This problem is magnified when applied to many-objective optimisation, as care is needed to ensure that the final population of candidate solutions is representative of the trade-off surface.
Local search is an integral part of many meta-heuristic strategies that solve single objective optimisation problems.
Moreover, many evolutionary multi-objective optimisation (EMO) techniques are also available in the literature to help GP design effective heuristics to deal with multiple conflicting objectives.
Sinha et al. (2015) used Taguchi method for single objective optimisation and then the signal-to-noise (S/N) ratios obtained from Taguchi method have been further used in principal component analysis (PCA) for multi-objective optimisation.
This methodology is able to handle multiple objective optimisation problems in the area of ship design, where the simultaneous optimisation of several conflicting objectives is considered.
The optimization problem can consider many objectives.
Building design can be considered as a multi-objective optimisation problem, in which many criteria are considered for determining the most favourable solution.
While there have been many adaptations of some of the more popular meta-heuristics for continuous multi-objective optimisation problems, Tabu Search has received relatively little attention, despite its suitability and effectiveness on a number of real-world design optimisation problems.
5. Multi-objective optimisation (using game theory) Cooperative game; non-cooperative game; Nash bargaining (Pareto optimisation); Stackelberg game.
This paper develops a particle swarm optimisation (PSO) based framework for multi-objective optimisation (MOO).
These two optimisation problems can be also integrated and treated as a multi-objective optimisation problem.
