OPTIMAL TESTING RESOURCE ALLOCATION FOR MODULAR SOFTWARE CONSIDERING COST, TESTING EFFORT AND RELIABILITY USING GENETIC ALGORITHM

2009 ◽  
Vol 16 (06) ◽  
pp. 495-508 ◽  
Author(s):  
P. K. KAPUR ◽  
ANU. G. AGGARWAL ◽  
KANICA KAPOOR ◽  
GURJEET KAUR
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Software Development ◽  
Large Scale ◽  
Optimization Problems ◽  
Low Cost ◽  
Computer Software ◽  
Critical Issue ◽  
Software Systems ◽  
The Cost

The demand for complex and large-scale software systems is increasing rapidly. Therefore, the development of high-quality, reliable and low cost computer software has become critical issue in the enormous worldwide computer technology market. For developing these large and complex software small and independent modules are integrated which are tested independently during module testing phase of software development. In the process, testing resources such as time, testing personnel etc. are used. These resources are not infinitely large. Consequently, it is an important matter for the project manager to allocate these limited resources among the modules optimally during the testing process. Another major concern in software development is the cost. It is in fact, profit to the management if the cost of the software is less while meeting the costumer requirements. In this paper, we investigate an optimal resource allocation problem of minimizing the cost of software testing under limited amount of available resources, given a reliability constraint. To solve the optimization problem we present genetic algorithm which stands up as a powerful tool for solving search and optimization problems. The key objective of using genetic algorithm in the field of software reliability is its capability to give optimal results through learning from historical data. One numerical example has been discussed to illustrate the applicability of the approach.

scholarly journals Modelling key market impacts and land allocation for biofuel production and forestry

2006 ◽  
Vol 2006 ◽  
pp. 1-12
Author(s):  
A. Korobeinikov ◽  
P. Read ◽  
A. Parshotam ◽  
J. Lermit
Keyword(s):  
Carbon Dioxide ◽  
Atmospheric Carbon Dioxide ◽  
Large Scale ◽  
Low Cost ◽  
Wood Products ◽  
Biofuel Production ◽  
Fuel Wood ◽  
Carbon Dioxide Levels ◽  
The Cost ◽  
The Impact

It has been suggested that the large scale use of biofuel, that is, fuel derived from biological materials, especially in combination with reforestation of large areas, can lead to a low-cost reduction of atmospheric carbon dioxide levels. In this paper, a model of three markets: fuel, wood products, and land are considered with the aim of evaluating the impact of large scale biofuel production and forestry on these markets, and to estimate the cost of a policy aimed at the reduction of carbon dioxide in the atmosphere. It is shown that the costs are lower than had been previously expected.

scholarly journals Research on Service-Oriented Software Systems and Computer Software and Intelligent Calculation Method

2021 ◽  
Vol 2083 (3) ◽  
pp. 032095
Author(s):  
Zhimin Ni ◽  
Fan Zhao
Keyword(s):  
Software Development ◽  
Calculation Method ◽  
Computer Software ◽  
Technical Support ◽  
Software Systems ◽  
Timely Manner ◽  
Software Failure ◽  
Business Software ◽  
Service Oriented ◽  
Software Business

Abstract For the existing service-oriented software single, favors business processing, cannot guarantee the software business processing into the development of software. When the operator encounters operational problems, software failure problems and other problems related to software operation and operation, software development technicians to provide technical support to ensure the software’s business processing functions. This study will move away from dependence on other software and provide technical support to business software operators accurately and in a timely manner to effectively solve the problems that operators may encounter.

Genetic Algorithm and Other Meta-Heuristics

2005 ◽  
pp. 144-173 ◽  
Author(s):  
Bernard K.S. Cheung
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Schema Theory ◽  
Heuristic Methods ◽  
Optimal Solutions ◽  
Corporate Globalization ◽  
Global Optimal ◽  
Mutation And Selection

Genetic algorithms have been applied in solving various types of large-scale, NP-hard optimization problems. Many researchers have been investigating its global convergence properties using Schema Theory, Markov Chain, etc. A more realistic approach, however, is to estimate the probability of success in finding the global optimal solution within a prescribed number of generations under some function landscapes. Further investigation reveals that its inherent weaknesses that affect its performance can be remedied, while its efficiency can be significantly enhanced through the design of an adaptive scheme that integrates the crossover, mutation and selection operations. The advance of Information Technology and the extensive corporate globalization create great challenges for the solution of modern supply chain models that become more and more complex and size formidable. Meta-heuristic methods have to be employed to obtain near optimal solutions. Recently, a genetic algorithm has been reported to solve these problems satisfactorily and there are reasons for this.

