Explicit building-block multiobjective evolutionary algorithms for NPC problems

This research emphasizes explicit building block (BB) based MOEA performance with detailed symbolic representations. An explicit BB-based MOEA for solving constrained and real-world multiple objective problems (MOPs) is developed, the multiobjective messy genetic algorithm II (MOMGA-II) in order to validate symbolic BB concepts. This algorithm provides insight into solving difficult NP-complete MOPs that are generally not realized through the use of implicit BB-based MOEA approaches. Specific constrained integer problem examples include advanced logistics and modified knapsack problems. A primary focus is on generic repair mechanisms for generating feasible solutions per generation. The insight provided is necessary to increase the effectiveness and efficiency over all possible MOEA approaches.