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In many engineering disciplines we need to find solutions in the presence of conflicting objectives. In such cases, solutions are chosen such that there are reasonable trade-offs among different objectives. Pareto search is an approach for handling such situations. Instead of generating a single optimal solution, many solutions are generated that satisfy Pareto Optimality Criterion. According to this criterion, a solution point P is accepted only if there are no solutions better than P with respect to all the objectives. For example, even if P is worse than another solution P1 with respect to one objective, P is accepted provided that it is better than P1 in at least one objective. Thus each Pareto optimal solution is good in some respect. The set of all Pareto optimal solutions form a surface known as a Pareto front. The Pareto front helps engineers understand the nature of trade-offs that need to be made in order to select good solutions. Visualizing the front helps engineers make good decisions.
Many techniques for generating the Pareto front are found in the literature. These include special versions of genetic algorithms and simulated annealing. Another option is to use Pareto PGSL, a multi-objective version of my PGSL algorithm. If you are interested, please contact me.
Useful links:
RRPExplorer - The multi-criteria decision making tool that I have developed.
PGSL - My global optimization algorithm.
Fundamentals of Computer Aided Engineering (John Wiley). My book that contains a description of Pareto optimization.