基于元启发式方法的自杀式恐怖袭击探测器最优布置新视角

我们考虑一种自杀式恐怖袭击的作战模型——这种形式的恐怖主义日益普遍——针对特定目标，以及基于探测器部署来实施防御措施的方案。这些探测器必须仔细布置，以最小化预期的人伤 casualties 或经济损失， resulting in a hard optimization problem， for which different metaheuristics have been proposed。 Rather than assuming random decisions by the attacker, the problem is approached by considering different models of the latter, whereby he takes informed decisions on which objective must be targeted and through which path it has to be reached based on knowledge on the importance or value of the objectives or on the defensive strategy of the defender (a scenario that can be regarded as an adversarial game)。我们考虑四种不同算法，即贪心启发式方法、爬坡法、禁忌搜索和遗传算法，并研究它们在旨在模拟不同真实情景的广泛问题实例上的表现，这些情景包括沿海地区、现代城市地区以及历史古城的核心区域。结果表明，对抗情景对所有技术都更具挑战性，而遗传算法似乎更适应于由此产生的搜索景观的复杂性。