In this study, we deal with a real-world problem on oil & gas upstream logistics, comprehending the transport of goods from ports to maritime units, through vessels called Platform Supply Vessels (PSVs). We present an integrated methodology to define the routes of these vessels and port schedules in a three-phase framework. In the first phase, we decompose the problem using a clustering heuristic and then solve periodic supply vessel routing problems for each cluster. The second phase employs a mixed-integer programming model for port scheduling and berth allocation. Finally, in the third phase, given port departure Supply vessel planning and port scheduling in O&G supply logistics times, the routes are re-sequenced to respect opening time constraints at installations, aiming to reduce waiting times and to balance the intervals between successive services. The framework was validated and evaluated considering a real scenario from an industrial partner located in Rio de Janeiro, Brazil. The experiments' results revealed that the framework could consistently and significantly outperform the solution adopted by the company in terms of economic costs.
In this study, we deal with a real-world problem on oil & gas upstream logistics, comprehending the transport of goods from ports to maritime units, through vessels called Platform Supply Vessels (PSVs). We present an integrated methodology to define the routes of these vessels and port schedules in a three-phase framework. In the first phase, we decompose the problem using a clustering heuristic and then solve periodic supply vessel routing problems for each cluster. The second phase employs a mixed-integer programming model for port scheduling and berth allocation. Finally, in the third phase, given port departure Supply vessel planning and port scheduling in O&G supply logistics times, the routes are re-sequenced to respect opening time constraints at installations, aiming to reduce waiting times and to balance the intervals between successive services. The framework was validated and evaluated considering a real scenario from an industrial partner located in Rio de Janeiro, Brazil. The experiments' results revealed that the framework could consistently and significantly outperform the solution adopted by the company in terms of economic costs.
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