— This paper describes two performance measures for measuring an EMO (Evolutionary Multiobjective Optimization) algorithm’s ability to track a time-varying Paretofront in a dyn...
In this paper, we present an approach that extends the Particle Swarm Optimization (PSO) algorithm to handle multiobjective optimization problems by incorporating the mechanism of...
This paper proposes a method to use reference points as preferences to guide a particle swarm algorithm to search towards preferred regions of the Pareto front. A decision maker c...
This paper introduces a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO), consisting of a combination of the Variable Neighborhood Search (VNS) ...
— Many optimisation problems are multi-objective and change dynamically. Many methods use a weighted average approach to the multiple objectives. This paper introduces the usage ...