Application of Hybrid Optimization Algorithm to Automotive Design Problems and Performance Comparison with Other Standard Optimizers

2015 ◽  
Author(s):  
Adarsh Viji Elango ◽  
Apurva Gokhale ◽  
Sumeet Parashar
2017 ◽  
Vol 23 (6) ◽  
pp. 1947-1964
Author(s):  
Ibrahima Diarrassouba ◽  
Mohamed Khalil Labidi ◽  
A. Ridha Mahjoub

Author(s):  
Dinesh Kumar, Dr Sunil Kumar

Distributed computing is the most recent developing pattern in disseminated processing that conveys equipment framework and programming applications as administrations. The clients can devour these administrations dependent on a SLA which characterizes their required QoS parameters. By using the cloud computing technique it is possible to reduce the investment on various resources like computer hardware and software. The application or processes that are hosted and executed using clouds consist of set of tasks and it is considered that this task will form the workflow. Therefore scheduling the task is considered as a major issue as resource usage has to be maximized without affecting the services that are facilitated by the cloud. In order to execute different virtual machine application of the tasks are assigned and it is termed as enterprise arranging. In the scheduling process the inter-dependent tasks are mapped and managed in the distributed resources. For additional improvement, this paper proposes a hybrid optimization algorithm for workflow scheduling (HOWS) in cloud environment. In the proposed algorithm the first contribution is the bees mating optimization (BMO) algorithm used to share physical infrastructure to enable multiple service providers to optimize scheduling. The second contribution in the proposed algorithm is the bacterial evolutionary algorithm used to flexible access of the resources in order to optimize the network resources. By combining the hybrid optimization algorithm provides the better improvement in terms of task scheduling and optimal resource allocation. The result and performance analysis shows that the proposed technique performs very efficient in terms of energy efficiency and scalability without compromising security. The performance is obtained using cloudSim tool


2002 ◽  
Vol 124 (2) ◽  
pp. 278-285 ◽  
Author(s):  
Gang Liu ◽  
Zhongqin Lin ◽  
Youxia Bao

In the tooling design of autobody cover panels, design of drawbead will affect the distribution of drawing restraining force along mouth of dies and the relative flowing velocity of the blank, and consequently, will affect the distributions of strain and thickness in a formed part. Therefore, reasonable design of drawbead is the key point of cover panels’ forming quality. An optimization design method of drawbead, using one improved hybrid optimization algorithm combined with FEM software, is proposed in this paper. First, we used this method to design the distribution of drawbead restraining force along the mouth of a die, then the actual type and geometrical parameters of drawbead could be obtained according to an improved drawbead restraining force model and the improved hybrid optimization algorithm. This optimization method of drawbead was used in designing drawing tools of an actual autobody cover panel, and an optimized drawbead design plan has been obtained, by which deformation redundancy was increased from 0% under uniform drawbead control to 10%. Plastic strain of all area of formed part was larger than 2% and the minimum flange width was larger than 10 mm. Therefore, not only better formability and high dent resistance were obtained, but also fine cutting contour line and high assembly quality could be obtained. An actual drawing part has been formed using the optimized drawbead, and the experimental results were compared with the simulating results in order to verify the validity of the optimized design plan. Good agreement of thickness on critical areas between experimental results and simulation results proves that the optimization design method of drawbead could be successfully applied in designing actual tools of autobody cover panels.


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