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The multiport container ship stowage problem consists in determining the position of the containers on board a ship along its route with the objective of minimizing the number of unproductive moves required in the loading and unloading operations at each port. This paper presents an integer programming model for the problem and proposes several sets of valid constraints that bring its LP-relaxation closer to an integer solution. Moreover, it presents a GRASP algorithm that generates stowage plans with a minimal number of unproductive moves in a high percentage of medium and large-size instances. An extended computational analysis has been performed in which, to the best of the authors' knowledge, the efficiency of integer programming models for the problem is tested for the first time. With respect to GRASP, the computational results show that it performs well on different sized datasets. [ABSTRACT FROM AUTHOR]

This work presents a generalization of the Slot Planning Problem which raises when the liner shipping industry needs to plan the placement of containers within a vessel (stowage planning). State-of-the-art stowage planning relies on a heuristic decomposition where containers are first distributed in clusters along the vessel. For each of those clusters a specific position for each container must be found. Compared to previous studies, we have introduced two new features: the explicit handling of rolled out containers and the inclusion of separations rules for dangerous cargo. We present a novel integer programming formulation and a Greedy Randomized Adaptive Search Procedure (GRASP) to solve the problem. The approach is able to find high-quality solution within 1 s. We also provide comparison with the state-of-the-art on an existing and a new set of benchmark instances. [ABSTRACT FROM AUTHOR]

Efficient routing and scheduling are critical for providing patients with quality health care in their homes, and palliative care involves specific requirements. This paper addresses the Palliative Home Health Care Routing and Scheduling Problem (PHHCRSP) through an integrated mathematical model. Key considerations include caregiver skills, care continuity, and a multi-period planning horizon. Special attention is also given to the case of clustered patients. Five formulations with different objective functions are analyzed and solutions reveal that optimizing only for minimum or maximum workload leads to non-efficient routing. The formulation that balances the total workload and the minimum workload emerges as the most effective, as it manages to obtain good routes while distributing the workload evenly among the caregivers. The results of the computational study on a set of well-known benchmark instances show that it is possible to obtain good patient care while keeping good working conditions for the caregivers. • We address the Palliative Home Health Care Routing and Scheduling Problem (PHHCRSP). • We develop and analyze five formulations with alternative objective functions. • We present valid constraints that improve the problem formulations. • The most effective formulation balances both the total and the minimum workload. • An extensive computational study is conducted on well-known benchmark instances. [ABSTRACT FROM AUTHOR]