Unifying clones with a generative programming technique: a case study

2006 ◽  
Vol 18 (4) ◽  
pp. 267-292 ◽  
Author(s):  
Stan Jarzabek ◽  
Shubiao Li
Keyword(s):  
Programming Technique ◽  
Generative Programming

MDA-Based Transformation of LMS Business Components

2013 ◽  
Vol 9 (4) ◽  
pp. 63-84 ◽  
Author(s):  
Rachid Dehbi ◽  
Mohamed Talea ◽  
Abderrahim Tragha
Keyword(s):  
Complete Solution ◽  
Model Transformations ◽  
Generative Programming ◽  
System Generator ◽  
Model Driven ◽  
Business Component ◽  
Component Approach ◽  
Uml Class Diagram

The model driven engineering and generative programming are revolutionizing software development just as automation and computerization revolutionized the manufacturing process. The key technologies of these approaches are the model transformations, and development in the XML technologies. In this paper the authors show the contribution of these two techniques in the implementation of LMSGENERATOR, a Multi-target Learning management system generator with a model-driven methodology based on MDA approach coupled with component approach. Based on generative programming, from user specifications (abstract models) and the desired technologies, software bricks will be generated and assembled to produce a complete solution adapted to the area and the users’ needs. This paper focuses on the transformation rules implemented in the LMSGENERATOR cores, in particular the transformation of a detailed UML class diagram, representing a business model, into the LMS Business component. Thus, the authors show the role of programming in model transformations through the use of API manipulating UML diagrams and XML files. Also this work presents a case study to illustrate this proposed plan.

scholarly journals A Fuzzy Group Decision Making for a Rail-Road Transshipment Yard Micro Locaton Problem

2018 ◽  
Vol 235 ◽  
pp. 00019 ◽  
Author(s):  
Ivan Belošević ◽  
Sanjin Milinković ◽  
Peter Marton ◽  
Slavko Vesković ◽  
Miloš Ivić
Keyword(s):  
Decision Making ◽  
Location Problem ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Practical Importance ◽  
Multi Criteria Decision Making ◽  
Intermodal Transportation ◽  
Programming Technique ◽  
Fuzzy Group Decision Making

Rail-road transhipment yards serve as interchange points between rail and road providing transhipment of loading units. These yards are of great importance for smooth functioning not only of railways but also of the whole intermodal transportation chains. The problem of choosing location of railway facilities, such as yards and depots, has great practical importance and is widely considered in the literature. In this paper, we present a multi criteria decision making (MCMD) model for selecting the most suitable micro location of a rail-road transhipment yard. The developed MCMD model is based on combining a compromise programming technique with the theory of fuzzy numbers. This approach was chosen to solve the considered location problem due to the specific decision-making environment that reflects in the presence of non-commensurable and conflicting criteria. As a case study we analysed several alternatives for locating rail-road transhipment facilities in the area of the rail freight yard in Vršac. The results confirm validity and usefulness of this approach.

scholarly journals Optimal Coordination of Directional Overcurrent Relays Using AI Algorithms and Comparison

10.29007/t8d1 ◽  
2018 ◽  
Author(s):  
Gaurav Darji ◽  
Ajay Patel ◽  
Rashesh P. Mehta
Keyword(s):  
Fine Tuning ◽  
Convergence Time ◽  
Coordination Problem ◽  
Programming Technique ◽  
Solution Convergence ◽  
Overcurrent Relays ◽  
Optimal Coordination ◽  
Optimum Solution ◽  
Boundary Limits

For identification of fault in time, with effectiveness and also to isolate the faulted part from the system to keep away from probable outages in a power system, the precise coordination of Directional Overcurrent Relays (DOCRs) is required. The coordination of DOCRs is assessed as optimization problem with containing complex nonlinear constraints. In this paper, several nature inspired AI techniques are implemented for the optimum solution of DOCR coordination problem. Fine tuning of presented AI algorithm is done to get the optimum possible results. Also the obtained results using the proposed methods are hybridized with the nonlinear programming technique for obtaining global best solution. All four algorithms represented for a case study system are compared with each other on the basis of Fitness of solution, convergence time of an algorithm for solution and on the basis of complexities presented by them in the way of solution. The results obtained present that with fine tuning of separate algorithm and using hybridization approach leads to the optimum as well as feasible solution within the boundary limits.

