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Highlights • We optimize shipping schedule for steel plants cluster alongside inland river. • The model considers timely demands of steel plants over multiple periods. • A MIP formulation and dynamic programming algorithm are developed. • We explore the iron ore trade volume under various scenarios. Abstract This paper aims to provide an optimal shipping schedule for steel-manufacturing plants cluster alongside the Yangtze River by developing a mixed integer programming formulation. The model takes into account the multi-layer shipping network on the Yangtze River, the dynamic iron ore price and transportation costs, and the timely demands of steel plants over multiple periods. By applying the proposed model to a real-world case, several interesting findings are observed, leading to further useful managerial insights. We also propose an exact solution approach based on a dynamic programming algorithm to a special case of this problem motivated by real-world practice. [ABSTRACT FROM AUTHOR]

The ultrasonic guided wave technique is extensively used for nondestructive structural testing, and one of the key steps is to extract a single mode with certain purity from multi-order mixed modes. In this paper, the propagation of ultrasonic guided waves in the cylindrical rod is simulated first; the appropriate broadband excitation signal is selected to excite the multi-order modes in a specific frequency range; and the time–space signal containing multi-order modes is converted to the frequency-wavenumber domain signal by two-dimensional Fourier transform. In the frequency-wavenumber domain, the frequency-wavenumber ridge is extracted from the multi-mode frequency-wavenumber domain based on the dynamic programming method, and then the time-domain signal corresponding to a single mode can be reconstructed. By comparing the excited multi-order mode and the separated single mode with the theoretical results, it is observed that the two results are consistent. Thus, the employed mode-excitation method can accurately excite the multi-order modes in rod structures. Furthermore, the proposed method enables the separation of a single-mode wave with high purity, providing a foundation for future utilization of isolated modes. [ABSTRACT FROM AUTHOR]

Highlights • Consider a stochastic bulk ship scheduling problem in industrial shipping that has never been addressed in the literature but has real impact in the shipping market. • Develop a two-step solution scheme consisting of a dynamic programming algorithm and a tailored Benders decomposition method to solve the problem effectively. • Conduct extensive numerical experiments to demonstrate that proposed solution method can well solve the considered problem in various and practical sizes. Abstract This paper studies a ship scheduling problem for an industrial corporation that manages a fleet of bulk ships under stochastic environments. The considered problem is an integration of three interconnected sub-problems from different planning levels: the strategic fleet sizing and mix problem, the tactical voyage planning problem, and the operational stochastic backhaul cargo canvassing problem. To obtain the optimal solution of the problem, this paper provides a two-step algorithmic scheme. In the first step, the stochastic backhaul cargo canvassing problem is solved by a dynamic programming (DP) algorithm, leading to optimal canvassing strategies for all feasible voyages of all ships. In the second step, a mixed-integer programming (MIP) model that jointly solves the fleet sizing and mix problem and the voyage planning problem is formulated using the results from the first step. To efficiently solve the proposed MIP model, this paper develops a tailored Benders decomposition method. Finally, extensive numerical experiments are conducted to demonstrate the applicability and efficiency of the proposed models and solution methods for practical instances. [ABSTRACT FROM AUTHOR]