Monte Carlo sampling for the tourist trip design problem

A Personalized Tourist Trip Design Algorithm for Mobile Tourist Guides

Mobile Tourist Guides evolve towards automated personalised tour planning devices [4]. The contribution of this paper is to put forward a combined artificial intelligence and metaheuristic approach to solve Tourist Trip Design Problems (TTDP). The approach enables fast decision support for tourists on small footprint mobile devices. The Orienteering Problem, which originates in the Operational ...

Efficient Sampling Method for Monte Carlo Tree Search Problem

We consider Monte Carlo tree search problem, a variant of Min-Max tree search problem where the score of each leaf is the expectation of some Bernoulli variables and not explicitly given but can be estimated through (random) playouts. The goal of this problem is, given a game tree and an oracle that returns an outcome of a playout, to find a child node of the root which attains an approximate m...

Christiane Lemieux Monte Carlo and Quasi - Monte Carlo Sampling

the algorithm for solving the inverse numerical range problem

برد عددی ماتریس مربعی a را با w(a) نشان داده و به این صورت تعریف می کنیم w(a)={x8ax:x ?s1} ، که در آن s1 گوی واحد است. در سال 2009، راسل کاردن مساله برد عددی معکوس را به این صورت مطرح کرده است : برای نقطه z?w(a)، بردار x?s1 را به گونه ای می یابیم که z=x*ax، در این پایان نامه ، الگوریتمی برای حل مساله برد عددی معکوس ارانه می دهیم.

Design of Sparse Linear Arrays by Monte Carlo Importance Sampling

The formation of acoustic images in real-time requires an enormous computational burden. To reduce this demand the use of sparse arrays for beamforming is mandated. The design of these arrays for adequate mainlobe width and low sidelobe level is a difficult nonlinear optimization problem. A new approach to the joint optimization of sensor placement and shading weights is discussed. Based on the...