Region-based memetic algorithm with archive for multimodal optimisation
نویسندگان
چکیده
منابع مشابه
Region-based memetic algorithm with archive for multimodal optimisation
In this paper we propose a specially designed memetic algorithm for multimodal optimisation problems. The proposal uses a niching strategy, called region-based niching strategy, that divides the search space in predefined and indexable hypercubes with decreasing size, called regions. This niching technique allows our proposal to keep high diversity in the population, and to keep the most promis...
متن کاملRegion based memetic algorithm for real-parameter optimisation
Memetic algorithms with an appropriate trade-off between the exploration and exploitation can obtain very good results in continuous optimisation. That implies the evolutionary algorithm should be focused in exploring the search space while the local search method exploits the achieved solutions. To tackle this issue, we propose to maintain a higher diversity in the evolutionary algorithm's pop...
متن کاملA memetic particle swarm optimisation algorithm for dynamic multi-modal optimisation problems
Hongfeng Wang*, Shengxiang Yang, W.H. Ip and Dingwei Wang College of Information Science and Engineering, Northeastern University, Shenyang 110004, China; State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110004, China; Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, UK; College of Mathematic...
متن کاملA Hooke-Jeeves Based Memetic Algorithm for Solving Dynamic Optimisation Problems
Dynamic optimisation problems are difficult to solve because they involve variables that change over time. In this paper, we present a new HookeJeeves based Memetic Algorithm (HJMA) for dynamic function optimisation, and use the Moving Peaks (MP) problem as a test bed for experimentation. The results show that HJMA outperforms all previously published approaches on the three standardised benchm...
متن کاملMemetic Algorithms for Continuous Optimisation Based on Local Search Chains
Memetic algorithms with continuous local search methods have arisen as effective tools to address the difficulty of obtaining reliable solutions of high precision for complex continuous optimisation problems. There exists a group of continuous local search algorithms that stand out as exceptional local search optimisers. However, on some occasions, they may become very expensive, because of the...
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: Information Sciences
سال: 2016
ISSN: 0020-0255
DOI: 10.1016/j.ins.2016.05.049