Developing two multi-objective algorithms for solving multi-objective flexible job shop scheduling problem considering total consumed power per month

In this paper, to make flexible job shop scheduling problem (FJSP) more realistic, an operational factor is considered in its model. This factor, which is called optimizing total consumed electric power per month, is known as the most important factor in calculation of the electric cost of the industries. Considering this factor, specifically after subsides elimination of the country, has became more important. In addition to this objective, two other common objectives, called complementation time and critical work load of machines, are considered. To solve the multi-objective model, two algorithms, called multi-objective biogeography-based optimization algorithm (MOBBO) and multi-objective harmony search algorithm (MOHS), are developed and introduced to scheduling area for the first time. Finally, by developing some famous libraries of the problem, performance of the algorithms is compared statistically.