Peng Sun

Post-Doc Operations and Supply Chain Management

Publications

Copy reference link   DOI: 10.1016/j.ejor.2017.07.004

Abstract: We introduce the time-dependent capacitated profitable tour problem with time windows and precedence constraints. This problem concerns determining a tour and its departure time at the depot that maximizes the collected profit minus the total travel cost (measured by total travel time). To deal with road congestion, travel times are considered to be time-dependent. We develop a tailored labeling algorithm to find the optimal tour. Furthermore, we introduce dominance criteria to discard unpromising labels. Our computational results demonstrate that the algorithm is capable of solving instances with up to 150 locations (75 pickup and delivery requests) to optimality. Additionally, we present a restricted dynamic programing heuristic to improve the computation time. This heuristic does not guarantee optimality, but is able to find the optimal solution for 32 instances out of the 34 instances.

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Copy reference link   DOI: 10.1016/j.matcom.2013.03.005

Abstract: In this paper, a ship lock scheduling problem is investigated. Ships arrive randomly over time, and the instantaneous arrival rates are allowed to vary both temporally and stochastically in an arbitrary manner. A data-driven approach is applied to a single ship lock scheduling, which is a typical optimizing and decision-making problem. The objective is to minimize the operation costs and other costs(e.g. water cost, electricity cost, and staff welfare cost) by selecting an appropriate slot number during a planned period. The convergence of data-driven approach is discussed from three aspects: the convergence of ant colony optimization algorithm, the convergence of the proposed algorithm, and the error between the historical ship data and the current arrival ship data. The research findings are beneficial for the convergence analysis of data-driven theory and the management of waterway transportation.

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Copy reference link   DOI: 10.1515/IJNSNS.2010.11.6.411

Abstract: This paper investigates traffic states and queuing occurring in water transportation. A scheduling model with a single ship lock is proposed, which is a typical optimization and decision-making model. Transportation states change randomly and stochastically. The objective is to minimize the operation cost and other costs (e.g. water cost, electricity cost, and staff welfare cost) by selecting an appropriate slot number in a planning period. A data-driven approach is proposed for solving this problem based on the previous transportation data, accordingly a detailed ship scheduling plan is obtained using the ant colony optimization algorithm. Finally a numerical example is given to demonstrate the efficiency of the proposed approach. This research results are helpful to transportation management.

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