This chapter reviews some of the best metaheuristics proposed in recent years for the
Vehicle Routing Problem. These are based on local search, on population search and on …

The key idea underlying iterated local search is to focus the search not on the full space of
all candidate solutions but on the solutions that are returned by some underlying algorithm …

The importance of high performance algorithms for tackling difficult optimization problems
cannot be understated, and in many cases the only available methods are metaheuristics …

Abstract The Traveling Salesman Problem (TSP) is one of the most famous problems in
combinatorial optimization. In this paper, we are going to examine how the techniques of …

We discuss several issues that arise in the implementation of Martin, Otto, and Felten's
Chained Lin-Kernighan heuristic for large-scale traveling salesman problems …

In this and the following chapter, we consider what approaches one should take when one is
confronted with a real-world application of the TSP. What algorithms should be used under …

Reactive Search integrates sub-symbolic machine learning techniques into search
heuristics for solving complex optimization problems. By automatically adjusting the working …

Iterated local search (ILS) is a general and powerful metaheuristic which provides an easily
implementable way of improving the performance of local search algorithms. In this article …

Memetic algorithms (MAs) have been shown to be very effective in finding near-optimum
solutions to hard combinatorial optimization problems. In this paper, the fitness landscapes …

In this work, we present a method, called Two-Phase Pareto Local Search, to find a good
approximation of the efficient set of the biobjective traveling salesman problem. In the first …