Now showing items 1-5 of 5
Bayesian inference for algorithm ranking analysis
The statistical assessment of the empirical comparison of algorithms is an essential step in heuristic optimization. Classically, researchers have relied on the use of statistical tests. However, recently, concerns about ...
Distance-based exponential probability models on constrained combinatorial optimization problems
Estimation of distribution algorithms have already demonstrated their utility when solving a broad range of combinatorial problems. However, there is still room for methodological improvements when approaching constrained ...
Are the artificially generated instances uniform in terms of difficulty?
In the field of evolutionary computation, it is usual to generate artificial benchmarks of instances that are used as a test-bed to determine the performance of the algorithms at hand. In this context, a recent work on ...
Spacecraft Trajectory Optimization: A review of Models, Objectives, Approaches and Solutions
This article is a survey paper on solving spacecraft trajectory optimization problems. The solving process is decomposed into four key steps of mathematical modeling of the problem, defining the objective functions, ...
perm mateda: A matlab toolbox of estimation of distribution algorithms for permutation-based combinatorial optimization problems
Permutation problems are combinatorial optimization problems whose solutions are naturally codified as permutations. Due to their complexity, motivated principally by the factorial cardinality of the search space of ...