Abstract Transportation services are crucial for any supply chain as these services deliver raw and intermediate materials to manufacturers and deliver finished goods to retailers and end customers. The present work focuses on the freight transportation adopted by an Indian food grain supply chain. The problem can be considered as a single-source multiple-destination distribution-allocation problem. Three penalty factors have been introduced to quantitatively represent the risk of incurrence of demurrage cost, to match time of supply and release of food grains and to maintain uniform capacity utilization throughout the network of depots. A multi-objective model is formulated with an objective to minimize these penalty factors. The model is solved using elitist non-dominated sorting genetic algorithm (NSGA II)-based heuristic. The solutions obtained prove the fast-converging nature of NSGA II algorithm.


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    Title :

    Elitist Non-dominated Sorting Genetic Algorithm-Based Heuristic for Optimizing Rail Freight Transportation


    Contributors:


    Publication date :

    2018-11-05


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English