Theoretical developments

Recent developments in GP

MO Exact solution methods

MO Hybrid/Parallel metaheuristics

Dynamic/Hierarchical GP

Constraints programming

Interactive methods

Preference based methods

Population based algorithms

Local search based algorithms

Fuzzy and stochastic programming

Multilevel linear programming

Discrete / Continuous optimization

Application areas

Planning and scheduling
Logistic and routing problems
Time tabling
Cutting problem
Knapsack problem
Portfolio optimization
Set covering / clustering / packing
Datamining
Health and environment
Bioinformatics
Business applications ( Finance,
management , marketing)