An Improved Generic Bet-and-Run Strategy with Performance Prediction for Stochastic Local Search

A Generic Bet-and-Run Strategy for Speeding Up Stochastic Local Search

A common strategy for improving optimization algorithms is to restart the algorithm when it is believed to be trapped in an inferior part of the search space. However, while specific restart strategies have been developed for specific problems (and specific algorithms), restarts are typically not regarded as a general tool to speed up an optimization algorithm. In fact, many optimization algori...

development and implementation of an optimized control strategy for induction machine in an electric vehicle

in the area of automotive engineering there is a tendency to more electrification of power train. in this work control of an induction machine for the application of electric vehicle is investigated. through the changing operating point of the machine, adapting the rotor magnetization current seems to be useful to increase the machines efficiency. in the literature there are many approaches wh...

A Generic Bet-and-run Strategy for Speeding Up Traveling Salesperson and Minimum Vertex Cover

A common strategy for improving optimization algorithms is to restart the algorithm when it is believed to be trapped in an inferior part of the search space. However, while specific restart strategies have been developed for specific problems (and specific algorithms), restarts are typically not regarded as a general tool to speed up an optimization algorithm. In fact, many optimization algori...

Characterizing the Run-time Behavior of Stochastic Local Search

Stochastic local search (SLS) algorithms have been successfully applied to hard combinatorial problems from diierent domains. One important feature of SLS algorithms is the fact that their run-time behavior is characterized by a random variable. Consequently, the detailed knowledge of the run-time distribution provides important information for the analysis of SLS algorithms. In this paper we i...

1.3 Generic Problem Solving Using Stochastic Local Search::::::::::: 11