Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
An interactive bi-objective shortest path approach: searching for unsupported nondominated solutions
Computers and Operations Research
LEDA: a platform for combinatorial and geometric computing
LEDA: a platform for combinatorial and geometric computing
A minimum spanning tree algorithm with inverse-Ackermann type complexity
Journal of the ACM (JACM)
Minimum-weight spanning tree algorithms a survey and empirical study
Computers and Operations Research
On the History of the Minimum Spanning Tree Problem
IEEE Annals of the History of Computing
A bi-criteria approach for Steiner's tree problems in communication networks
Proceedings of the 2011 International Workshop on Modeling, Analysis, and Control of Complex Networks
Exact algorithms for OWA-optimization in multiobjective spanning tree problems
Computers and Operations Research
A bi-criteria algorithm for multipoint-to-multipoint virtual connections in transport networks
Proceedings of the 7th International Conference on Network and Services Management
Finding all nondominated points of multi-objective integer programs
Journal of Global Optimization
| Hi-index | 0.01 |
A common way of computing all efficient (Pareto optimal) solutions for a biobjective combinatorial optimisation problem is to compute first the extreme efficient solutions and then the remaining, non-extreme solutions. The second phase, the computation of non-extreme solutions, can be based on a ''k-best'' algorithm for the single-objective version of the problem or on the branch-and-bound method. A k-best algorithm computes the k-best solutions in order of their objective values. We compare the performance of these two approaches applied to the biobjective minimum spanning tree problem. Our extensive computational experiments indicate the overwhelming superiority of the k-best approach. We propose heuristic enhancements to this approach which further improve its performance.