AOF-Based Algorithm for Dynamic Multi-Objective Distributed Constraint Optimization

摘要: Many real world problems involve multiple criteria that should be considered separately and optimized simultaneously. A Multi-Objective Distributed Constraint Optimization Problem MO-DCOP is the extension of a mono-objective DCOP. DCOP fundamental problem can formalize various applications related to multi-agent cooperation. This consists set agents, each which needs decide value assignment its variables so sum resulting rewards maximized. An involves criteria. Most researches have focused on developing algorithms for solving static problems. However, many are dynamic. In this paper, we focus change criteria/objectives model Dynamic DMO-DCOP defined by sequence MO-DCOPs. Furthermore, develop novel algorithm DMO-DCOPs. The characteristics as follows: i it reused finds Pareto optimal solutions all MO-DCOPs in using information previous solutions, ii utilizes Aggregate Objective Function AOF technique widely used classical method find iii complexity determined induced width instances.