Two Ant Algorithms Based on DEA in Flexible Flow Shops

This paper addresses to flexible flow shops environment with sequence dependant setup times and considers a scheduling problem with the aim of minimizing makespan andcumulative tardiness, simultaneously. In this paper we developed two new different ant algorithms, ACO and MMAS, based onData Envelopment Analysis (DEA). We considered each artificial ant as a Decision Making Unit (DMU) with two inputs, makespanand cumulative tardiness, and an output, equal to one for all of them. For developing the method we used the efficiency concept and efficient frontier of DEA

Keywords:

data envelopment analysis , decision making unit , effiCiency , flexible flow shops , ant algorithm