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The rapid advance in technology allows logistics companies to tackle with dynamic nature of distribution networks (e.g., a change in the vehicle speed due to unexpected events). The planned routes at the beginning of the time horizon could be subject to modification at any point in time to account for the recent traffic information. This study addresses a dynamic open time\u2010dependent traveling salesman problem. The problem also involves speed optimization that aims to find optimal vehicle speed in a dynamic setting by respecting real\u2010time traffic conditions. We develop a mixed integer linear programming (MILP) formulation for the addressed problem to determine routing and vehicle speed decisions. Furthermore, a MILP\u2010based myopic\u2010clustering decomposition heuristic algorithm has been introduced to solve large\u2010sized instances within reasonable solution times. 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