We present approximation algorithms for balanced partitioning problems. These problems are notoriously hard and we present new bicriteria approximation algorithms, that approximate the optimal cost and relax the balance constraint. In the first scenario, we consider Min-Max k-Partitioning, the problem of dividing a graph into k equal-sized parts while minimizing the maximum cost of edges cut by...

We prove a general result demonstrating the power of Lagrangian relaxation in solving constrained maximization problems with arbitrary objective functions. This yields a unified approach for solving a wide class of subset selection problems with linear constraints. Given a problem in this class and some small ε ∈ (0, 1), we show that if there exists a ρ-approximation algorithm for the Lagrangia...

We investigate the optimal portfolio deleveraging (OPD) problem with permanent and temporary price impacts, where objective is to maximize equity while meeting a prescribed debt/equity requirement. take real situation cross impact among different assets into consideration. The resulting is, however, nonconvex quadratic program constraint box constraint, which known be NP-hard. In this paper, we...

In order to select the location of fire stations more scientifically and improve efficiency emergency management in chemical industry parks (CIPs), an improved risk calculation model for hazardous chemicals has been proposed by taking domino effect identification major installations into account. analysis effect, Monte Carlo simulation was used. Then, a established with optimization objectives ...

We consider maximizing a monotone submodular function under cardinality constraint or knapsack in the streaming setting. In particular, elements arrive sequentially and at any point of time, algorithm has access to only small fraction data stored primary memory. propose following algorithms taking O(ε− 1) passes: (1) (1 − e− 1 ε)-approximation for cardinality-constrained problem, (2) (0.5 knaps...

We prove a general result demonstrating the power of Lagrangian relaxation in solving constrained maximization problems with arbitrary objective functions. This yields a unified approach for solving a wide class of subset selection problems with linear constraints. Given a problem in this class and some small ε ∈ (0, 1), we show that if there exists an r-approximation algorithm for the Lagrangi...

This paper is concerned with the numerical approximation of the isothermal Euler equations for charged particles subject to the Lorentz force (the ’Euler-Lorentz’ system). When the magnetic field is large, or equivalently, when the parameter ε representing the non-dimensional ion cyclotron frequency tends to zero, the so-called drift-fluid (or gyrofluid) approximation is obtained. In this limit...

This analysis investigates the distortion of flow measurement and the increase of cavitation along orifice flowmeter. The analysis using the numerical method (CFD) validated the distortion of flow measurement through the inlet velocity profile considering the convergence and grid dependency. Realizable k-e model was selected and y+ was about 50 in this numerical analysis. This analysis also est...

We introduce a tactical resource allocation model for large aerospace engine system manufacturer aimed at long-term production planning. Our identifies the routings product takes through factory, and which machines should be qualified balanced loading, to reduce lead times. prove some important mathematical properties of that are used develop heuristic providing good initial feasible solution. ...

The firstand second-order optimum achievable exponents in the simple hypothesis testing problem are investigated. The optimum achievable exponent for type II error probability, under the constraint that the type I error probability is allowed asymptotically up to ε, is called the ε-optimum exponent. In this paper, we first give the second-order ε-optimum exponent in the case where the null hypo...