On the relationship of approximation algorithms for the minimum and the maximum traveling salesman problem

1986 ◽  
Vol 26 (2) ◽  
pp. 262-265 ◽  
Author(s):  
Frank Korner
2020 ◽  
Vol 39 (5) ◽  
pp. 7505-7519
Author(s):  
Meng Li ◽  
Yifei Zhao ◽  
Xinglong Xiong ◽  
Yuzhao Ma

Synchronous delivery with different vehicles, as an emerging concept of the delivery network, improves the efficiency of the modern logistics system significantly, which gradually gives birth to a new issue: the traveling salesman problem with drone (TSP-D). In this paper, we propose a one-truck-multiple-drone (OTMD) model on the base of the TSP-D. Compared with the traditional one-truck-one-drone (OTOD) and multiple drones models, our scheme introduces a united objective function into the optimization calculation. In terms of the proposed multiple levels iterative theory, we can compute the optimal synchronous delivery network that takes both the total delivery time and the number of drones into consideration. Four types of customer distributions are employed to investigate the OTMD model and its associated calculation approaches. Comparing the parameters of the optimal network in different delivery models, we study the relationship among the total delivery time, customer distribution and the number of serving drones. These simulation results verify the feasibility and practicality of the OTMD, and demonstrate the features of optimization calculation with different customer distributions, being beneficial to improve the efficiency of the model logistics system.


2001 ◽  
Vol 12 (06) ◽  
pp. 809-819 ◽  
Author(s):  
DAVID BLOKH ◽  
EUGENE LEVNER

We investigate the Maximum Traveling Salesman Problem on banded distance matrices. A (p, q)-banded matrix has all its non-zero elements contained within a band consisting of p diagonals above the principal diagonal and q diagonals below it. We investigate the properties of the problem and prove that the number K of different permutations which can be optimal solutions for different instances of the problem, is exponential in n where n is the problem size (= the number of cities). For the Maximum-TSP on the (2, 0)-banded matrices, K=O(λn) where 1.7548 <λ< 1.7549, whereas on the (1, 1)-banded matrices K=O(λn) where 1.6180 <λ< 1.6181. Using recursive equations, we derive a linear-time algorithm that exactly solves the Maximum-TSP on the (2, 0)-banded distance matrices.


Sign in / Sign up

Export Citation Format

Share Document