RRSL Report

JMOO
1) We have a system for very easily instancing new problems, and have already implemented most baselines such as Fonseca, Srinivas, ConstrEx and more.  Capabilities can handle constrained or non-constrained problems.

Modifiable Genetic Algorithm Approach
2) A basis for a very plain and dull GA is as follows:
 - Read a 100-row dataset for the problem (so that we begin on a consistent standpoint).
 - Evaluate all of these as the initial population and record Median & IQR metrics for each objective.
 - Begin an iterative process, stopping at a given criteria (# of runs, or %change between iterations):
 - - - a: Select offspring for CM
 - - - b: Crossover for the offspring
 - - - c: Mutation for the offspring
 - - - d: Combine population with the new offspring and select a new population from these

RRSL GA
3) Different Algorithms follow from adjusting (a,b,c,d) above:
 - RRSL GA:
 - - - a: Selection of offspring via rrsl non-dominating leaves. Maintain two copies of these offspring.
 - - - b: Crossover of the offspring via moving averages idea
 - - - c: Mutation for the offspring via Differential Evolution
 - - - d: Tournament Selection on the (few) offspring + adjustedoffspring

NSGA2/SPEA2
4) Benchmark Algorithms also follow from adjusting (a,b,c,d) above:
 - NSGA2/SPEA2:
 - - - a: Selection of offspring using k-round tournament selection
 - - - b: Standard Crossover to swap attributes for a given pair of individuals
 - - - c: Standard Mutation to re-roll the dice on some individual's attribute chosen decision
 - - - d: Selection via NSGA2 or SPEA2 sub-routines.

Goals
5) The Goal of the Research:
 - We want RRSL GA to perform as well as NSGA2/SPEA2.
 - There's an argument on what it means to be better.  Solutions lie across the optimal pareto frontier, but different algorithms may discover solutions at different areas along the frontier.
 - The absolute emphasis of the research: Improving upon the number of objective function evaluations.  The theory is that RRSL GA will require log N the number of evaluations needed by NSGA2/SPEA, and still do just as well.

Results
6) Results

charts: http://unbox.org/stuff/var/joe/joe/fall2012/pom2rrslTesting/charts/1-16-2013/
--- full results pending ---