Algoritma Differential Evolution Untuk Penjadwalan Flow Shop Banyak Mesin Dengan Multi Obyektif

Abstract

This research focuses on the development of Differential Evolution(DE) algorithmto solve m-machine flow shop
scheduling problems with respect to both makespan and total flow time. Development of DE algorithm is done by modifying
the adaptive parameter determination procedure in order to change the value of adaptive parameters in each generation,
adding local search strategy to the algorithm in order to improve the quality of the resulting solutions, as ewell as modifying
the crossover in order to reduce computation time. The result indicates that the proposed DE algorithm has proven to be
better than the original DE algorithm, Genetic Algorithm (GA), and for certain cases it also out performs Multi-Objective
Ant Colony System Algorithm (MOCSA).