In contrast to vehicle routing problems, little work has been done in ship routing and scheduling, although large benefits may be expected from improving this scheduling process. We will present a real ship planning problem, which is a combined inventory management problem and a routing problem with time windows. A fleet of ships transports a single product (ammonia) between production and consumption harbors. The quantities loaded and discharged are determined by the production rates of the harbors, possible stock levels, and the actual ship visiting the harbor. We describe the real problem and the underlying mathematical model. To decompose this model, we discuss some model adjustments. Then, the problem can be solved by a Dantzig–Wolfe decomposition approach including both ship routing subproblems and inventory management subproblems. The overall problem is solved by branch-and-bound. Our computational results indicate that the proposed method works for the real planning problem.
Railned is an independent organization that advises the Dutch government on investments in future railway infrastructure. It generates and evaluates infrastructural scenarios that stem from the government's objectives and those of the operators of the railway network, the Dutch railway company Nederlandse Spoorwegen (NS) being by far the largest. The government and the railway operators often have different objectives, which may conflict sometimes. The government finances and manages the infrastructure, and wants to meet certain social and environmental priorities, thereby not exceeding budget limits. The operators exploit the infrastructure and wish to have a dependable infrastructure that guarantees long-term profitability. Railned uses various decision support systems (DSS) to develop and analyze infrastructural scenarios that yield win-win solutions for both the Dutch government and the railway operators.
In this paper the problem of scheduling train crew is considered. We discuss a general framework of which the method for solving the train crew scheduling problem is a special case. In particular, our method is a heuristic branch-and-price algorithm suitable for large scale crew scheduling problems. This algorithm is applied to a real life train guard scheduling problem which is provided to us by the Dutch Railways. Computational results show that our algorithm is capable of getting sub-optimal solutions for a large scale instance within reasonable computation time.
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