This paper is on practical solutions to the multi-objective optimization problem; it advocates for single-point solutions either of the Nash equilibrium or the Tchebycheff compromise type, depending on whether one can reasonably ascribe competition or cooperation to the problem at hand. A transform method that greatly simplifies implementation of the compromise solution is presented and shown to be effective. The exposition is largely couched in game-theoretic terms, and with reference to an evolutionary multi-objective solver called GENO. The paper includes five numerical examples that illustrate the ideas and issues discussed.
Siwale, I. (2013). Practical multi-objective programming. Technical Report No. RD-14-2013, London: Apex Research Ltd