Abstract
From the perspective of supply-side reform in China, it is hard for COSCO Shipping, a merged company with a strong shipping capacity, to abandon the container shipping market. Meanwhile, the new company could cooperate with new strategic ports along the Maritime Silk Road in liner service. Against this backdrop, this paper aims to optimize the liner shipping network (LSN) from strategic, tactical, and operational levels and help the merged shipping company adjust its operational measures according to market changes. The optimization towards different levels of decision-making process is a new research of highly practical values. Specifically, this paper created two-phase optimization models for LSN based on the selection of hub ports. In Network Assessment (NA) phase, the LSNs of two types of hub ports selected are designed and assessed on strategic and tactical levels, and the primary and secondary routes are identified; in Network Operation (NO) phase, the “path-based flow” formulations are proposed from the operational level, considering operational measures including demand rejection and flow integration. The models in both phases are mixed-integer linear programming (MILP), but are solved by different tools: CPLEX for the NA phase models and the Genetic Algorithm (GA) for the NO phase models due to the computational complexity of the latter problem. Then, a computational experiment is performed on the LSN of COSCO Shipping on the Persian Gulf trade lane. The results have proved the effectiveness of the methodology and inspired important countermeasures for the merged shipping company.
Highlights
From the perspective of supply-side reform in China, it is hard for China Ocean Shipping Company (COSCO) Shipping, a merged company with a strong shipping capacity, to abandon the container shipping market
This paper aims to optimize the liner shipping network (LSN) from strategic, tactical, and operational levels and help the merged shipping company adjust its operational measures according to market changes. e optimization towards different levels of decision-making process is a new research of highly practical values
E optimization models for both phases are mixed-integer linear programming (MILP). e models in the Network Assessment (NA) phase are programmed in CPLEX, and those in the Network Operation (NO) phase are solved by a Genetic Algorithm (GA)-based algorithm
Summary
We consider the LSN optimization for a shipping company in the context of supply-side reform, typically a merger or acquisition. NA and NO phases after a merger are analyzed: selecting the most profitable route in the NA phase from all the similar preset routes that have been designed by different acquired shipping companies, and figuring out the optimal plan of flowing cargoes in the NO phase according to the actual shipping market. Erefore, for shipping company C that can either cooperate with THP or EHP, it is necessary to assess the profitability of the preset routes in order to make adjustment plans. In the NO phase, in order to start operation in practice, shipping company C needs to depict more detailed plans on how to adjust cargo flows, which involve how to pick up, unload, and transship containers at any port of call according to the actual market situation. For each O-D pair, shipping company C in the NO phase needs to figure out how many containers to be transported through s1o d and s2o d and how many containers to be rejected
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