multi-objective evolutionary algorithms (MOEA) typically utilize non-dominated sorting to provide a number of Pareto solutions for decision-makers rather than converting all objectives into a single-objective function. Thus, this optimization technique has become more popular with researchers...
(3) The individuals generated by the two methods were sorted according to the value of fitness, and the N individuals with the highest fitness were selected to form the initial population. 3.3. Adaptive weight The strategy of weight is very common in particle swarm optimization algorithm. ...
The second heuristic is a greedy algorithm. In this case, if a product cannot be assigned to a bundle because of capacity limitations, the bundle is not closed. Rather, the following products may be assigned to this bundle (if this was possible considering the maximum distance and capacity)....