Hybrid Heuristics and Metaheuristics for Solving Combinatorial Optimization Problems

The presentation focuses on the application of hybrid heuristics and metaheuristics to address several combinatorial optimization problems. Specifically, we discuss three optimization problems: the Multidimensional Knapsack Problem (MKP), the Knapsack Sharing Problem (KSP), and the K-Traveling Repairman Problem (K-TRP). In order to tackle these problems, we introduce a set of heuristics and metaheuristics, namely the Filter-and-Fan (F&F) metaheuristic, the Iterative Linear Programming-based Heuristic (ILPH), and the Quantum Particle Swarm Optimization metaheuristic (QPSO).
Throughout the presentation, we provide insights into the application of these approaches and discuss their performance on the MKP, KSP, and K-TRP problems. We showcase their ability to handle complex combinatorial optimization scenarios and present empirical results highlighting their effectiveness.