A Hybrid Predictive Strategy Carried through Simultaneously from Decision Space and Objective Space for Evolutionary Dynamic Multiobjective Optimization

Algorithm 6

A hybrid predictive strategy carried through simultaneously from decision space and objective space.

Initialization: number of time change, ; generation counter, ; total generation

number, .

Step 1: Initialize the population, .

Step 2: Detect the environmental change. If no change, go to step 8;

else, calculate the non-dominated set in the current population.

Step 3: If t=1, go to step 1.

Step 4: Select randomly individuals from non-dominated set, as memory set, ;

Step 5: According to Algorithm 4, get the non-dominated set in t+1 time step,

and its size, .

Step 6: According to Algorithm 5, get the random set, .

Step 7: Get the predicted population in the new environment by equation ().

              ()

Step 8: The optimization algorithm   [51] is used to optimize the problem.

Step 9: If , output , and then end; else, gt:=gt+1; go to step 2.