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While members contribute to the attainment of the system-level goal, complementariness of task division and the efficiency of task allocation have become the main needs.
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Both ways of task allocation can lead to cost-efficiency but they are difficult to combine.
In this paper we present several solutions to the problem of task allocation among autonomous agents, and suggest that the agents form coalitions in order to perform tasks or improve the efficiency of their performance.
The pattern of task allocation is close to that of task division because it has to solve the allocation problems based on task division (Puranam et al., 2014).
Table 1 Accuracy and efficiency of task performance Pt.
Overall productivity is given by the number of grafting units, the number of robotic modules implemented in the supply system, and the efficiency of the control and task allocation strategy.
Performance of the task allocation scheme in terms of energy balancing and scheduling length objectives.
Fig. 1 An illustration of the task allocation problem.
Most of them rather consider static task allocation instead of focusing on distributed task scheduling.
Fig. 5 Convergence of multi-objective fitness function of genetic algorithm-based task allocation.
Using exact schedulability tests increases the efficiency of these allocation algorithms, but the execution cost to validate a task partition is also greatly increased.
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