Objective increment based hybrid GA for no-wait flowshops

No-wait flowshops with flowtime minimization are typical NP-complete combinatorial optimization problems, widely existing in practical manufacturing systems. Different from traditional methods by which objective of a new schedule being completely computed objective increment methods are presented in this paper by which the objective of an offspring being obtained just by objective increments and computational time can be considerably reduced. HGAI (hybrid GA based on objective increment) is proposed by integrating genetic algorithm with a local search method. A heuristic is constructed to generate an individual of initial population and a crossover operator is introduced for mating process. HGAI is compared with two best so far algorithms for the considered problem on 110 benchmark instances. Computational results show that HGAI outperforms the existing two in effectiveness with a little more computation time.