Multi-Objective Optimization Algorithms to Solve Molecular Docking

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 bymeans 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.

New Hybrid Evolutionary Algorithm for Solving Multi-Objective Optimization Problems

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.