نبذة مختصرة : Vehicle routing problems occur in many practical situations where the distribution of goods and / or services to different demand points is necessary. In this context, this research aims to study a ship routing and scheduling problem that arises at the collection and delivery operations of different types of crude oil from offshore platforms to coastal terminals. In the paradigm adopted for the representation of the problem, the transportation is largely the result of the need to maintain inventories at each supply point (platforms) between minimum and maximum levels, considering production rates on these operating points and the demand attendance of each product in the coastal terminals. The routing and scheduling of the fleet aims to achieve minimum variable cost solutions, and considers various operational constraints, such as the maximum cargo volume transported on each ship, the ships mooring in the operational points ports, the simultaneous unloading of the ships in terminals with more than one berth, among many others. In this research, Inventory Constrained Routing Problem (ICRP) models in the maritime context have been modified and extended for appropriately representating and solving real problems based on data collected in a case study performed on a Brazilian oil company, involving relatively short distances and time horizons. Small sized instances are solved by a mathematical programming software. Given the difficulties of solving larger examples, this study proposes a multistart heuristic method that includes a metaheuristic GRASP and improvement procedures, and also a rolling horizon heuristic. Both methods provide feasible good quality solutions in reasonable computing times. In order to improve the quality of the solutions found by these constructive methods, it is also discussed a procedure that combines the mathematical programming software and local search heuristic methods (matheuristic). The results show the potential of the proposed models and solution methods to tackle the problem and ...
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