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A discrete Bat Algorithm for the vehicle routing problem with time windows

机译:带时间窗的车辆路径问题的离散蝙蝠算法

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Bat Algorithm (BA) is a new bio-inspired meta-heuristic based on the echolocation behavior of microbats when searching for their prey in nature. Since its first implementation in 2010, BA has been used to solve a broad range of continuous optimization problems. In this paper, we present a new hybrid algorithm that executes a discrete version of the bat algorithm in combination with the Large Neighborhood Search (LNS) framework to solve the well-known Vehicle Routing Problem with Time Windows (VRPTW). Our proposed algorithm, named BA-LNS aims at enhancing the performance of the discrete BA using the destroy and repair paradigm of the LNS, allowing the bat to discover a large part of the solution space. To justify that our proposal is a promising approximation algorithm, we tested its performance on 56 instances of Solomon's benchmark and compared the convergence with the best-known solutions in the literature. Computational results indicate that our proposed approach has a satisfactory performance in solving VRPTW instances.
机译:蝙蝠算法(BA)是一种新型的启发式元启发式算法,基于微蝙蝠在自然界中寻找猎物时的回声定位行为。自2010年首次实施以来,BA已用于解决广泛的连续优化问题。在本文中,我们提出了一种新的混合算法,该算法结合大邻居搜索(LNS)框架执行bat算法的离散版本,以解决众所周知的带有时间窗的车辆路径问题(VRPTW)。我们提出的名为BA-LNS的算法旨在使用LNS的破坏和修复范例来增强离散BA的性能,从而使蝙蝠能够发现很大一部分解决方案空间。为了证明我们的建议是一种有前途的近似算法,我们在所罗门基准测试的56个实例上测试了该算法的性能,并将其收敛性与文献中最著名的解决方案进行了比较。计算结果表明,我们提出的方法在解决VRPTW实例方面具有令人满意的性能。

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