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New method optimizes resource handover policies using evolutionary algorithms

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method for optimizing resource allocation in business processes by creating resource-specific handover policies. This approach combines a multi-agent system simulator with a multi-objective evolutionary algorithm to generate Pareto-optimal policies. Experiments on synthetic and real-world data demonstrated significant improvements, reducing costs by an average of 37% and waiting times by 58% compared to existing methods. AI

IMPACT Introduces a novel approach to optimize business process resource allocation, potentially improving efficiency and reducing costs in real-world applications.

RANK_REASON The cluster contains a research paper detailing a new methodology for multi-objective optimization. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New method optimizes resource handover policies using evolutionary algorithms

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The cluster contains a research paper detailing a new methodology for multi-objective optimization. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Hugo A. López ·

    From Global Policies to Local Strategies: Multi-Objective Optimization of Resource-Specific Handover Policies

    Efficient resource allocation is a key challenge in business process management, with direct implications for cost, throughput time, and utilization. While recent Reinforcement Learning (RL) approaches have shown promise in deriving adaptive allocation policies, they typically ne…

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