STUDS MATING IMMIGRANTS IN EVOLUTIONARY ALGORITHM TO SOLVE THE EARLINESS-TARDINESS SCHEDULING PROBLEM

Current trends in manufacturing are focused on just-in-time production which emphasizes policies discouraging earliness as well as tardiness of job completion. New trends to enhance evolutionary algorithms introduced multiple-crossovers-on-multiple-parents (MCMP) a multirecombinative approach allowing multiple crossovers on the selected pool of (more than two) parents. As a novel variant, MCMP-SRI considers the inclusion of a stud-breeding individual in a pool of random immigrant parents. Members of this mating pool subsequently undergo multiple crossover operations. This paper describes implementation and performance of MCMP-SRI when solving diverse instances of the earliness-tardiness problem in a single machine environment.