Model and Algorithm for Passenger Station Task Allocation Problem in Railway Terminal

ICCTP 2010 ◽  
2010 ◽  
Author(s):  
Yu Li ◽  
Jun Zhao ◽  
Jie Cheng
1994 ◽  
Vol 03 (01) ◽  
pp. 47-60
Author(s):  
R.A. McCONNELL ◽  
B.L. MENEZES

This article compares three techniques for allocating tasks in a mesh-based multi-computer. Tasks are expressed as rectangles of a certain width and height corresponding to the topology of processors desired. The task allocation problem, is thus a variant of the bin-packing problem, with one major difference: in the bin-packing problem one seeks to minimize the height of the bin, while here we seek to maximize the utilization of processors in a multicomputer. The three techniques compared are a classical level-by-level algorithm, a connectionist simulated annealing variant of the Hopfield network, and a genetic algorithm. An extension to the dynamic processor allocation problem is modeled by fixing some rectangles in place and packing the request rectangles in the residual space on the mesh; this corresponds to a pre-existing condition, i.e., some tasks have already been allocated to the Processor Mesh. Implementation and experimental results are presented.


Robotica ◽  
2021 ◽  
pp. 1-25
Author(s):  
An Zhang ◽  
Mi Yang ◽  
Bi Wenhao ◽  
Fei Gao

Abstract This paper considers the task allocation problem under the requirement that the assignments of some critical tasks must be maximized when the network capacity cannot accommodate all tasks due to the limited capacity for each unmanned aerial vehicle (UAV). To solve this problem, this paper proposes an extended performance impact algorithm with critical tasks (EPIAC) based on the traditional performance impact algorithm. A novel task list resizing phase is developed in EPIAC to deal with the constraint on the limited capacity of each UAV and maximize the assignments of critical tasks. Numerical simulations demonstrate the outstanding performance of EPIAC compared with other algorithms.


1992 ◽  
Vol 39 (3) ◽  
pp. 502-518 ◽  
Author(s):  
A. Billionnet ◽  
M. C. Costa ◽  
A. Sutter

Sign in / Sign up

Export Citation Format

Share Document