Randomized time-varying knapsack problems via binary beetle antennae search algorithm: Emphasis on applications in portfolio insurance

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.

Automated summary

In this paper, the knapsack problem is transformed into the TV-ILP problem, presenting an online solution to the RTVKP combinatorial optimization problem and emphasizing the limitations of static methods. The RTVKP is also utilized in finance and tested with real-world data sets to demonstrate it as an excellent alternative to traditional approaches.