Computer Science ›› 2018, Vol. 45 ›› Issue (4): 240-246.doi: 10.11896/j.issn.1002-137X.2018.04.040

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Greedy Randomized Adaptive Search Procedure Algorithm Combining Set Partitioning for Heterogeneous School Bus Routing Problems

HOU Yan-e, KONG Yun-feng and DANG Lan-xue   

  • Online:2018-04-15 Published:2018-05-11

Abstract: In practice of school bus route planning,there are a variety of planning applications with different optimization objectives under the types of school buses constraints.This paper dealt with a class of heterogeneous school bus routing problem(HSBRP) with different objectives.A greedy randomized adaptive search procedure(GRASP) algorithm combining set partition(SP) procedure was proposed in this paper.First,the routes generated in the execution of GRASP are used to build the set partition model,and then the model is solved by the CPLEX optimization software.To keep the algorithm suitable for different HSBRP problems,the initialization solution generation procedure of GRASP is adapted for these problems to obtain a valid solution,and the routes of this initialization solution are put into the route pool.In the local search phase,the many neighborhood operators and variable neighborhood descent procedure are executed for improving the solution.At the same time,the routes of the solution that is improved and the best local optimization in every iteration are both put into the route pool.The test results on the benchmark datasets show that the SP procedure of the proposed algorithm can improve the quality and stability of the algorithm.The proposed algorithm can effectively solve two types of HSBRP with different objectives,and it is effective when compared with the existing HSBRP algorithms.

Key words: Heterogeneous school bus routing problem,Set partitioning,Greedy randomized adaptive search procedure,Hybrid meta-heuristic

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