Multiobjective Search/Optimization (MOO)

• Multi-objective evolutionary algorithms

• Multi-objective meta-heuristics (scatter and Tabu search)

• Multi-objective article swarm optimization

• Multi-objective ant colonies, bacteria optimization, and other heuristic search methods

• Handling a large number of objectives

• Handling large-scale multi-objective problems

Multiobjective Machine Learning (MOML)

• Accuracy and complexity trade-off

• Accuracy-interpretability, stability-plasticity dilemma

• Pareto-based ensemble generation

• Pareto-analysis of learning systems

Decision Making (DM) Techniques

• Preference elicitation and representation

• Aggregation/trade-off operators & algorithms

• Fuzzy logic based DM techniques

• Bayesian and other DM techniques

Interactive Visualization (IV)

• Progressive aggregation methods

• Decision maker in the loop

Integration of MOO, ML, DM, and IV to support Multicriteria Decision Making