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This paper proposes a new parallel search procedure for dynamic multi-objective traveling salesman problem. We design a multi-objective TSP in a stochastic dynamic environment. The proposed procedure first uses parallel processors to identify the extreme solutions of the search space for each of k objectives individually at the same time. These solutions are merged into a matrix E. The solutions in E are then searched by parallel processors and evaluated for dominance relationship. The proposed procedure was implemented in two different ways: a master-worker architecture and a pipeline architecture.