Solving molecular flexible docking problems with metaheuristics: A comparative study
نویسندگان
چکیده
منابع مشابه
Solving molecular docking problems with multi-objective metaheuristics.
Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. 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 clarif...
متن کاملParaDockS: A Framework for Molecular Docking with Population-Based Metaheuristics
Molecular docking is a simulation technique that aims to predict the binding pose between a ligand and a receptor. The resulting multidimensional continuous optimization problem is practically unsolvable in an exact way. One possible approach is the combination of an optimization algorithm and an objective function that describes the interaction. The software ParaDockS is designed to hold diffe...
متن کاملA comparative study on multiobjective metaheuristics for solving constrained in-core fuel management optimisation problems
In this paper, the topic of constrained multiobjective in-core fuel management optimisation (MICFMO) using metaheuristics is considered. Several modern and stateof-the-art metaheuristics from different classes, including evolutionary algorithms, local search algorithms, swarm intelligence algorithms, a probabilistic model-based algorithm and a harmony search algorithm, are compared in order to ...
متن کاملHeuristics and Metaheuristics for Solving Scheduling Problems
Manufacturing scheduling plays a very important function in successful operation of the production planning and control department of an organization. It also offers a great theoretical challenge to the researchers because of its combinatorial nature. Earlier, researchers emphasized classical optimization methods such as linear programming and branch-and-bound method to solve scheduling problem...
متن کاملComparative Study of Cuckoo Inspired Metaheuristics Applying to Knapsack Problems
Cuckoo Optimization Algorithm (COA) and Cuckoo Search Algorithm (CS) are two population-based metaheuristics. They are based on the cuckoo’s behavior in their lifestyle and their characteristics in egg laying and breeding. Both algorithms are proposed for continuous optimization problems. In this paper, we propose a comparative study of COA and CS. For this we have proposed a binary version of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Soft Computing
سال: 2015
ISSN: 1568-4946
DOI: 10.1016/j.asoc.2014.10.049