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Diversity-based adaptive genetic algorithm for a Workforce Scheduling and Routing Problem

机译:基于多样性的劳动力调度和路径自适应遗传算法

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The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across various geographical locations. Solving this problem demands tackling numerous scheduling and routing constraints while aiming to minimise total operational cost. One of the main obstacles in designing a genetic algorithm for this highly-constrained combinatorial optimisation problem is the amount of empirical tests required for parameter tuning. This paper presents a genetic algorithm that uses a diversity-based adaptive parameter control method. Experimental results show the effectiveness of this parameter control method to enhance the performance of the genetic algorithm. This study makes a contribution to research on adaptive evolutionary algorithms applied to real-world problems.
机译:劳动力调度和路由问题是指人员在不同地理位置的访问。解决该问题需要解决众多的调度和路由约束,同时旨在使总运营成本最小化。针对此高度受限的组合优化问题设计遗传算法的主要障碍之一是参数调整所需的经验测试量。本文提出了一种遗传算法,该算法使用基于分集的自适应参数控制方法。实验结果表明,该参数控制方法有效地提高了遗传算法的性能。这项研究为应用于实际问题的自适应进化算法的研究做出了贡献。

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