Science and Technology Production
Article
Authorship
Date
2015
Publishing House and Editing Place
Elsevier
Magazine
COMPUTERS AND CHEMICAL ENGINEERING,
vol. 72
(pp. 350-362)
Elsevier
Summary
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SIGEVA
This paper presents a novel column generation algorithm for managing the logistics activities performed by a fleet of multi-parcel chemical tankers. In our procedure, for providing elementary routes, the conventional dynamic programming routes-generator is replaced by an efficient continuous-time MILP-slave problem. The performance of the decomposition method is evaluated by solving several examples dealing with the operations of a shipping company operating in the Asia Pacific Region. Computat...
This paper presents a novel column generation algorithm for managing the logistics activities performed by a fleet of multi-parcel chemical tankers. In our procedure, for providing elementary routes, the conventional dynamic programming routes-generator is replaced by an efficient continuous-time MILP-slave problem. The performance of the decomposition method is evaluated by solving several examples dealing with the operations of a shipping company operating in the Asia Pacific Region. Computational results show that the proposed approach outperforms a pure exact optimization model and an alternative heuristic solution method reported in the literature.
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Key Words
Ship routing and schedulingTramp shippingMILP slave formulationColumn generation
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