Molecular docking is a hard optimization problem that has been
tackled in the past, demonstrating new and challenging results when
looking for one objective . However, only a few papers can be
found in the literature that deal with this problem by
means of a
multi-objective approach, and no experimental comparisons have
been made in order to clarify which of them has the best overall
performance. In this research, we use and compare, a set of
representative multi-objective optimization algorithms. The
approach followed is focused on optimizing the inter-molecular and
intra-molecular energies as two main objectives to minimize.
Multi-objective evolutionary algorithms are used in a wide range
of fields to solve the issues of optimization, which require several
conflicting objectives to be considered together. Basic evolutionary
algorithm algorithms have several drawbacks,
such as lack of a
good criterion for termination, and lack of evidence of good
convergence. A multi-objective hybrid evolutionary algorithm is
often used to overcome these defects.
optimization
الأمثلة
الأمثلة متعددة الأهداف
الخوارزميات التطورية
الخوارزميات التطورية المتعددة الأهداف
الخوارزميات التطورية عديدة الأهداف
(Multi-Objective Optimization (MO
Evolutionary Algorithms
(Multi-Objective Evolutionary Algorithms (MOEAs
(Many-Objective Evolutionary Algorithms (MaOEAs
المزيد..