Multi-objective shortest path problem (MOSP) plays an important role
in practical applications, which seeks for the efficient paths satisfying
several conflicting objectives between two nodes of a network. In
this paper, we present an algorithm based on Physarum Polycephalum
model to solve the bi-objective shortest path problem. By aggregating
the two attributes into one by weighted sum, we successfully convert the
bi-objective shortest path problem (BOSP) into the shortest path problem.
Here, in order to reduce the computational time, binary weight
allocation (BWA) technique is implemented to distribute the weight for
each criterion. To cheek the quality of the proposed method and the
accuracy of the algorithm, experimental analyzes are conducted. Random
networks are generated to verify the accuracy of the proposed algorithm.
Results on the testing problems are compared with label correcting
algorithm known as an efficient algorithm for solving the BOSP. The
results demonstrate the proposed Physarum Polycephalum optimization
algorithm can produce the non-dominated solutions successfully when
dealing with the BOSP.
Keywords: Shortest path problem,physarum polycephalmn, pareto frontiers, bi-objective
shortest path problem