, which is done in the multil...

This paper presents a method for optimizing oil production on large scale production networks such as the Troll west field in the North Sea. The method is based on piecewise linearization of all nonlinearities, and on decomposition of the full scale problem into smaller sub-problems. Column generation in a Branch & Price framework is used to solve the decomposed problem. The methods differs fro...

We suggest that planning for automated earthmoving operations such as digging a foundation or leveling a mound of soil, be treated at multiple levels. In a system that we have developed, a coarse-level planner is used to tessellate the volume to be excavated into smaller pieces that are sequenced in order to complete the task efficiently. Each of the smaller volumes is treated with a refined pl...

In this paper we present a very simple, efficient while effective placement algorithm for Row-based VLSIs. This algorithm is based on strict mathematical analysis, and provably can find the global optima. From our experiments, this algorithm is one of the fastest algorithms, especially for very large scale circuits. Another point desired to point out is that our algorithm can be run in both wir...

The dynamic multicriteria optimization problem related to the regulation of lake-river systems is a challenging one. It is typical that there are strong control constraints imposed by legislation and the hydrophysics as well as multiple environmental criteria and uncertainties due to weather conditions. We will introduce a dynamic goal programming approach to the multicriteria control problem w...

In this paper, for topology optimization of double layer grids, an efficient optimization method is presented by combination of Imperialist Competitive Algorithm (ICA) and Gravitational Search Algorithm (GSA) which is called ICA-GSA method. The present hybrid method is based on ICA but the moving of countries toward their relevant imperialist is done using the la...