Packaging Geometric measures to check requirements Occupant model Inputs Shoulder room, knee room etc Roominess measure GM RD Trunk∨oume

The experience of the 1960s has shown that for military aircraft the cost of the final increment of performance usually is excessive in terms of other characteristics and that the overall system must be optimized, not just performance Ref: Current State of the art of Multidisciplinary design Optimization

Why multiobjective optimization? Example-twin peaks optimization History of multiobjective optimization Weighted Sum Approach(Convex Combination) Dominance and Pareto-Optimality Pareto Front Computation -nBl o Massachusetts Institute of Technology-Prof de Weck and Prof Willcox Engineering Systems Division and Dept of Aeronautics and Astronautics

Multidisciplinary System Optimality Conditions & Termination Design Optimization(MSDO) Gradient-based techniques Post-Optimality Analysis Heuristic techniques

Alternatives to Weighted Sum(WS)Approach Multiobjective Heuristic Programming Utility Function Optimization Physical Programming(Prof. Messac) Application to Space System Optimization Lab Preview(Friday 4-9-2003-Section 1) Massachusetts Institute of Technology-prof. de Weck and Prof. Willcox Engineering Systems Division and Dept of Aeronautics and Astronautics

Mlesd Particle Swarm Optimization 5. 9 A pseudo-optimization method (heuristic) inspired by the collective intelligence of swarms of biological populations Flocks of birds Colonies of insects C Rania Hassan 3/2004 Engineering Systems Division -Massachusetts Institute of Technology

Outline Heuristics Background in Statistical Mechanics -Atom Configuration Problem Metropolis Algorithm Simulated Annealing algorithm Sample Problems and Applications · Summary

What are heuristics The Origin and Analogy of Simulated Annealing The Simulated Annealing algorithm An Example: The Terrestrial Planet Finder Mission Sample results Ways to Tailor the simulated Algorithm Summary References O Massachusetts Institute of Technology- Dr. Cyrus D Jilla& Prof. Olivier de Weck ngineering Systems Division and Dept of Aeronautics Astronautics

This 90 minutes lecture to be delivered via telelink addresses a class of MIT undergraduates unrolled in Engineering Design and Rapid Prototyping Course. The students have been introduced to the basic optimization concepts of design variables, design space, objective function

More on Fitness Function Assignment Mutation Constraint implementation in Gas Multiobjective optimization with Gas Tabu search Selection of Optimization algorithms o Massachusetts Institute of Technology -Prof de Weck and Prof Willcox Engineering Systems Division and Dept of Aeronautics and Astronautics