A brilliant treatment of a knotty problem in computing. This volume contains chapters written
by reputable researchers and provides the state of the art in theory and algorithms for the …

For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between
two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms …

Contemporary flowshops that are variants of the classical flowshop frequently pose
challenging scheduling problems. Such flowshops include no-wait, blocking, and robotic …

Abstract Machine Learning (ML) can help solve combinatorial optimization (CO) problems
better. A popular approach is to use a neural net to compute on the parameters of a given …

Heuristics for the traveling salesman problem (TSP) have made remarkable advances in
recent years. We survey the leading methods and the special components responsible for …

This article presented a parallel cooperative hybrid algorithm for solving traveling salesman
problem. Although heuristic approaches and hybrid methods obtain good results in solving …

Computational experiments show that the greedy algorithm (GR) and the nearest neighbor
algorithm (NN), popular choices for tour construction heuristics, work at acceptable level for …

This paper describes an algorithm for minimizing the non-productive time or 'airtime'for
milling by optimally connecting different toolpath segments. This problem is formulated as a …

Abstract POPMUSIC—Partial OPtimization Metaheuristic Under Special Intensification
Conditions—is a template for tackling large problem instances. This metaheuristic has been …

In this chapter, we consider what approaches one should take when confronting a real-world
application of the asymmetric TSP, that is, the general TSP in which the distance d (c, c′) …