scholarly journals A Balanced Heuristic Mechanism for Multirobot Task Allocation of Intelligent Warehouses

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Luowei Zhou ◽  
Yuanyuan Shi ◽  
Jiangliu Wang ◽  
Pei Yang
Keyword(s):  
Mobile Robots ◽  
Task Allocation ◽  
System Performance ◽  
Travel Cost ◽  
Allocation Problem ◽  
Good System ◽  
Allocation Methods

This paper presents a new mechanism for the multirobot task allocation problem in intelligent warehouses, where a team of mobile robots are expected to efficiently transport a number of given objects. We model the system with unknown task cost and the objective is twofold, that is, equally allocating the workload as well as minimizing the travel cost. A balanced heuristic mechanism (BHM) is proposed to achieve this goal. We raised two improved task allocation methods by applying this mechanism to the auction and clustering strategies, respectively. The results of simulated experiments demonstrate the success of the proposed approach regarding increasing the utilization of the robots as well as the efficiency of the whole warehouse system (by 5~15%). In addition, the influence of the coefficientαin the BHM is well-studied. Typically, this coefficient is set between 0.7~0.9 to achieve good system performance.

EVALUATION OF TASK ALLOCATION IN MESH-BASED MULTICOMPUTERS USING GENETIC, NEURAL, AND TRADITIONAL ALGORITHMS

1994 ◽  
Vol 03 (01) ◽  
pp. 47-60
Author(s):  
R.A. McCONNELL ◽  
B.L. MENEZES
Keyword(s):  
Task Allocation ◽  
Bin Packing ◽  
Packing Problem ◽  
Allocation Problem ◽  
Hopfield Network ◽  
Processor Allocation ◽  
Classical Level ◽  
Bin Packing Problem ◽  
Residual Space ◽  
Computer Tasks

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.

Distributed task allocation with critical tasks and limited capacity

Robotica ◽  
2021 ◽  
pp. 1-25
Author(s):  
An Zhang ◽  
Mi Yang ◽  
Bi Wenhao ◽  
Fei Gao
Keyword(s):  
Numerical Simulations ◽  
Unmanned Aerial Vehicle ◽  
Task Allocation ◽  
Network Capacity ◽  
Allocation Problem ◽  
Limited Capacity ◽  
Performance Impact ◽  
Task List ◽  
Aerial Vehicle ◽  
Traditional Performance

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.

An efficient algorithm for a task allocation problem

1992 ◽  
Vol 39 (3) ◽  
pp. 502-518 ◽  
Author(s):  
A. Billionnet ◽  
M. C. Costa ◽  
A. Sutter
Keyword(s):  
Task Allocation ◽  
Efficient Algorithm ◽  
Allocation Problem
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