@article{MAKHILLIJSC201510121254,
    title = {Hybrid Multi-Objective Workflow Scheduling on Utility Grids},
    journal = {International Journal of Soft Computing},
    volume = {10},
    number = {1},
    pages = {6-18},
    year = {2015},
    issn = {1816-9503},
    doi = {ijscomp.2015.6.18},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2015.6.18},
    author = {Sunita and},
    keywords = {NSGA-II,hybrid,ranking,workflow,scheduling},
    abstract = {Workflow scheduling is solved using heuristics and meta-heuristics. Heuristics are used to get an optimal solution while meta-heuristics are used to get near optimal solution. Meta-heuristics are general purpose method of solving different types of problem. This study puts Double Hybrid Multi-objective Non-Dominated Sorting Genetic Algorithm (DHNSGA-II) that gears up the convergence of the algorithm. DHNSGA-II does hybridization at two levels. At the first level it uses pre-selection operator. At the second level it uses Memetic algorithm. Pre-selection operator seeds the DHNSGA-II with the previously generated solutions. Memetic algorithm improves the current population using multi-objective local search. Apart from DHSNGA-II researchers introduced an approach to rank the Pareto frontiers because Pareto frontier has many solutions; it is nearly impossible to choose the best solution. The experimental result reveals that the proposed approach in this research performs well in optimizing the workflow scheduling jobs.}
    }