A multi-objective paradigm arises a viable approach to solving complex problems of optimization based on integrating multiple disciplines. This paper sets forth a new multi-objective teaching–learning-based optimization (short for MTLBO) for the issue of automotive fuel consumption. The vehicle’s fuel consumption is related to the cost of traveling by gasoline and the current traffic conditions, e.g., congestion, roads. The least use of fuel and the shortest routes are modeled as the objective functions for candidates’ solutions on the automobile navigation route. A road transportation system is built based on wireless sensor network (WSN)-fitted sensor nodes and the car fitted with the global positioning system (GPS). The results of the simulation are contrasted with the approaches of the Dijkstra and the A* algorithm. Results from experiments show that the proposed method increases precision.


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    Title :

    Multi-Objective Teaching–Learning-Based Optimization for Vehicle Fuel Saving Consumption


    Additional title:

    Advs in Intelligent Syst., Computing



    Conference:

    Congress on Intelligent Systems ; 2020 ; New Delhi, India September 05, 2020 - September 06, 2020



    Publication date :

    2021-06-02


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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