scholarly journals A GPU-Enabled Compact Genetic Algorithm for Very Large-Scale Optimization Problems

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 758
Author(s):  
Andrea Ferigo ◽  
Giovanni Iacca
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Optimization Problems ◽  
Search Space ◽  
Large Scale Problems ◽  
Processing Power ◽  
Compact Genetic Algorithm ◽  
Estimation Of Distribution ◽  
Feasible Solutions ◽  
Compact Optimization

The ever-increasing complexity of industrial and engineering problems poses nowadays a number of optimization problems characterized by thousands, if not millions, of variables. For instance, very large-scale problems can be found in chemical and material engineering, networked systems, logistics and scheduling. Recently, Deb and Myburgh proposed an evolutionary algorithm capable of handling a scheduling optimization problem with a staggering number of variables: one billion. However, one important limitation of this algorithm is its memory consumption, which is in the order of 120 GB. Here, we follow up on this research by applying to the same problem a GPU-enabled “compact” Genetic Algorithm, i.e., an Estimation of Distribution Algorithm that instead of using an actual population of candidate solutions only requires and adapts a probabilistic model of their distribution in the search space. We also introduce a smart initialization technique and custom operators to guide the search towards feasible solutions. Leveraging the compact optimization concept, we show how such an algorithm can optimize efficiently very large-scale problems with millions of variables, with limited memory and processing power. To complete our analysis, we report the results of the algorithm on very large-scale instances of the OneMax problem.

scholarly journals Hierarchical System Decomposition Using Genetic Algorithm for Future Sustainable Computing

2020 ◽  
Vol 12 (6) ◽  
pp. 2177
Author(s):  
Jun-Ho Huh ◽  
Jimin Hwa ◽  
Yeong-Seok Seo
Keyword(s):  
Genetic Algorithm ◽  
Software Architecture ◽  
Large Scale ◽  
Structural Characteristics ◽  
Optimal Solution ◽  
Hill Climbing ◽  
Software Systems ◽  
Small Scale ◽  
Hill Climbing Algorithm ◽  
Architecture Management

A Hierarchical Subsystem Decomposition (HSD) is of great help in understanding large-scale software systems from the software architecture level. However, due to the lack of software architecture management, HSD documentations are often outdated, or they disappear in the course of repeated changes of a software system. Thus, in this paper, we propose a new approach for recovering HSD according to the intended design criteria based on a genetic algorithm to find an optimal solution. Experiments are performed to evaluate the proposed approach using two open source software systems with the 14 fitness functions of the genetic algorithm (GA). The HSDs recovered by our approach have different structural characteristics according to objectives. In the analysis on our GA operators, crossover contributes to a relatively large improvement in the early phase of a search. Mutation renders small-scale improvement in the whole search. Our GA is compared with a Hill-Climbing algorithm (HC) implemented by our GA operators. Although it is still in the primitive stage, our GA leads to higher-quality HSDs than HC. The experimental results indicate that the proposed approach delivers better performance than the existing approach.

Performance and Isotherm Studies in Phenol Adsorption From Wastewater Using Low Cost Biomass Derived From Coconut Shells

2019 ◽  
Vol 8 (2) ◽  
pp. 23-37
Author(s):  
Mohan Rao T. ◽  
K. Rajesh Kumar ◽  
G. Shyamala ◽  
R. Gobinath
Keyword(s):  
Activated Carbon ◽  
Large Scale ◽  
Low Cost ◽  
Batch Adsorption ◽  
Phenol Removal ◽  
Waste Biomass ◽  
Textile Processing ◽  
Leather Processing ◽  
Coconut Shells ◽  
The Cost

