There are many multi objective optimization algorithms such as NSGA II, MOEA, VEGA etc. You can find the code of NSGA II on the following link:

http://www.mathworks.com/matlabcentral/fileexchange/10429-nsga-ii--a-multi-objective-optimization-algorithm

There is a book on multi objective optimization by Kalyanmoy Deb, a mechanical engineer. Th information of that book is available at

http://as.wiley.com/WileyCDA/WileyTitle/productCd-047187339X.html

Other codes are also available on net.

Thanks Rajesh.

I have used Dr. Deb's algorithms on MOO. What I am primarily looking for is some prior work or literature in the vehicle architecture optimization domain. Also an effective algorithm based on experience to solve these problems by using methods like MOGA or the one's suggested by you.

I am looking for specific information related to the architecture optimization.

This is an interesting topic. Vehicle architecture is influenced by several, partially conflicting factors, e.g. vehicle type and size, ergonomic aspects, legislative boundary conditions, drivetrain and energy storage technology, materials. Thus the optimization problem is multi-dimensional and rather complex. In automotive industry, this optimizaiton is done by experts, supported by different simulation tools.

One approach to integrate the conflicting aspects into one virtual vehicle model has been developed in the course of a reserach project in co-operation with a large car manufacturer (see the attachted publication). The idea was to create a variable vehicle architecture model within a CAD environment and to add some calculation modules, e.g. for drivetrain layout and fuel (energy) consumption simulation.

Kind regards,

Mario

NSGA II can be very effective for the problem mentioned. Also, any heuristic algorithm, like PSO, DE, HS etc., can easily be tuned to solve any multiobjective optimization problem.

Think to use M.O. Simulating Annealing or also Tabu Search hybridized with Simulating Annealing.

http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5939419&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F5920928%2F5939294%2F05939419.pdf%3Farnumber%3D5939419

Conference Paper A hybrid approach based on Multi-Objective Simulated Anneali...

Thanks a lot for the suggestions.

The architecture model is a simulation model developed in AMSIM and what we are trying to do is use an optimization algorithm to optimize the outer loop.

At this point of time we are not focused on optimizing the inner loop.

For optimizing the outer loop, I recommend to define an overall approach, considering the main influencing parameters, e.g. drive train characteristics including efficiency chain, vehicle mass and acceleration behavior (translatory and rotory inertia), air drag, rolling resistances, etc. The optimization is a multidisciplinary type with interacting influences. For evaluation, pareto-type diagrams in combination with look-up tables can be applied. 

Kind regards,

Mario

 Thanks a lot Mario Hirz.  

I am primarily looking at many conflicting parameters like fuel efficiency, vehicle mass systems and other dynamic characteristics

Any literature or presentation to help me with this would be highly appreciated. 

Thanks and Regards, 

Amit 

Here is some literature:

- vehicle dynamics simulation, including fuel consumption estimation (With this method, you can create a simulation model, e.g. in MATLAB SIMULINK): https://www.researchgate.net/publication/280303367_Basics_of_longitudinal_vehicle_dynamics?ev=prf_pub

- a publication which is more related to vehicle architecture, but shows an approach for multidisciplinary optimization (attached)

- In addition, there is commercial software available, which supports longitudinal vehicle simulation, including fuel efficiency, e.g. IPG (http://ipg.de/de/simulationsolutions/carmaker/), AVL Cruise (https://www.avl.com/de/cruise).

Kind regards,

Mario

Conference Paper Basics of longitudinal vehicle dynamics