Abstract:One indicator for efficient management in a port is the time spent by a ship in the port quays. The time allowed for loading-unloading into a specialized quay is mentioned in the management contract. Because the cost of the overtime is very high, it is very important to have a special plan to unload the container ship in a short time. Given the number of containers to be unloaded from a vessel and the initial state (in regards of number of slots) of a block, the genetic algorithm that we propose in this paper finds the plan of container stacking in the block, whilst the objective function is to minimize summation of handling time of yard crane in placing the containers in the available storage cells of the stacking area. The performance of the proposed method is evaluated through several sets of tests on control parameters of the algorithm.
In 1980 S.P. Han proposed a finitely terminating (in exact arithmetic) algorithm for solving an inconsistent system of linear inequalities in a least squares sense. This algorithm uses a singular value decomposition of a submatrix of the problem matrix on each iteration, making it impractical for all but only smaller problems. In this paper we show that a modification of Han's algorithm allows us to introduce an iterative approximation to the singular value decomposition solution.
At each port of destination, some containers are unloaded from a vessel and stored in the terminal to be delivered to their customers. One of the strategies used to arrange the containers in a terminal is residence time strategy: based on their delivery deadlines, each incoming container being assigned to a priority class. The aim of this study is to determine a valid arrangement of incoming containers in a block (part) of the terminal, in the shortest amount of time, with higher priority containers located above lower priority ones. In this way, some of the main objectives of a container terminal may be achieved: avoiding further reshuffles (number of relocations) and reducing the vessel berthing time. We developed a genetic algorithm and its performance is evaluated against a random stacking strategy used as benchmark for the experiments, and through several sets of tests on control parameters. All the tests showed that, if a reliable estimation of the delivery time can be assigned to every incoming container, the proposed method may be a useful tool for container terminal operators.
In this paper we present a modified version of S. P. Han iterative method for solving inconsistent systems of linear inequalities. Our method uses an iterative Kaczmarz-type solver to approximate the minimal norm least squares solution of the problems involved in each iteration of Han’s algorithm. We prove some convergence properties for the sequence of approximations generated in this way and present numerical experiments and comparisons with Han’s and other direct solver based methods for inconsistent linear inequalities.
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