Interactive Evolutionary Computation Approach to Permutation Flow Shop Scheduling Problem

Artificial intelligence and its subfields have be-come part of our everyday lives and eÿciently solve many problems that are very hard for us humans. But in some tasks, these methods strug-gle, while we, humans, are much better solvers with our intuition. Because of that, the ques-tion arises: why not combine intelligent methods with human skills and intuition? This paper pro-poses an Interactive Evolutionary Computation approach to the Permutation Flow Shop Schedul-ing Problem by incorporating human-in-the-loop in MAX-MIN Ant System through gamification of the problem. The analysis shows that combin-ing the evolutionary computation approach and human-in-the-loop leads to better solutions, sig-nificantly when the complexity of the problem in-creases.