The knapsack problem is a problem in combinatorial optimization, and in many such problems, exhaustive search is not tractable. In this paper, we describe and analyze the randomized time‐varying knapsack problem (RTVKP) as a time‐varying integer linear programming (TV‐ILP) problem. In this way, we present the on‐line solution to the RTVKP combinatorial optimization problem and highlight the restrictions of static methods. In addition, the RTVKP is applied in the field of finance and converted into a portfolio insurance problem. Our methodology is confirmed by simulation tests in real‐world data sets, in order to explain being an excellent alternative to traditional approaches.

中文翻译：

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通过二进制甲虫天线搜索算法的随时间变化的背包问题：强调在证券保险中的应用

背包问题是组合优化中的一个问题，在许多这样的问题中，穷举搜索是难以处理的。在本文中，我们将随机时变背包问题（RTVKP）描述为时变整数线性规划（TV-ILP）问题并进行分析。这样，我们提出了针对RTVKP组合优化问题的在线解决方案，并强调了静态方法的局限性。此外，RTVKP还应用于金融领域，并转化为证券投资问题。我们的方法已通过现实世界数据集中的模拟测试得到证实，目的是解释它是传统方法的绝佳替代方案。