Abstract

Acommon problem faced by carriers in liner shipping is the design of their service network. Given a set of demands to be transported and a set of ports, a carrier wants to design service routes for its ships as efficiently as possible, using the underlying facilities. Furthermore, the profitability of the service routes designed depends on the paths chosen to ship the cargo. We present an integrated model, a mixed-integer linear program, to solve the ship-scheduling and the cargo-routing problems, simultaneously. The proposed model incorporates relevant constraints, such as the weekly frequency constraint on the operated routes, and emerging trends, such as the transshipment of cargo between two or more service routes. To solve the mixed-integer program, we propose algorithms that exploit the separability of the problem. More specifically, a greedy heuristic, a column generation-based algorithm, and a two-phase Benders decomposition-based algorithm are developed, and their computational efficiency in terms of the solution quality and the computational time taken is discussed. An efficient iterative search algorithm is proposed to generate schedules for ships. Computational experiments are performed on randomly generated instances simulating real life with up to 20 ports and 100 ships. Our results indicate high percentage utilization of ships' capacities and a significant number of transshipments in the final solution.

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