The cooperative group optimization (CGO) system consists of a group of intelligent agents cooperating with their peers in a sharing environment for realizing a common intention of finding high-quality solution(s) based on the landscape representation of an optimization task.


Numerical Optimization

CGO has also been applied on numerical optimization problem (NOP) to find solutions in high-dimensional nonlinear continuous space. Some algorithms, including Dissipative Particle Swarm Optimization (DPSO), Differential Evolution (DE), Social Cognitive Optimization (SCO), Genetic Algorithms (GA), and Electromagnetism-like Mechanism (EM) Heuristic, etc, and their hybrids (e.g., DEPSO), could be easily implemented into CGO.

Both SCO and DEPSO have been incorporated into the NLPSolver extension of Calc in Apache Office. DEPSO was used for finding narrow admissible k-tuples.

Combinatorial Optimization

CGO can also been applied on some combinatorial optimization problems, such as Travelling Salesman Problem (TSP), Graph Coloring Problem (GCP), Quadratic Knapsack Problem (QKP), Flow-Shop Scheduling Problem (FSP), Quadratic Assignment Problem (QAP), etc, by combining with low-level Metaheuristic Local Search techniques.