The cross-docking system is a new distribution strategy which can reduce inventories, lead times, and improve responding time\nto customers. This paper considers biobjective problem of truck scheduling in cross-docking systems with temporary storage.\nThe objectives are minimizing both makespan and total tardiness. For this problem, it proposes a multiobjective iterated greedy\nalgorithmemploying advance features such asmodified crowding selection, restart phase, and local search. To evaluate the proposed\nalgorithm for performance, it is compared with two available algorithms, subpopulation particle swarm optimization-II and\nstrength Pareto evolutionary algorithm-II.Thecomparison shows that the proposedmultiobjective iterated greedy algorithmshows\nhigh performance and outperforms the other two algorithms.
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