scholarly journals A modified greedy algorithm for the task assignment problem.

2007 ◽  
Author(s):  
Allison Douglas
Keyword(s):  
Greedy Algorithm ◽  
Assignment Problem ◽  
Task Assignment ◽  
Task Assignment Problem

Quadratic Convex Reformulation for Solving Task Assignment Problem with Continuous Hopfield Network

2021 ◽  
Author(s):  
Youssef Hami ◽  
Chakir Loqman
Keyword(s):  
Assignment Problem ◽  
Optimal Allocation ◽  
Task Assignment ◽  
Hopfield Network ◽  
Quadratic Program ◽  
Convex Objective Function ◽  
Calculation Results ◽  
Quadratic Convex Reformulation ◽  
Task Assignment Problem ◽  
Theoretical Results

This research is an optimal allocation of tasks to processors in order to minimize the total costs of execution and communication. This problem is called the Task Assignment Problem (TAP) with nonuniform communication costs. To solve the latter, the first step concerns the formulation of the problem by an equivalent zero-one quadratic program with a convex objective function using a convexification technique, based on the smallest eigenvalue. The second step concerns the application of the Continuous Hopfield Network (CHN) to solve the obtained problem. The calculation results are presented for the instances from the literature, compared to solutions obtained both the CPLEX solver and by the heuristic genetic algorithm, and show an improvement in the results obtained by applying only the CHN algorithm. We can see that the proposed approach evaluates the efficiency of the theoretical results and achieves the optimal solutions in a short calculation time.

scholarly journals Multi-UAV Rapid-Assessment Task-Assignment Problem in a Post-Earthquake Scenario

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 74542-74557 ◽  
Author(s):  
Moning Zhu ◽  
Xiaoxia Du ◽  
Xuehua Zhang ◽  
He Luo ◽  
Guoqiang Wang
Keyword(s):  
Assignment Problem ◽  
Rapid Assessment ◽  
Task Assignment ◽  
Earthquake Scenario ◽  
Assessment Task ◽  
Task Assignment Problem ◽  
Multi Uav

scholarly journals Research on the Task Assignment Problem with Maximum Benefits in Volunteer Computing Platforms

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 862
Author(s):  
Ling Xu ◽  
Jianzhong Qiao ◽  
Shukuan Lin ◽  
Xiaowei Wang
Keyword(s):  
Assignment Problem ◽  
Low Cost ◽  
Task Assignment ◽  
Task Completion ◽  
Volunteer Computing ◽  
Computing Services ◽  
Pruning Strategy ◽  
Computing Platforms ◽  
Deadline Constraints ◽  
Task Assignment Problem

As a type of distributed computing, volunteer computing (VC) has provided unlimited computing capacity at a low cost in recent decades. The architecture of most volunteer computing platforms (VCPs) is a master–worker model, which defines a master–slave relationship. Therefore, VCPs can be considered asymmetric multiprocessing systems (AMSs). As AMSs, VCPs are very promising for providing computing services for users. Users can submit tasks with deadline constraints to the VCPs. If the tasks are completed within their deadlines, VCPs will obtain the benefits. For this application scenario, this paper proposes a new task assignment problem with the maximum benefits in VCPs for the first time. To address the problem, we first proposed a list-based task assignment (LTA) strategy, and we proved that the LTA strategy could complete the task with a deadline constraint as soon as possible. Then, based on the LTA strategy, we proposed a maximum benefit scheduling (MBS) algorithm, which aimed at maximizing the benefits of VCPs. The MBS algorithm determined the acceptable tasks using a pruning strategy. Finally, the experiment results show that our proposed algorithm is more effective than current algorithms in the aspects of benefits, task acceptance rate and task completion rate.

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