Certification of an optimal TSP tour through 85,900 cities

We describe a computer code and data that together certify the optimality of a solution to the 85,900-city traveling salesman problem pla85900, the largest instance in the TSPLIB collection of challenge problems.     

Multi-criteria TSP: Min and max combined

We present randomized approximation algorithms for multi-criteria traveling salesman problems (TSP), where some objective functions should be minimized while others should be maximized. For the symmetric multi-criteria TSP (STSP), we present an algorithm that computes (2/3,3+ε)-approximate Pareto curves. Here, the first parameter is the approximation ratio for the objectives that should be maximized, and the second parameter is the ratio for the objectives that should be minimized. For the asymmetric multi-criteria TSP (ATSP), we obtain an approximation performance of (1/2,log₂n+ε).     

On the nearest neighbor rule for the traveling salesman problem

Rosenkrantz et al. (SIAM J. Comput. 6 (1977) 563) and Johnson and Papadimitriou (in: E.L. Lawler, J.K. Lenstra, A.H.G. Rinnooy Kan, D.B. Shmoys (Eds.), The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization, Wiley, Chichester, 1985, pp. 145-180, (Chapter 5)) constructed families of TSP instances with n cities for which the nearest neighbor rule yields a tour-length that is a factor above the length of the optimal tour.We describe two new families of TSP instances, for which the nearest neighbor rule shows the same bad behavior. The instances in the first family are graphical, and the instances in the second family are Euclidean. Our construction and our arguments are extremely simple and suitable for classroom use.     

Four-point conditions for the TSP: The complete complexity classification

The combinatorial optimization literature contains a multitude of polynomially solvable special cases of the traveling salesman problem (TSP) which result from imposing certain combinatorial restrictions on the underlying distance matrices. Many of these special cases have the form of so-called four-point conditions: inequalities that involve the distances between four arbitrary cities.In this paper we classify all possible four-point conditions for the TSP with respect to computational complexity, and we determine for each of them whether the resulting special case of the TSP can be solved in polynomial time or whether it remains NP-hard.     

Finding low cost TSP and 2-matching solutions using certain half-integer subtour vertices

Consider the traveling salesman problem (TSP) defined on the complete graph, where the edge costs satisfy the triangle inequality. Let TOUR denote the optimal solution value for the TSP. Two well-known relaxations of the TSP are the subtour elimination problem and the 2-matching problem. If we let SUBT and 2M represent the optimal solution values for these two relaxations, then it has been conjectured that TOUR/SUBT ≤4/3, and that 2M/SUBT ≤10/9.In this paper, we exploit the structure of certain 1/2-integer solutions for the subtour elimination problem in order to obtain low cost TSP and 2-matching solutions. In particular, we show that for cost functions for which the optimal subtour elimination solution found falls into our classes, the above two conjectures are true. Our proofs are constructive and could be implemented in polynomial time, and thus, for such cost functions, provide a 4/3 (or better) approximation algorithm for the TSP.     

On the tour partitioning heuristic for the unit demand capacitated vehicle routing problem

The tour partitioning heuristic for the vehicle routing problem assumes an unlimited supply of vehicles. If the number of vehicles is fixed, this heuristic may produce infeasible solutions. We modify the heuristic to guarantee feasibility in this situation and we analyze the worst-case performance of the modified heuristic.     

Average-case approximation ratio of the 2-opt algorithm for the TSP

We show that the 2-opt heuristic for the traveling salesman problem achieves an expected approximation ratio of roughly for instances with n nodes, where the edge weights are drawn uniformly and independently at random.     

模糊蚁群算法及其在TSP中的应用

在传统蚁群算法的基础上加入了使用模糊规则表更新信息素的策略,提出了一种新的算法——模糊蚁群算法.算法结合了模糊控制中输入输出的模糊化处理和蚁群寻优的特点,为实际问题提供了新的解决手段.文中将模糊蚁群算法应用于TSP问题,通过对中国31个省会城市等实例数据进行的测试,验证表明了新算法具有良好的有效性和鲁棒性.     

