Note on the Work Function Algorithm
نویسنده
چکیده
We prove that the work function algorithm is (n ? 1)-competitive for the k-server problem, where n is the number of points in the metric space. This gives improved upper bounds when k + 3 n 2k ?1; in particular, it shows that the work function algorithm is optimal for k = n ? 1.
منابع مشابه
Pareto Optimization of a Two-degree of Freedom Passive Linear Suspension Using a New Multi-objective Genetic Algorithm (TECHNICAL NOTE)
The primary function of a suspension system of a vehicle is to isolate the road excitations experienced by the tires from being transmitted to the passengers. In this paper, we formulate an optimal vehicle suspension design problem with the quarter-car vehicle dynamic model. A new multi-objective genetic algorithm is used for Pareto optimization of a two-degree of freedom vehicle vibration mode...
متن کاملOptimal Design of a Brushless DC Motor, by Cuckoo Optimization Algorithm (RESEARCH NOTE)
This contribution deals with an optimal design of a brushless DC motor, using optimization algorithms, based on collective intelligence. For this purpose, the case study motor is perfectly explained and its significant specifications are obtained as functions of the motor geometric parameters. In fact, the geometric parameters of the motor are considered as optimization variables. Then, the obj...
متن کاملDiscrete Multi Objective Particle Swarm Optimization Algorithm for FPGA Placement (RESEARCH NOTE)
Placement process is one of the vital stages in physical design. In this stage, modules and elements of circuit are placed in distinct locations according to optimization basis. So that, each placement process tries to influence on one or more optimization factor. In the other hand, it can be told unequivocally that FPGA is one of the most important and applicable devices in our electronic worl...
متن کاملOptimization of Meshless Local Petrov-Galerkin Parameters using Genetic Algorithm for 3D Elasto-static Problems (TECHNICAL NOTE)
A truly Meshless Local Petrov-Galerkin (MLPG) method is developed for solving 3D elasto-static problems. Using the general MLPG concept, this method is derived through the local weak forms of the equilibrium equations, by using a test function, namely, the Heaviside step function. The Moving Least Squares (MLS) are chosen to construct the shape functions. The penalty approach is used to impose ...
متن کاملAerodynamic Design Optimization Using Genetic Algorithm (RESEARCH NOTE)
An efficient formulation for the robust shape optimization of aerodynamic objects is introduced in this paper. The formulation has three essential features. First, an Euler solver based on a second-order Godunov scheme is used for the flow calculations. Second, a genetic algorithm with binary number encoding is implemented for the optimization procedure. The third ingredient of the procedure is...
متن کاملA Trust Region Algorithm for Solving Nonlinear Equations (RESEARCH NOTE)
This paper presents a practical and efficient method to solve large-scale nonlinear equations. The global convergence of this new trust region algorithm is verified. The algorithm is then used to solve the nonlinear equations arising in an Expanded Lagrangian Function (ELF). Numerical results for the implementation of some large-scale problems indicate that the algorithm is efficient for these ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Acta Cybern.
دوره 14 شماره
صفحات -
تاریخ انتشار 2000