Aiming at the problem that unreasonable distribution between weight vector and individual in MOEA/D reduce diversity

the

constrained multi-objective decomposition optimization algorithm based on re-matching strategy is proposed.Firstly

through theoretical analysis of the chebycheff decomposition strategy

two theorems about diversity and convergence are gained

which could provide a theoretical basis for the research of MOEA/D.Secondly

in order to solve the problem of diversity reduction caused by random assignment of individual to weight vector

the re-matching strategy is presented for reasonably assigning individual to weight vector

and then diversity is impr

oved.Finally

the suggested individual comparison criterion has a good balance between diversity and convergence

and it increases optimization performance.Comparative experiment results with five excellent algorithms show that our algorithm achieves better diversity and convergence

and our algorithm has a certain advantage.