An Improved Memetic Algorithm for Break Scheduling

2010 ◽  
pp. 133-147 ◽  
Author(s):  
Magdalena Widl ◽  
Nysret Musliu
Keyword(s):  
Memetic Algorithm ◽  
Improved Memetic Algorithm

scholarly journals Improved Memetic Algorithm Enabled Intelligent Multi Agent (IMAEIMA) System for Web Mining

2019 ◽  
Vol 8 (6) ◽  
pp. 3198-3203
Keyword(s):  
Intelligent Agents ◽  
Web Mining ◽  
Memetic Algorithm ◽  
Relevant Information ◽  
Common People ◽  
User Request ◽  
Multi Agent ◽  
The Common ◽  
Logarithmic Weight ◽  
Improved Memetic Algorithm

Wider web space, the searching of a relevant data is the most curious problem for the common people accessing the web. For retreving the relevant information the user request is given to search engine. The relevant pages combined with irrelevant pages are returned to the user. The proposed work emphasizes an Improved Memetic Algorithm Enabled Intelligent Multi Agent (IMAEIMA) for searching the most appropriate pages when submitting complex queries. Improved Memetic algorithm is the traditional genetic algorithm combined with local search and random selection. In this proposed system Improved Memetic algorithm additionally enhanced with logarithmic weight function for more accuracy. Intelligent Agents are introduced in this IMAEIMA to improve its performance and accuracy by reacting intelligently based on feedback and previous experience. This system helps to retrieve relevant pages from web databases with high precision and recall. The derived architecture reveals greater precision and recall overriding the conventional search algorithms.

Optimization of UWB Receiver using the Improved Memetic Algorithm in WBAN

2013 ◽  
Vol 6 (12) ◽  
pp. 2187-2191
Author(s):  
Qi-Ming Zeng ◽  
Hang Yu ◽  
Yan Li ◽  
Lai Jiang ◽  
Zhen Ji
Keyword(s):  
Memetic Algorithm ◽  
Improved Memetic Algorithm ◽  
Uwb Receiver

Application of Operator Libraries on Laminate Strength Optimization of Composites

2013 ◽  
Vol 853 ◽  
pp. 686-692
Author(s):  
Gong Dong Wang ◽  
Jun Wang ◽  
Hao Chen
Keyword(s):  
Memetic Algorithm ◽  
Laminated Composite ◽  
Object Oriented ◽  
Composite Plates ◽  
Object Oriented Programming ◽  
Local Operator ◽  
Stacking Sequence ◽  
Laminated Composite Plates ◽  
Practical Design ◽  
Improved Memetic Algorithm

An improved Memetic algorithm is applied in this article. Mathematical model is proposed to optimize the laminate strength. The composites laminate strength optimization system with local operator library and rule operator library has been developed by the object-oriented programming with C++. The local operator has contributed to increase the convergence rate and the rule operators have contributed to implement practical design aspects in optimization of laminated composite plates. A numerical example demonstrates the validity of optimization model and practical applicability of the improved Memetic algorithm; hence, exhibiting the improvement of the method in tackling the stacking sequence.

scholarly journals Improved Memetic Algorithm for Solving the Minimum Weight Vertex Independent Dominating Set

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1155 ◽  
Author(s):  
Yupeng Zhou ◽  
Jinshu Li ◽  
Yang Liu ◽  
Shuai Lv ◽  
Yong Lai ◽  
...  
Keyword(s):  
Dynamic Optimization ◽  
Memetic Algorithm ◽  
State Of The Art ◽  
Dominating Set ◽  
Minimum Weight ◽  
High Quality ◽  
Local Optima ◽  
Configuration Checking ◽  
Improved Memetic Algorithm ◽  
Independent Dominating Set

The minimum weight vertex independent dominating set (MWVIDS) problem is an important version of the minimum independent dominating set. The MWVIDS problem has a number of applications in many fields. However, the MWVIDS problem is known to be NP-hard and thus computationally challenging. In this work, we present the improved memetic algorithm called MSSAS for solving the MWVIDS problem. The proposed MSSAS algorithm combines probability-based dynamic optimization (PDO) (to generate good and diverse offspring solutions by assembling elements of existing good solutions) as well as a local search phase named C_LS (to seek high-quality local optima by combining the idea of constrained-based two-level configuration checking strategy and tabu mechanism). The extensive results on popular DIMACS and BHOLIB benchmarks demonstrate that MSSAS competes favorably with the state-of-the-art algorithms. In addition, we analyze the benefits of the newly raised components including two above proposed ideas with our memetic framework. It is worth mentioning that the combination of both components has excellent effects for the MWVIDS problem.

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