With the growth of urbanization and industrialization, water bodies are getting polluted. Among various pollutants, phenol-based pollutants are common water pollutions which originate from wastewater discharged from processing manufacturing industries like petrochemical refineries, ceramic plants, textile processing, leather processing, synthetic rubbers, etc. These pollutants are toxic and have long-term ill effects on both humans and aquatic animals. Adsorption is well proven technique which is widely used for removal of pollutions from aqueous environments. But this process, is hindered due to the cost of adsorbents especially for large scale continuous processes. In this regard, adsorbents derived from waste biomass can be a great asset to reduce the cost of wastewater treatment. To meet this objective, coconut shells are chosen as biomass which is abundantly available from south east Asia. This biomass is converted into activated carbon and hence used to remove phenol from wastewater. Batch adsorption experiments were performed with different initial concentration, carbon dosage, pH and contact time. At a lower concentration of 50 mg/L of initial feed (phenol) concentration resulted in around 90% phenol removal and henceforth optimum results in phenol removal obtained in only 64%. Experimental results are in good agreement with Langmuir adsorption isotherm model and have shown a better fitting to the experimental data. These studies confirm that the coconut shell-based activated carbon could be used to effectively adsorb phenol from aqueous solutions.

scholarly journals Software Tools for Engineering Dark Skies

1991 ◽  
Vol 112 ◽  
pp. 71-76
Author(s):  
A. M. Smith ◽  
D. L. Dilaura
Keyword(s):  
Applied Mathematics ◽  
Computer Software ◽  
Principal Component ◽  
Software Systems ◽  
Atmospheric Scattering ◽  
Recent Developments ◽  
Proper Design ◽  
Lighting Systems ◽  
The Cost ◽  
Optical Astronomy

ABSTRACTAtmospheric scattering of outdoor nighttime electric illumination produces the principal component of background sky luminance that seriously affects ground-based optical astronomy. The sources for this scattering are Tight emitted skyward directly from luminaires, and light reflected off the ground and other illuminated objects. Careful illumination engineering can thus significantly reduce background sky luminance in two ways: 1) by providing outdoor electric lighting equipment that controls the directions in which light is emitted, and; 2) by proper design of outdoor lighting systems which make efficient use of the east amount of light. Recent developments in applied mathematics and computer software have produced computational tools that are being used to design lighting equipment and lighting systems. The software system for luminaire design significantly reduces the cost of this process by eliminating the need for extensive prototyping and provides for inexpensive experimentation with new designs. The system for outdoor lighting calculations permits the design of highly controlled lighting systems that eliminate glare and upward directed light while providing light appropriate for the visual task. These two software systems are described, along with examples of their use in areas that directly affect astronomical observations.

Low-cost manufacturing process for nanostructured metals and alloys

2002 ◽  
Vol 17 (10) ◽  
pp. 2484-2488 ◽  
Author(s):  
Travis L. Brown ◽  
Srinivasan Swaminathan ◽  
Srinivasan Chandrasekar ◽  
W. Dale Compton ◽  
Alexander H. King ◽  
...  
Keyword(s):  
Nanostructured Materials ◽  
Manufacturing Process ◽  
Large Scale ◽  
Bulk Material ◽  
Low Cost ◽  
Limited Range ◽  
Pure Metals ◽  
The Cost ◽  
Machining Operations ◽  
Low Cost Manufacturing

In spite of their interesting properties, nanostructured materials have found limited uses because of the cost of preparation and the limited range of materials that can be synthesized. It has been shown that most of these limitations can be overcome by subjecting a material to large-scale deformation, as occurs during common machining operations. The chips produced during lathe machining of a variety of pure metals, steels, and other alloys are shown to be nanostructured with grain (crystal) sizes between 100 and 800 nm. The hardness of the chips is found to be significantly greater than that of the bulk material.

Improved Genetic Algorithms Based Optimal Design of The Shuangji River Aqueduct

2011 ◽  
Vol 201-203 ◽  
pp. 1288-1291
Author(s):  
Xin Li Bai ◽  
Wei Yu ◽  
Dan Fei Wang ◽  
Yuan Yuan Fan
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Structural Optimization ◽  
Large Scale ◽  
Hybrid Genetic Algorithm ◽  
Computer Software ◽  
Search Method ◽  
Discrete Variables ◽  
Original Design ◽  
Design Plan

The simple genetic algorithm (SGA) is taken as the global search method, and the traditional direct search method for mixed-discrete variables as the local search method. The improved (hybrid) genetic algorithm (IGA) is obtained by improving the SGA. And through the introduction of penalty constraints, the problem dealing with the constraints in GA is successfully resolved. A mathematical model for structural optimization of aqueduct is established, and computer software is developed for structural optimization of large-scale aqueduct based on IGA. Using this program, the Shuangji River aqueduct is optimized and Rectangle-sectioned aqueduct design plan is obtained. Compared with the original design plan, optimal design is very economical and was adopted by Design Institute.

Sign in / Sign up

Export Citation Format

Share Document