عنوان مقاله [English]
Vehicle Routing Problem (VRP) wasone of the mostpopular
optimization problems that hadmany usages for productivity and
efficiency of transportation systems in recent decades.The Vehicle
Routing Problem with Simultaneous pick-up and deliveries (VRP/SPD),
which considers simultaneous distribution and collection of goods
from/to customers (VRP/SDP/SDC) was a variant of the classical vehicle
routing problem where customers require simultaneous pick-up and
delivery at their locations to be completed within a specified time.
Applications of the SPD and its related variants are commonly come
across in every day transportation and optimizing logistic planning. This
paper had used Meta-heuristic to this end. The proposed method was
applied for solving capacitated vehicle routing problem (CVRP) to
improve the distribution efficiency and productivity with an objective of
minimizing the total distance covered in each route, while considering
the capacity of different routes. This problemwas essentially an NP-Hard
in nature, so there was no known optimal solution method with
polynomial time. To solve this NP-hard VRP a hybrid genetic based
algorithm was developed. The proposed geneticalgorithm was tested on
some standardproblem with respect to computational efficiency and
solution quality. The presented method was implemented and its
performance was further investigated by comparing it against existing
heuristics for the same problem. Theresults showed that the success of
the proposed approach in handling the difficult problem constraints and
devising simple and robust solution mechanisms that can be integrated
with routing optimization tools and used in real world applications.
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