Traveling Baseball Players' Problem in Korea

We study the so-called the traveling tournament problem (TTP), to find an optimal tournament schedule. Differently from the original TTP, in which the total travel distance of all the participants is the objective function to minimize, we instead seek to maximize the fairness of the round robin tournament schedule of the Korean Baseball League. The standard deviation of the travel distances of teams is defined as the energy function, and the Metropolis Monte-Carlo method combined with the simulated annealing technique is applied to find the ground state configuration. The resulting tournament schedule is found to satisfy all the constraint rules set by the Korean Baseball Organization, but with drastically increased fairness in traveling distances.Comment: 8 pages, 4 figure

Mixed integer programming in production planning with backlogging and setup carryover : modeling and algorithms

This paper proposes a mixed integer programming formulation for modeling the capacitated multi-level lot sizing problem with both backlogging and setup carryover. Based on the model formulation, a progressive time-oriented decomposition heuristic framework is then proposed, where improvement and construction heuristics are effectively combined, therefore efficiently avoiding the weaknesses associated with the one-time decisions made by other classical time-oriented decomposition algorithms. Computational results show that the proposed optimization framework provides competitive solutions within a reasonable time

Platooning of Automated Ground Vehicles to Connect Port and Hinterland: A Multi-objective Optimization Approach

Automated ground vehicles (AGVs) are essential parts of container operations at many ports. Forming platoons—as conceptually established in trucking—may allow these vehicles to directly cater demand points such as dry ports in the hinterland. In this work, we aim to assess such AGV platoons in terms of operational efficiency and costs, considering the case of the Port of Rotterdam. We propose a multi-objective mixed-integer programming model that minimizes dwell and idle times, on the one hand, and the total cost of the system involving transportation, labor, and platoon formation costs, on the other hand. To achieve Pareto optimal solutions that capture the trade-offs between minimizing cost and time, we apply an augmented epsilon constraint method. The results indicate that all the containers are delivered by AGVs. This not only shortens the dwell time of the containers by decreasing loading/unloading processes and eliminating stacking but also leads to considerable cost savings.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport Engineering and Logistic

The Lockmaster's Problem

Inland waterways form a natural network infrastructure with capacity for more traffic. Transportation by ship is widely promoted as it is a reliable, efficient and environmental friendly way of transport. Nevertheless, locks managing the water level on waterways and within harbors sometimes constitute bottlenecks for transportation over water. The lockmaster's problem concerns the optimal strategy for operating such a lock. In the lockmaster's problem we are given a lock, a set of upstream-bound ships and another set of ships traveling in the opposite direction. We are given the arrival times of the ships and a constant lockage time; the goal is to minimize total waiting time of the ships. In this paper, a dynamic programming algorithm is proposed that solves the lockmaster's problem in polynomial time. This algorithm can also be used to solve a single batching machine scheduling problem more efficiently than the current algorithms from the literature do. We extend the algorithm such that it can be applied in realistic settings, taking into account capacity, ship-dependent handling times, weights and water usage. In addition, we compare the performance of this new exact algorithm with the performance of some (straightforward) heuristics in a computational study