scholarly journals Metaheuristic Design Pattern: Visitor for Genetic Operators

2016 ◽  
Author(s):  
Giovani Guizzo ◽  
Silvia R. Vergilio
Keyword(s):  
Design Pattern ◽  
Genetic Operators

ANALYZING AND IMPROVING WEB APPLICATION QUALITY USING DESIGN PATTERNS

2012 ◽  
Vol 2 (2) ◽  
pp. 112-116
Author(s):  
Shikha Bhatia ◽  
Mr. Harshpreet Singh
Keyword(s):  
Web Application ◽  
Design Pattern ◽  
Design Patterns ◽  
Web Applications ◽  
Past Research ◽  
Software Systems ◽  
Interactive Software ◽  
Web Based ◽  
Software Application ◽  
Execution Speed

With the mounting demand of web applications, a number of issues allied to its quality have came in existence. In the meadow of web applications, it is very thorny to develop high quality web applications. A design pattern is a general repeatable solution to a generally stirring problem in software design. It should be noted that design pattern is not a finished product that can be directly transformed into source code. Rather design pattern is a depiction or template that describes how to find solution of a problem that can be used in many different situations. Past research has shown that design patterns greatly improved the execution speed of a software application. Design pattern are classified as creational design patterns, structural design pattern, behavioral design pattern, etc. MVC design pattern is very productive for architecting interactive software systems and web applications. This design pattern is partition-independent, because it is expressed in terms of an interactive application running in a single address space. We will design and analyze an algorithm by using MVC approach to improve the performance of web based application. The objective of our study will be to reduce one of the major object oriented features i.e. coupling between model and view segments of web based application. The implementation for the same will be done in by using .NET framework.

A multi-objective sparse evolutionary framework for large-scale weapon target assignment based on a reward strategy

2021 ◽  
Vol 40 (5) ◽  
pp. 10043-10061
Author(s):  
Xiaoping Shi ◽  
Shiqi Zou ◽  
Shenmin Song ◽  
Rui Guo
Keyword(s):  
Large Scale ◽  
The Novel ◽  
Genetic Operators ◽  
Multi Objective ◽  
Target Assignment ◽  
Solution Selection ◽  
Battlefield Environment ◽  
Sparse Problems ◽  
Novel Model ◽  
Error Parameter

 The asset-based weapon target assignment (ABWTA) problem is one of the important branches of the weapon target assignment (WTA) problem. Due to the current large-scale battlefield environment, the ABWTA problem is a multi-objective optimization problem (MOP) with strong constraints, large-scale and sparse properties. The novel model of the ABWTA problem with the operation error parameter is established. An evolutionary algorithm for large-scale sparse problems (SparseEA) is introduced as the main framework for solving large-scale sparse ABWTA problem. The proposed framework (SparseEA-ABWTA) mainly addresses the issue that problem-specific initialization method and genetic operators with a reward strategy can generate solutions efficiently considering the sparsity of variables and an improved non-dominated solution selection method is presented to handle the constraints. Under the premise of constructing large-scale cases by the specific case generator, two numerical experiments on four outstanding multi-objective evolutionary algorithms (MOEAs) show Runtime of SparseEA-ABWTA is faster nearly 50% than others under the same convergence and the gap between MOEAs improved by the mechanism of SparseEA-ABWTA and SparseEA-ABWTA is reduced to nearly 20% in the convergence and distribution.

Minimization of total trim loss occurring in pipe cutting in shipbuilding with genetic algorithm

2021 ◽  
pp. 147509022199169
Author(s):  
Abdullah Türk ◽  
Dursun Saral ◽  
Murat Özkök ◽  
Ercan Köse
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Search Space ◽  
Cutting Process ◽  
Genetic Operators ◽  
Critical Stage ◽  
Different Types ◽  
Trim Loss ◽  
Pipe Systems

Outfitting is a critical stage in the shipbuilding process. Within the outfitting, the construction of pipe systems is a phase that has a significant effect on time and cost. While cutting the pipes required for the pipe systems in shipyards, the cutting process is usually performed randomly. This can result in large amounts of trim losses. In this paper, we present an approach to minimize these losses. With the proposed method it is aimed to base the pipe cutting process on a specific systematic. To solve this problem, Genetic Algorithms (GA), which gives successful results in solving many problems in the literature, have been used. Different types of genetic operators have been used to investigate the search space of the problem well. The results obtained have proven the effectiveness of the proposed approach.

A Study on Sun Shading Reconstruction Design of Residential Buildings in Chongqing City

2014 ◽  
Vol 953-954 ◽  
pp. 1481-1487
Author(s):  
Liu Jin
Keyword(s):  
Energy Saving ◽  
Personal Experience ◽  
Design Pattern ◽  
Simulation Analysis ◽  
Residential Buildings ◽  
Residential Building ◽  
Specific Time ◽  
High Rise ◽  
Time Period ◽  
Chongqing City

Windows energy saving design of residential buildings has increasingly got the attention of people. Through a large number of surveys and analysis of residential buildings in Chongqing and consumers personal experience, the author finds problems and deficiency, and then proposes principles of residential buildings sun shading reconstruction in Chongqing city. Taking the high-rise residential building of one university in Chongqing as reconstruction sample, selecting a specific time period, the author recalculates sun shading coefficient with and without sun shading by using Ecotect software to do simulation analysis. Finally, the reasonable reconstruction design pattern is put forward through cases. Keywords: Buildings Sun Shading, Sun Shading Reconstruction, Energy Saving

ONE IMPROVED AGENT GENETIC ALGORITHM — RING-LIKE AGENT GENETIC ALGORITHM FOR GLOBAL NUMERICAL OPTIMIZATION

2009 ◽  
Vol 26 (04) ◽  
pp. 479-502 ◽  
Author(s):  
BIN LIU ◽  
TEQI DUAN ◽  
YONGMING LI
Keyword(s):  
Genetic Algorithm ◽  
Numerical Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Genetic Operators ◽  
Global Numerical Optimization ◽  
Candidate Solution ◽  
Low Dimension ◽  
Multi Agent ◽  
Agent Structure

In this paper, a novel genetic algorithm — dynamic ring-like agent genetic algorithm (RAGA) is proposed for solving global numerical optimization problem. The RAGA combines the ring-like agent structure and dynamic neighboring genetic operators together to get better optimization capability. An agent in ring-like agent structure represents a candidate solution to the optimization problem. Any agent interacts with neighboring agents to evolve. With dynamic neighboring genetic operators, they compete and cooperate with their neighbors, and they can also use knowledge to increase energies. Global numerical optimization problems are the most important ones to verify the performance of evolutionary algorithm, especially of genetic algorithm and are mostly of interest to the corresponding researchers. In the corresponding experiments, several complex benchmark functions were used for optimization, several popular GAs were used for comparison. In order to better compare two agents GAs (MAGA: multi-agent genetic algorithm and RAGA), the several dimensional experiments (from low dimension to high dimension) were done. These experimental results show that RAGA not only is suitable for optimization problems, but also has more precise and more stable optimization results.

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