A Cooperative Learning Approach for the Quadratic Knapsack Problem

摘要

The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has several applications in different fields such as telecommunications, graph theory, logistics, hydrology and data allocation, among others. In this paper, we propose the application of a novel population-based metaheuristic referred to as Multi-leader Migrating Birds Optimization (MMBO), which exploits the concepts of cooperation and communication along the search leading to a collective learning, to solve a wide range of well-known QKP instances.