Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems
نویسندگان
چکیده
In this study, the performance of Slime-Mould-Algorithm (SMA), a current Meta-Heuristic Search algorithm, is improved. order to model search process lifecycle more effectively in SMA solution candidates guiding were determined using fitness-distance balance (FDB) method. Although algorithm accepted, it seen that FDB-SMA developed thanks applied FDB method much better. CEC 2020, which has benchmark problems, was used test algorithm. 10 different unconstrained comparison problems taken from 2020 are designed by arranging them 30-50-100 dimensions. Experimental studies carried out and analyzed with Friedman Wilcoxon statistical methods. According results analysis, been variations outperform basic (SMA) all experimental studies.
منابع مشابه
Improved Cuckoo Search Algorithm for Global Optimization
The cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. To enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. Normally, the parametersof the cuckoo search are kept constant. This may lead todecreasing the efficiency of the algorithm. To cop...
متن کاملimproved cuckoo search algorithm for global optimization
the cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. to enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. normally, the parametersof the cuckoo search are kept constant. this may lead todecreasing the efficiency of the algorithm. to cop...
متن کاملA Stochastic/Perturbation Global Optimization Algorithm for Distance Geometry Problems
We present a new global optimization approach for solving exactly or inexactly constrained distance geometry problems. Distance geometry problems are concerned with determining spatial structures from measurements of internal distances. They arise in the structural interpretation of nuclear magnetic resonance data and in the prediction of protein structure. These problems can be naturally formu...
متن کاملAn Improved Bat Algorithm with Grey Wolf Optimizer for Solving Continuous Optimization Problems
Metaheuristic algorithms are used to solve NP-hard optimization problems. These algorithms have two main components, i.e. exploration and exploitation, and try to strike a balance between exploration and exploitation to achieve the best possible near-optimal solution. The bat algorithm is one of the metaheuristic algorithms with poor exploration and exploitation. In this paper, exploration and ...
متن کاملA Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems
A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best ...
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: Düzce Üniversitesi bilim ve teknoloji dergisi
سال: 2021
ISSN: ['2148-2446']
DOI: https://doi.org/10.29130/dubited.1016209