This paper deals with the problem of constructing a Hamiltonian cycle of optimal weight, called TSP. We show that TSP is 2/3-differential approximable and cannot be differential approximable greater than 649/650. Next, we demonstrate that, when dealing with edge-costs 1 and 2, the same algorithm idea improves this ratio to 3/4 and we obtain a differential non-approximation threshold equal to 741/742. Remark that the 3/4-differential approximation result has been recently proved by a way more specific to the 1-, 2-case and with another algorithm in the recent conference, Symposium on Fundamentals of Computation Theory, 2001. Based upon these results, we establish new bounds for standard ratio: 5/6 for Max TSP[a,2a] and 7/8 for Max TSP[1,2]. ...
The Traveling Salesman Problem (TSP) is the task of finding a route through a given set of cities wi...
Abstract. We present an approximation algorithm for {0, 1}-instances of the travelling salesman prob...
AbstractThe investigation of the possibility to efficiently compute approximations of hard optimizat...
This paper deals with the problem of constructing a Hamiltonian cycle of optimal weight, called TSP...
We prove that both minimum and maximum traveling salesman problems on complete graphs with edge-dist...
This paper deals with the problem of constructing Hamiltonian paths of optimal weight, called HPP_s,...
The traveling salesman problem (TSP) is one of the most fundamental optimization problems....
The traveling salesman problem (TSP) is the problem of finding a shortest Hamiltonian circuit or pat...
This paper deals with the problem of constructing Hamiltonian paths of optimal weight, called HPPs,t...
We first prove that the minimum and maximum traveling salesman problems, their metric versions as we...
TSP(1,2) is the problem of finding a tour with minimum length in a complete weighted graph where eac...
Though 2-approximation algorithms are available for several Multiple Depot Travelling Salesman Probl...
The traveling salesman problem is one of the most important problems in operations researc...
The Clarke and Wright heuristic for the travelling salesman problem (TSP) has been used for several ...
n this extended abstract, we survey some of the recent results on approximating the traveling salesm...
The Traveling Salesman Problem (TSP) is the task of finding a route through a given set of cities wi...
Abstract. We present an approximation algorithm for {0, 1}-instances of the travelling salesman prob...
AbstractThe investigation of the possibility to efficiently compute approximations of hard optimizat...
This paper deals with the problem of constructing a Hamiltonian cycle of optimal weight, called TSP...
We prove that both minimum and maximum traveling salesman problems on complete graphs with edge-dist...
This paper deals with the problem of constructing Hamiltonian paths of optimal weight, called HPP_s,...
The traveling salesman problem (TSP) is one of the most fundamental optimization problems....
The traveling salesman problem (TSP) is the problem of finding a shortest Hamiltonian circuit or pat...
This paper deals with the problem of constructing Hamiltonian paths of optimal weight, called HPPs,t...
We first prove that the minimum and maximum traveling salesman problems, their metric versions as we...
TSP(1,2) is the problem of finding a tour with minimum length in a complete weighted graph where eac...
Though 2-approximation algorithms are available for several Multiple Depot Travelling Salesman Probl...
The traveling salesman problem is one of the most important problems in operations researc...
The Clarke and Wright heuristic for the travelling salesman problem (TSP) has been used for several ...
n this extended abstract, we survey some of the recent results on approximating the traveling salesm...
The Traveling Salesman Problem (TSP) is the task of finding a route through a given set of cities wi...
Abstract. We present an approximation algorithm for {0, 1}-instances of the travelling salesman prob...
AbstractThe investigation of the possibility to efficiently compute approximations of hard optimizat...