This chapter surveys approximation algorithms for hard geometric problems. The problems
we consider typically take inputs that are point sets or polytopes in two-or three-dimensional …

We present a polynomial time approximation scheme for Euclidean TSP in fixed dimensions.
For every fixed c> 1 and given any n nodes in ℛ2, a randomized version of the scheme finds …

In this paper, we analyze local search heuristics for the k-median and facility location
problems. We define the\em locality gap\/of a local search procedure as the maximum ratio …

Local search with k-exchange neighborhoods, k-opt, is the most widely used heuristic
method for the traveling salesman problem (TSP). This paper presents an effective …

We are pleased to introduce the third edition of the book, and we are thankful to those who
used the book in research and practice and to those who sent us comments and feedback …

Most textbooks on modern heuristics provide the reader with detailed descriptions of the
functionality of single examples like genetic algorithms, genetic programming, tabu search …

We present a polynomial time approximation scheme for Euclidean TSP in/spl Rfr//sup 2/.
Given any n nodes in the plane and/spl epsiv/> 0, the scheme finds a (1+/spl epsiv/) …

Local search has been applied successfully to a diverse collection of optimization problems.
It's appreciated for its basic conceptual foundation, its general applicability, and its power to …

Opt is probably the most basic local search heuristic for the TSP. This heuristic achieves
amazingly good results on “real world” Euclidean instances both with respect to running time …

Mobile crowdsensing has been a promising and cost-effective sensing paradigm for the
Internet of Things by exploiting the proliferation and prevalence of sensor-rich mobile …