Scalarization allows to solve a multi-objective optimization problem by solving many single-objective sub-problems, uniquely determined some parameters. In this work, several adaptive strategies select such parameters are proposed in order obtain uniform approximation of the Pareto front. This is done introducing heuristic dynamics where interact through binary repulsive potential. The approach...

Abstract Many real-world problems can be naturally formulated as discrete multi-objective optimisation (DMOO) problems. We have proposed a novel Physarum-inspired competition algorithm (PCA) to tackle these DMOO Our is based on hexagonal cellular automata (CA) representation of problem search space and reaction–diffusion systems that control the Physarum motility. Physarum’s decision-making pow...

This paper deals with multi- objective nonlinear programming problem having rough intervals in the constraints. The problem is approached by taking maximum value range and minimum value range inequalities as constraints conditions, reduces it into two classical multi-objective nonlinear programming problems, called lower and upper approximation problems.  All of the lower and upper approximatio...

This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial problems viz. assignment problem, allocation travelling salesman vehicle routing scheduling and knapsack problem. It is identified that based on manner in which has been implemented solving aforementioned group problems, there can be three categories: Conventional NSG...