Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
The parallel complexity of TSP heuristics
Journal of Algorithms
Symbolic model checking: 1020 states and beyond
Information and Computation - Special issue: Selections from 1990 IEEE symposium on logic in computer science
On the effect of local changes in the variable ordering of ordered decision diagrams
Information Processing Letters
Branching programs and binary decision diagrams: theory and applications
Branching programs and binary decision diagrams: theory and applications
A Symbolic Algorithms for Maximum Flow in 0-1 Networks
Formal Methods in System Design
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
The Traveling Salesman Problem: A Computational Study (Princeton Series in Applied Mathematics)
Exponential space complexity for OBDD-based reachability analysis
Information Processing Letters
The complexity of problems on implicitly represented inputs
SOFSEM'06 Proceedings of the 32nd conference on Current Trends in Theory and Practice of Computer Science
Exponential lower bounds on the space complexity of OBDD-Based graph algorithms
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
An efficient implicit OBDD-Based algorithm for maximal matchings
LATA'12 Proceedings of the 6th international conference on Language and Automata Theory and Applications
On symbolic OBDD-based algorithms for the minimum spanning tree problem
Theoretical Computer Science
Implicit computation of maximum bipartite matchings by sublinear functional operations
TAMC'12 Proceedings of the 9th Annual international conference on Theory and Applications of Models of Computation
| Hi-index | 0.89 |
One approach to deal with very large graphs G=(V,E) consists of a Boolean encoding of the vertices and edges and implicitly representing and manipulating the characteristic functions of V and E using OBDDs, a well-known data structure for Boolean functions. A possibility to attack hard optimization problems is the design of approximation algorithms. Based on the well-known double minimum spanning tree heuristic, the first implicit approximation algorithm is designed for an NP-hard problem, the metric traveling salesperson problem. Priority functions are used in a new approach for the computation of the shortcuts and three different variants are experimentally evaluated with respect to the approximation quality. Furthermore, the worst case complexity of the approximation algorithm is investigated in more detail.