The Scientific World Journal / 2014 / Article / Alg 2

Research Article

Multiobjective Memetic Estimation of Distribution Algorithm Based on an Incremental Tournament Local Searcher

Algorithm 2

The details of MMEDA.
Step  1. Initialization: Set , generate initial population P(0) and evaluate it.
Step  2. Update non-dominated population: Identify non-dominated solutions from population P(t), and update archive N(t)
by dominance.
Step  3. Termination: If is satisfied, export N(t) as the output of the algorithm, and Stop, else go to step 3.
Step  3. ITLS: Perform incremental tournament local searcher to generate new solutions (t).
Step  4. Modeling: Perform the (m-1)-d local PCA to partition P(t) into disjoint clusters . For each cluster ,
build model (2) by (4) and (5).
Step  5. Sampling: Sample new population O(t) from model (2) and evaluate O(t).
Step  6. Update current population: select solutions from to create .
Step  7. set and go to Step 2.

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