Improvements for multi-objective flow shop scheduling by Pareto Iterated
  Local Search
  The article describes the proposition and application of a local search
metaheuristic for multi-objective optimization problems. It is based on two
main principles of heuristic search, intensification through variable
neighborhoods, and diversification through perturbations and successive
iterations in favorable regions of the search space. The concept is
successfully tested on permutation flow shop scheduling problems under multiple
objectives and compared to other local search approaches. While the obtained
results are encouraging in terms of their quality, another positive attribute
of the approach is its simplicity as it does require the setting of only very
few parameters.
