We investigate per-instance algorithm selection techniques for solving the Travelling
Salesman Problem (TSP), based on the two state-of-the-art inexact TSP solvers, LKH and …

Abstract The Travelling Salesperson Problem (TSP) is one of the best-studied NP-hard
problems. Over the years, many different solution approaches and solvers have been …

Building on the award-winning, portfolio-based ASP solver claspfolio, we present claspfolio
2, a modular and open solver architecture that integrates several different portfolio-based …

Cost-optimal planning has not seen many successful approaches that work well across all
domains. Some costoptimal planners excel on some domains, while exhibiting less exciting …

As classical planning is known to be computationally hard, no single planner is expected to
work well across many planning domains. One solution to this problem is to use online …

Automated planning is one of the foundational areas of AI. Since no single planner can work
well for all tasks and domains, portfolio-based techniques have become increasingly …

A key challenge in satisficing planning is to use multiple heuristics within one heuristic
search. An aggregation of multiple heuristic estimates, for example by taking the maximum …

State-of-the-art planners often exhibit substantial runtime variation, making it useful to be
able to efficiently predict how long a given planner will take to run on a given instance. In …

Sequential planning portfolios exploit the complementary strengths of different planners.
Similarly, automated algorithm configuration tools can customize parameterized planning …

Subgraph isomorphism is a computationally challenging problem with important practical
applications, for example in computer vision, biochemistry, and model checking. There are a …