Now showing items 1-5 of 5
Statistical assessment of experimental results: a graphical approach for comparing algorithms
Non-deterministic measurements are common in real-world scenarios: the performance of a stochastic optimization algorithm or the total reward of a reinforcement learning agent in a chaotic environment are just two examples ...
On the fair comparison of optimization algorithms in different machines
An experimental comparison of two or more optimization algorithms requires the same computational resources to be assigned to each algorithm. When a maximum runtime is set as the stopping criterion, all algorithms need to ...
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment Problem
The Quadratic Assignment Problem (QAP) is a well-known permutation-based combinatorial optimization problem with real applications in industrial and logistics environments. Motivated by the challenge that this NP-hard ...
An adaptive neuroevolution-based hyperheuristic
According to the No-Free-Lunch theorem, an algorithm that performs efficiently on any type of problem does not exist. In this sense, algorithms that exploit problem-specific knowledge usually outperform more generic ...
Approaching the Quadratic Assignment Problem with Kernels of Mallows Models under the Hamming Distance
The Quadratic Assignment Problem (QAP) is a specially challenging permutation-based np-hard combinatorial optimization problem, since instances of size $n>40$ are seldom solved using exact methods. In this sense, many ...