MOMACCO: Multi-Objective Memetic-Ant-Colony-Constrained-​Optimization.

 

MOMACCO combine an Ant Colony Optimization Heuristic with the non dominated sorting strategy of NSGA-II proposed in [1].

MOMACCO software solves both constrained and unconstrained multi-objective optimization problems in the form:

 

 

 

 

 

 

 

 

 

MOMACCO finds non-dominated solutions; the set of returned solutions is a local pareto front.

The final pareto front is further optimized with a non-monotone local search algotihm. Each solution of the pareto front is optimized by using an epsilon-constrained multi-objective method; a non-monotone sequential quadratic programming algorithm [2].                          

 

References:

[1] "Pareto Optimal Reconfiguration of Power Distribution Systems Using

    a Genetic Algorithm Based on NSGA-II". Tomoiaga, B.; Chindris, M.; 

    Sumper, A.; Sudria-Andreu, A.; Villafafila-Robles, R. -  

    Energies 2013, 6, 1439-1455.

[2] "A non-monotone trust region algorithm for nonlinear optimization 

    subject to general constraints", Hongchao Zhang.