Reinforcement learning for combinatorial optimization: A survey
Many traditional algorithms for solving combinatorial optimization problems involve using
hand-crafted heuristics that sequentially construct a solution. Such heuristics are designed …
hand-crafted heuristics that sequentially construct a solution. Such heuristics are designed …
Automated algorithm selection: Survey and perspectives
It has long been observed that for practically any computational problem that has been
intensely studied, different instances are best solved using different algorithms. This is …
intensely studied, different instances are best solved using different algorithms. This is …
Leveraging TSP solver complementarity through machine learning
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 …
problems. Over the years, many different solution approaches and solvers have been …
A case study of algorithm selection for the traveling thief problem
Many real-world problems are composed of several interacting components. In order to
facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in …
facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in …
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem
Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems.
With this paper we contribute to the understanding of the success of 2-opt based local …
With this paper we contribute to the understanding of the success of 2-opt based local …
Deep learning as a competitive feature-free approach for automated algorithm selection on the traveling salesperson problem
In this work we focus on the well-known Euclidean Traveling Salesperson Problem (TSP)
and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per …
and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per …
Problem features versus algorithm performance on rugged multiobjective combinatorial fitness landscapes
In this article, we attempt to understand and to contrast the impact of problem features on the
performance of randomized search heuristics for black-box multiobjective combinatorial …
performance of randomized search heuristics for black-box multiobjective combinatorial …
Which local search operator works best for the open-loop TSP?
The traveling salesman problem (TSP) has been widely studied for the classical closed-loop
variant. However, very little attention has been paid to the open-loop variant. Most of the …
variant. However, very little attention has been paid to the open-loop variant. Most of the …
Effectiveness of local search for geometric optimization
V Cohen-Addad, C Mathieu - 31st International Symposium on …, 2015 - drops.dagstuhl.de
What is the effectiveness of local search algorithms for geometric problems in the plane? We
prove that local search with neighborhoods of magnitude 1/epsilon^ c is an approximation …
prove that local search with neighborhoods of magnitude 1/epsilon^ c is an approximation …
Evolutionary algorithm with geometrical heuristics for solving the Close Enough Traveling Salesman Problem: Application to the trajectory planning of an Unmanned …
Evolutionary algorithms have been widely studied in the literature to find sub-optimal
solutions to complex problems as the Traveling Salesman Problem (TSP). In such a …
solutions to complex problems as the Traveling Salesman Problem (TSP). In such a …