Many computer vision problems can be cast as an optimization problem whose feasible solutions are decompositions of a graph. The minimum cost lifted multicut problem is such an optimization problem. Its objective function can penalize or reward all decompositions for which any given pair of nodes are in distinct components. While this property has many potential applications, such applications ...

The partitioning of random graphs is investigated numerically using \simulated annealing" and \extremal optimization." While generally an NP-hard problem, it is shown that the optimization of the graph partitions is particularly diicult for sparse graphs with average connectivities near the percolation threshold. At this threshold, the relative error of \simulated annealing" is found to diverge...

In this letter we discuss cost optimization of sensor networks monitoring structurally full-rank systems under distributed observability constraint. Using structured systems theory, the problem is relaxed into two subproblems: (i) sensing cost optimization and (ii) networking cost optimization. Both problems are reformulated as combinatorial optimization problems. The sensing cost optimization ...

In this article, adaptive resource allocation (ARA) is investigated for multiple primary networks based-cognitive radio networks under a more practical system model, where the bandwidth of each secondary user is assumed to be limited and the maximum allowable interference for each primary network is different. We first formulate the ARA as a constrained optimization problem with the objective f...

Travelling salesman problem (TSP) is a combinatorial optimization problem. It is NP hard problem and TSP is the most intensively studied problem in the area of optimization. There are a number of approximation algorithms and heuristics proposed in the literature which can yield to good solutions. But with the increase in the number of cities, the complexity of the problem goes on increasing. Th...

It is significant to discover a global optimization in the problems dealing with large dimensional scales to increase the quality of decision-making in the mining operation. It has been broadly confirmed that the long-term production scheduling (LTPS) problem performs a main role in mining projects to develop the performance regarding the obtainability of constraints, while maximizing the whole...

The traveling salesman problem and the quadratic assignment problem are the two of the most commonly studied optimization problems in Operations Research because of their wide applicability. Due to their NP-hard nature, the individual problems are already complex and difficult to solve. In this paper, the two hard problems are integrated together first, that is called the integrated problem of ...

We propose a new method for finding the minimum ratio-cut of a graph. Ratio-cut is NP-hard problem for which the best previously known algorithm gi ves an O(log n)-factor approximation by solving its dually related maximum concurrent flow problem. We formulate the minimum ratio-cut as a certain nondifferentiable optimization problem, and sho w that the global minimum of the optimization problem...

State of the art methods for generating non-player character (NPC) tactical behaviors typically depend on hard-coding actions or minimizing a given objective function. In many games however, it is hard to foresee how the NPC should behave to appear intelligent or to accommodate human player preferences for NPC tactics. In this paper we consider an alternative approach, by training NPC tactical ...

in this paper, according to high load capacity and rather large workspace characteristics of cable driven robots (cdrs), maximum dynamic load carrying capacity (dlcc) between two given end points in the workspace along with optimal trajectory is obtained. in order to find dlcc of cdrs, joint actuator torque and workspace of the robot constraints concerning to non-negative tension in cables are ...