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Solving Deadlock Problem for Consensus-Based Bundle Algorithm in Distributed Systems With Practical Fuel Consumption Evaluation
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DOI：10.1002/asjc.70239.png)
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Abstract
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This paper proposes the Deadlock-Free Consensus-Based Bundle Algorithm (DF-CBBA) to address deadlock in distributed multi-agent task allocation problems with practical fuel consumption evaluation. A more practical optimization problem, which intentionally violates the Diminishing Marginal Gains (DMG) property, is formulated by enhancing the fuel consumption penalty within the time-window task allocation framework. Under this formulation, the marginal benefit of a task is no longer computed using a pre-defined objective function formula. Instead, it is derived from the actual increase in the overall objective value resulting from the task's insertion. The critical innovation of the proposed DF-CBBA is a redesigned bidding strategy equipped with adaptive conflict-resolution mechanisms, enabling agents to dynamically re-evaluate task valuations during the bundle construction phase. Theoretical analysis and simulation results validate the performance of the algorithm.
Keywords:
deadlock resolution
diminishing marginal gains
distributed task allocation
practical constraint
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