Greedy heuristics with regret, with application to the cheapest insertion algorithm for the TSP

We consider greedy algorithms that allow partial regret. As an example we consider a variant of the cheapest insertion algorithm for the TSP. Our numerical study indicates that in most cases it significantly reduces the relative error, and the added computational time is quite small.     

A new lower bound for the geometric traveling salesman problem in terms of discrepancy

We give a new lower bound for the shortest hamiltonian path through n points of [0,1]^d in terms of the discrepancy of these n points. This improves an earlier result by Steele.     

A 4/3-approximation for TSP on cubic 3-edge-connected graphs

For a 3-edge-connected cubic graph $G=(V,E)$, we give an algorithm to construct a connected Eulerian subgraph of $2G$ using at most $?4\left|V\right|∕3?$ edges.     

A threshold accepting heuristic with intense local search for the solution of special instances of the traveling salesman problem

In real life scheduling, variations of the standard traveling salesman problem are very often encountered. The aim of this work is to present a new heuristic method for solving three such special instances with a common approach. The proposed algorithm uses a variant of the threshold accepting method, enhanced with intense local search, while the candidate solutions are produced through an insertion heuristic scheme. The main characteristic of the algorithm is that it does not require modifications and parameter tuning in order to cope with the three different problems. Computational results on a variety of real life and artificial problems are presented at the end of this work and prove the efficiency and the ascendancy of the proposed method over other algorithms found in the literature.     

Algorithms for the universal and a priori TSP

We present two simple results for generalizations of the traveling salesman problem (TSP): for the universal TSP, we show that one can compute a tour that is universally optimal whenever the input is a tree metric. A (randomized) O(logn)-approximation algorithm for the a priori TSP follows as a corollary.     

A production scheduling heuristic for an electronics manufacturer with sequence-dependent setup costs

In this paper, we develop a three-step heuristic to address a production scheduling problem at a high volume assemble-to-order electronics manufacturer. The heuristic provides a solution for scheduling multiple product families on parallel, identical production lines so as to minimize setup costs. The heuristic involves assignment, sequencing, and time scheduling steps, with an optimization approach developed for each step. For the most complex step, the sequencing step, we develop a greedy randomized adaptive search procedure (GRASP). We compare the setup costs resulting from the use of our scheduling heuristic against a heuristic previously developed and implemented at the electronics manufacturer that assumes approximately equal, sequence-independent, setup costs. By explicitly considering the sequence-dependent setup costs and applying GRASP, our empirical results show a reduction in setups costs for an entire factory of 14–21% with a range of single production line reductions from 0% to 49%.     

On the integrality ratio of the subtour LP for Euclidean TSP

A long standing conjecture says that the integrality ratio of the subtour LP for metric TSP is 4/3$4/3$. A well known family of graphic TSP instances achieves this lower bound asymptotically. For Euclidean TSP the best known lower bound on the integrality ratio was 8/7$8/7$. We improve this value by presenting a family of Euclidean TSP instances for which the integrality ratio of the subtour LP converges to 4/3.     

The two-convex-polygons TSP: A solvable case

In this paper, the Travelling Salesman Problem whenm points are on one convex polygonP, andn points are on another convex polygonQ, insideP, is polynomially solved. For this specific case, anO(m ³ n ³) time andO(m ² n ²) space algorithm to obtain the tour with minimum length is provided.     

New TSP Construction Heuristics and Their Relationships to the 2-Opt

Correction heuristics for the traveling salesman problem (TSP), with the 2-Opt applied as a postprocess, are studied with respect to their tour lengths and computation times. This study analyzes the 2-Opt dependency, which indicates how the performance of the 2-Opt depends on the initial tours built by the construction heuristics. In accordance with the analysis, we devise a new construction heuristic, the recursive-selection with long-edge preference (RSL) method, which runs faster than the multiple-fragment method and produces a comparable tour when they are combined with the 2-Opt.