Warianty tytułu
Języki publikacji
Abstrakty
The second most important function of a warehouse, apart from the storing of goods, is internal transport with a focus on time-effectiveness. When there is a time gap between the production and export of products, the goods need to be stored until they are dispatched to the consumers. An important problem that concerns both large and small warehouses is the selection of priorities, that is handling the tasks in order of importance. Another problem is to identify the most efficient routes for forklift trucks to transport goods from a start-point to a desired destination and prevent the routes from overlapping. In automated warehouses, the transport of objects (the so called pallets of goods) is performed by machines controlled by a computer instead of a human operator. Thus, it is the computer, not the man, that makes the difficult decisions regarding parallel route planning, so that the materials are transported within the warehouse in near-optimal time. This paper presents a method for enhancing this process. (original abstract)
Czasopismo
Rocznik
Tom
Numer
Strony
33--44
Opis fizyczny
Twórcy
- Lodz University of Technology, Poland
Bibliografia
- [1] Harmon L.D., Artificial Neuron, Science, 129, 3354, 962-963, 1959.
- [2] Hassoun M., Fundamentals of Artificial Neural Networks, Massachusetts Institute of Technology, 2003.
- [3] Braspenning P.J., Thuijsman F., Weijters A.J.M.M., Artificial Neural Networks: An Introduction to ANN Theory and Practice, Lecture Notes in Computer Science, Springer, 1995.
- [4] Ma Y., Zhan K., Wang Z., Applications of Pulse-Coupled Neural Networks, Springer, 2011.
- [5] Lindbland T., Kinser J.M., Image Processing using Pulse-Coupled Neural Networks: Applications in Python, Springer, 1997.
- [6] Miao H., Tian Y., Dynamic robot path planning using an enhanced simulated annealing approach, Applied Mathematics and Computation, 222, 420-437, 2013.
- [7] Lee M., Lee Y., Rittenhouse R.G., A genetic algorithm for PDA optimal path generation using GPS, Applied Soft Computing, 12, 2379-2386, 2012.
- [8] Roth U., Walker M., Hilman A., Klar H., Dynamic Path Planning with Spiking Neutral Networks, Lecture Notes in Computer Science, Computer Science Logic, 2007.
- [9] Effati S., Jafarzadeh M., Nonlinear neural networks for solving the shortest path problem, Applied Mathematics and Computation, 189, 567-574, 2007.
- [10] Yang S.X., Meng M., An efficient neural network method for real-time motion planning with safety consideration, Robotics and Autonomous Systems, 32, 115-128, 2000.
- [11] Davoodi M., Abedin M., Banyassady B., Khanteimouri P., Mohades A., An optimal algorithm for two robots path planning problem on the grid, Robotics and Autonomous Systems, 61, 1406-1414, 2013.
- [12] Chong J.W.S., Ong S.K., Nee A.Y.C., Youcef-Youmi K., Robot programming using augmented reality: An interactive method for planning collision free paths, Robotics and Computer-Integrated Manufacturing, 25, 689-701, 2009.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171327609