DETERMINATION OF EOQ OF MULTI-ITEM INVENTORY PROBLEMS THROUGH NONLINEAR GOAL PROGRAMMING WITH PENALTY FUNCTION

2005 ◽  
Vol 22 (04) ◽  
pp. 539-553 ◽  
Author(s):  
S. PANDA ◽  
K. BANERJEE ◽  
M. BASU
Keyword(s):  
Decision Making ◽  
Goal Programming ◽  
Penalty Function ◽  
Penalty Functions ◽  
Economic Order Quantity ◽  
Programming Formulation ◽  
Order Quantity ◽  
Programming Technique

This paper proposes a nonlinear goal programming technique for obtaining economic order quantity of multi-item inventory problems. In the decision-making context, penalty functions are incorporated in the goal programming formulation. The proposed technique has been demonstrated via a case study.

Cassava Transportation Planning under Uncertain Demand Using Hybrid Algorithm: Case Study of Roi Et Province

2014 ◽  
Vol 931-932 ◽  
pp. 1658-1663
Author(s):  
Thoranin Sujjaviriyasup ◽  
Komkrit Pitiruek
Keyword(s):  
Transportation Planning ◽  
Transportation Network ◽  
Distribution Center ◽  
Average Error ◽  
Forecasting Model ◽  
Programming Technique ◽  
Optimal Value ◽  
Hybrid Forecasting ◽  
Linear Programming Technique

Cassava transportation planning usually involves unexpected demand, which may result in shortage supply. Furthermore, a distribution center at which cassava is collected is difficult to be located since the demand is unknown. In this research, hybrid forecasting model for predicting future demand in order to determine transshipment points is proposed. In addition, cluster analysis and particle swarm optimization are used for creating potential zones and determine a proper location as a new hub. Finally, the optimal value of a transportation network model using both forecasted value and actual value obtained from linear programming technique are tested and compared. The results indicate that the hybrid forecasting model provides the lowest error and forecasting value provides average error of optimal value compared to actual value by 19.81%. Moreover, zoning technique can be able to improve shipping volume fulfilled to a large truck.

scholarly journals Is water trading policy an effective solution for water allocation in Voshmgir dam?

Water Policy ◽  
2017 ◽  
Vol 19 (6) ◽  
pp. 1119-1142 ◽  
Author(s):  
Parinaz Jansouz ◽  
Javad Shahraki ◽  
Mohammad Abdolhosseini
Keyword(s):  
Water Allocation ◽  
Probability Distributions ◽  
Water Volume ◽  
Water Deficiency ◽  
Programming Technique ◽  
Trading Systems ◽  
Water Trading ◽  
Irrigated Area ◽  
Trading Policy

Abstract The aim of this study is to assess the effectiveness of water trading policy as a solution for optimal use of water between farmers in Voshmgir dam, Iran. For assessment, four villages were selected and two water allocation programs under non-trading and trading systems were designed by two-stage stochastic programming technique and uncertainties expressed as intervals and probability distributions. The results obtained from the two programs were compared based on water volume which is released through trading and decrease in water deficiency as effectiveness indices. The results show that the water allocation under trading policy has changed so that it has led to released water and decrease in water deficiency by keeping the agricultural profit under non-trading, but irrigated area is decreased under trading. Generally, trading policy can lead to more effective allocation from the view of released water and decrease in water deficiency, but it can remove some farmers from agricultural activities by decreasing the irrigated area. As a result, trading policy can be effective in the short term especially in drought conditions due to insufficient water supply and can be unnecessary in normal and wet years in this case study.

scholarly journals Operational Risk of Insecurity using Control Self Risk Assessment and Linear Programming

2018 ◽  
Author(s):  
Monday Osagie Adenomon ◽  
Ezekiel Awhigbo Bulus
Keyword(s):  
Risk Assessment ◽  
Linear Programming ◽  
Research Work ◽  
Modern Technology ◽  
Risk Level ◽  
Programming Technique ◽  
Security Personnel ◽  
Religious Crisis ◽  
Linear Programming Technique

This research work focused on the risks we are faced with on our day to day activities, either directly or indirectly, which can gradually accumulates and results to communal crisis, religious crisis, socio-economic agitations and tribal crises. Nasarawa Eggon Local Government Area of Nasarawa State was used as case study and a well structure close–ended questionnaire was used for data collection as it relates to Controlled Self Risk Assessment (CSRA) and linear programming technique was used to analyze. The results proved that many of this processes were neglected in these communities, making them to be prone to incessant communal crisis. The study recommend that Government should strongly, as a matter of urgency address the unemployment rate, distribution of political position, schools, primary health care and equip security personnel with the modern technology facilities, which happen to record the highest risk level.

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